The University of Memphis

Graduate Teaching Assistant

- Prepare and Grade Homework for "Signals and Systems" Course in undergrad for Fall 2010 and Spring 2011.
- Grade the Homework for "Probabilistic System Analysis" course in undergrad for Spring 2010.
- Maintain grades for online assignments for "Introduction to Engineering" course.

The University of Memphis

Ph.D. in Computer Science

-Works on different federal funded projects (IARPA, FEMA, NSF) on computer and network security to provide a better security for the organizations.
-Involved in different projects in the areas of data mining, machine learning, mathematical modeling, biometric authentication, multi-objective optimization, and big data analytics.
-Works as a guest lecturer on Network/Internet Security (COMP 7327/8327), Computer Security (COMP 4410/6410), and Computer Forensics (COMP 7125) courses.
-Mentors a team of undergraduate students in their final year Capstone Project (COMP 4882) to design, analysis and implement an android based mobile application.
-Work as a subject matter expert(SME) to update different course contents supported by TEEX and FEMA.
-Prepare course outlines for an online based course titled "Cyber Identity and Authentication".
The details will be found at http://www.memphis.edu/cfia/student-success/a-mfa-framework.php.
CS department at The University of Memphis also highlighted in Spring 2017 NewsLetter:
http://www.memphis.edu/cs/pdfs/newsletter_w17.pdf

The University of Memphis

Graduate Research Assistant

I am a graduate student of the University of Memphis in the department of Electrical and Computer Engineering Department. I work in CVPIA lab(http://cvpia.memphis.edu).
My areas of interest:
- Medical Informatics
- Machine Learning and Data Mining
- Parallel and Distributive Computing

• Implemented retrieval system of clinical data using Matlab, Perl and R.
• Developed web service to display the input query and result of the retrieval as well as providing query suggestions.
• Collaborated with Bioinformatics group to develop the gene information extraction system from PubMED website.
• Upgraded and maintained the research lab website (http://cvpia.memphis.edu/) using MySQL and Drupal.

The University of Memphis

Graduate Research Assistant

Working at Center for Information Assurance (CfIA) [http://www.memphis.edu/cfia/] as a researcher and be part of a wide variety of projects that address the current security challenges and foster the current ongoing demand of security research, education, and outreach.

The University of Memphis

Graduate Research Assistant Funded by IARPA

This project is to design and implement an immune-inspired Negative Authentication System (NAS) by providing a robust solution to immunizing authentication systems (local or remote) through putting an additional invisible layer of password protection to the user.
The poster for this project is found in the following link:
https://www.dropbox.com/s/grxz7g7ffldo8cf/CfIA_poster01_1118.pdf
Accomplishments:
-Developed Binary space, Real space, and Grid space based representation of the NAS using Java, MySQL, ArcSight logger as a lead software developer. This developed authentication system, later was integrated with Microsoft Windows authentication (Active Directory) using pGina.
-Developed test scenarios using JUnit framework to check the business logic of the system.
-Implemented multi-threaded version in Binary space and Real space model to reduce the required run-time up to 40% from previous implementations.

The University of Memphis

Graduate Teaching Assistant

I worked as a teaching assistant in Discrete structures course (COMP 2700) for about 68 students in Spring 2014. My duties as TA are following:
- Prepare the homework and exam questions.
- Grade the Homeworks, Midterms, and Final exams.
- Conduct some classes if required.
- Assist the students to understand the course materials and class quizzes.

FedEx Services

Software Developer- Testing and Remediation as a Consultant

-Working in J2EE platform using Hibernate and EJB module based on the clients’ software requirements.
-Designed use-cases, test-cases and fit-cases testscripts to check the business logic and perform remediation of code if necessary.
- Use Bugzilla to report the existing bug in code and provide remediation with the testscripts to generate the same bug.
- Designed different modules for RCP client and integrate with the weblogic server.

Texas A&M University-Central Texas

Assistant Professor

Teaching:
Taught undergraduate and graduate-level courses in face-to-face and online settings, including but not limited to:
-Computer Security Fundamentals
-Computer and Network Security
-IT security and Risk Management
-Applied Security
-Comprehensive Networking
-Data Communications and Infrastructure
-Object-Oriented Programming
-Website Design and Development
Also advice Computer Science/CIS students on a regular basis.
Research:
-publish research articles in journals and conferences.
-serve as an invited reviewer for various journals and conferences including
-European Journal of Operational Research (EJOR)
-Evolutionary Computation Journal (ECJ)
-Elsevier Journal of Computers & Security (COSE)
-Information Sciences (INS)
- Soft Computing
- World Multi-Conference on Systemics, Cybernetics and Informatics (WMSCI)
- IEEE Symposium Series on Computational Intelligence (SSCI)
- Hawaii International Conference on System Sciences (HICSS)
- IEEE INFOCOM
- IEEE International Conference on Computing, Networking and Communications (ICNC)

Interviewed with local news channel KXXV on Cybersecurity awareness and user privacy on social apps.
https://www.kxxv.com/hometown/bell-county/popular-faceapp-poses-cybersecurity-concerns

https://www.facebook.com/2132927123588934/posts/2337027903178854?s=100002653522575&v=e&sfns=cl

Received a TEES grant (2019-2022 period) as a lead PI for the project titled "Powering up: Cybersecurity Education for a Dispersed Workforce ".
Partnering Institutions:
Prairie View A&M University;
Texas A&M University-Commerce;
Texas A&M University-Texarkana; and
Texas A&M University-San Antonio
URL: https://tarc.tamu.edu/funded-collaborations/

Human-Cognition- Based CAPTCHAs

IEEE

CAPTCHAs play a significant role in differentiating humans and machines in any Web-based authentication process. With technological advances in text recognition and image extraction, it's now possible to extract the characters shown in a CAPTCHA with satisfactory accuracy. CAPTCHAs were introduced to cope with the immense threat to online authentication systems, but interpreting them becomes harder for regular Internet users every day. The authors' alternative CAPTCHA provides a variety of mathematical, logical, and inference problems that only humans can understand and answer correctly. The proposed framework supports question diversity and a user-friendly interface. The authors' informal user study evaluates the developed system's performance with different backgrounds. The study shows the efficacy of the implemented system with a good level of user satisfaction.

An Adaptive Approach Towards the Selection of Multi-factor Authentication

IEEE

Authentication is the fundamental defense against any illegitimate access to a computing device or any sensitive online applications. Due to recent trends of emerging security threats, authentication using only a single factor is not reliable to provide adequate protection for these devices and applications. Hence, to facilitate continuous protection of computing devices and other critical online services from an un-authorized access, multi-factor authentication emerges as a viable option. Many authentication mechanisms with varying degrees of accuracy and portability are available for different types of computing devices connected with various communicating media. As a consequence, several existing and well-known multi-factor authentication strategies have already been utilized to enhance the security of various applications. Keeping this in mind, this research is focused on designing a robust and scalable framework for authenticating a legitimate user efficiently through a subset of available authentication modalities along with their several features (authentication factors) in time-varying operating environments (devices, media and surrounding conditions) on a regular basis. This paper highlights the creation of a trustworthy framework to quantify different authentication factors in terms of selection of different types of devices and media. In addition, a novel adaptive selection strategy for the available authentication factors incorporating the trustworthy values, previous history of selection as well as surrounding conditions is proposed in the paper. Selection through adaptive strategy ensures the incorporation of the existing environmental conditions within the selection of authentication factors and provides better diversity in the selection of these factors.

Human-Cognition- Based CAPTCHAs

IEEE

CAPTCHAs play a significant role in differentiating humans and machines in any Web-based authentication process. With technological advances in text recognition and image extraction, it's now possible to extract the characters shown in a CAPTCHA with satisfactory accuracy. CAPTCHAs were introduced to cope with the immense threat to online authentication systems, but interpreting them becomes harder for regular Internet users every day. The authors' alternative CAPTCHA provides a variety of mathematical, logical, and inference problems that only humans can understand and answer correctly. The proposed framework supports question diversity and a user-friendly interface. The authors' informal user study evaluates the developed system's performance with different backgrounds. The study shows the efficacy of the implemented system with a good level of user satisfaction.

An Adaptive Approach Towards the Selection of Multi-factor Authentication

IEEE

Authentication is the fundamental defense against any illegitimate access to a computing device or any sensitive online applications. Due to recent trends of emerging security threats, authentication using only a single factor is not reliable to provide adequate protection for these devices and applications. Hence, to facilitate continuous protection of computing devices and other critical online services from an un-authorized access, multi-factor authentication emerges as a viable option. Many authentication mechanisms with varying degrees of accuracy and portability are available for different types of computing devices connected with various communicating media. As a consequence, several existing and well-known multi-factor authentication strategies have already been utilized to enhance the security of various applications. Keeping this in mind, this research is focused on designing a robust and scalable framework for authenticating a legitimate user efficiently through a subset of available authentication modalities along with their several features (authentication factors) in time-varying operating environments (devices, media and surrounding conditions) on a regular basis. This paper highlights the creation of a trustworthy framework to quantify different authentication factors in terms of selection of different types of devices and media. In addition, a novel adaptive selection strategy for the available authentication factors incorporating the trustworthy values, previous history of selection as well as surrounding conditions is proposed in the paper. Selection through adaptive strategy ensures the incorporation of the existing environmental conditions within the selection of authentication factors and provides better diversity in the selection of these factors.

Human-Cognition- Based CAPTCHAs

IEEE

CAPTCHAs play a significant role in differentiating humans and machines in any Web-based authentication process. With technological advances in text recognition and image extraction, it's now possible to extract the characters shown in a CAPTCHA with satisfactory accuracy. CAPTCHAs were introduced to cope with the immense threat to online authentication systems, but interpreting them becomes harder for regular Internet users every day. The authors' alternative CAPTCHA provides a variety of mathematical, logical, and inference problems that only humans can understand and answer correctly. The proposed framework supports question diversity and a user-friendly interface. The authors' informal user study evaluates the developed system's performance with different backgrounds. The study shows the efficacy of the implemented system with a good level of user satisfaction.

An Adaptive Approach Towards the Selection of Multi-factor Authentication

IEEE

Authentication is the fundamental defense against any illegitimate access to a computing device or any sensitive online applications. Due to recent trends of emerging security threats, authentication using only a single factor is not reliable to provide adequate protection for these devices and applications. Hence, to facilitate continuous protection of computing devices and other critical online services from an un-authorized access, multi-factor authentication emerges as a viable option. Many authentication mechanisms with varying degrees of accuracy and portability are available for different types of computing devices connected with various communicating media. As a consequence, several existing and well-known multi-factor authentication strategies have already been utilized to enhance the security of various applications. Keeping this in mind, this research is focused on designing a robust and scalable framework for authenticating a legitimate user efficiently through a subset of available authentication modalities along with their several features (authentication factors) in time-varying operating environments (devices, media and surrounding conditions) on a regular basis. This paper highlights the creation of a trustworthy framework to quantify different authentication factors in terms of selection of different types of devices and media. In addition, a novel adaptive selection strategy for the available authentication factors incorporating the trustworthy values, previous history of selection as well as surrounding conditions is proposed in the paper. Selection through adaptive strategy ensures the incorporation of the existing environmental conditions within the selection of authentication factors and provides better diversity in the selection of these factors.

Human-Cognition- Based CAPTCHAs

IEEE

CAPTCHAs play a significant role in differentiating humans and machines in any Web-based authentication process. With technological advances in text recognition and image extraction, it's now possible to extract the characters shown in a CAPTCHA with satisfactory accuracy. CAPTCHAs were introduced to cope with the immense threat to online authentication systems, but interpreting them becomes harder for regular Internet users every day. The authors' alternative CAPTCHA provides a variety of mathematical, logical, and inference problems that only humans can understand and answer correctly. The proposed framework supports question diversity and a user-friendly interface. The authors' informal user study evaluates the developed system's performance with different backgrounds. The study shows the efficacy of the implemented system with a good level of user satisfaction.

An Adaptive Approach Towards the Selection of Multi-factor Authentication

IEEE

Authentication is the fundamental defense against any illegitimate access to a computing device or any sensitive online applications. Due to recent trends of emerging security threats, authentication using only a single factor is not reliable to provide adequate protection for these devices and applications. Hence, to facilitate continuous protection of computing devices and other critical online services from an un-authorized access, multi-factor authentication emerges as a viable option. Many authentication mechanisms with varying degrees of accuracy and portability are available for different types of computing devices connected with various communicating media. As a consequence, several existing and well-known multi-factor authentication strategies have already been utilized to enhance the security of various applications. Keeping this in mind, this research is focused on designing a robust and scalable framework for authenticating a legitimate user efficiently through a subset of available authentication modalities along with their several features (authentication factors) in time-varying operating environments (devices, media and surrounding conditions) on a regular basis. This paper highlights the creation of a trustworthy framework to quantify different authentication factors in terms of selection of different types of devices and media. In addition, a novel adaptive selection strategy for the available authentication factors incorporating the trustworthy values, previous history of selection as well as surrounding conditions is proposed in the paper. Selection through adaptive strategy ensures the incorporation of the existing environmental conditions within the selection of authentication factors and provides better diversity in the selection of these factors.

Design and implementation of Negative Authentication System

Springer

Modern society is mostly dependent on online activities like official or social communications, fund transfers and so on. Unauthorized system access is one of the utmost concerns than ever before in cyber systems. For any cyber system, robust authentication is an absolute necessity for ensuring security and reliable access to all type of transactions. However, more than 80% of the current authentication systems are password based, and surprisingly, they are prone to direct and indirect cracking via guessing or side channel attacks. The inspiration of Negative Authentication System (NAS) is based on the negative selection algorithm. In NAS, the password-based authentication data for valid users are termed as password profile or self-region (positive profile); any element other than the self-region is defined as non-self-region in the same representative space. The anti-password detectors are generated which covers most of the non-self-region. There are also some uncovered regions left in the non-self-region for inducing uncertainty to the attackers. In this work, we describe the design and implementation of three approaches of NAS and its efficacy over the other authentication methods. These three approaches represent three different ways to achieve obfuscation of password points with non-password space. The experiments are conducted with both real and simulated password profiles to justify the efficiency of different implementations of NAS.

Human-Cognition- Based CAPTCHAs

IEEE

CAPTCHAs play a significant role in differentiating humans and machines in any Web-based authentication process. With technological advances in text recognition and image extraction, it's now possible to extract the characters shown in a CAPTCHA with satisfactory accuracy. CAPTCHAs were introduced to cope with the immense threat to online authentication systems, but interpreting them becomes harder for regular Internet users every day. The authors' alternative CAPTCHA provides a variety of mathematical, logical, and inference problems that only humans can understand and answer correctly. The proposed framework supports question diversity and a user-friendly interface. The authors' informal user study evaluates the developed system's performance with different backgrounds. The study shows the efficacy of the implemented system with a good level of user satisfaction.

An Adaptive Approach Towards the Selection of Multi-factor Authentication

IEEE

Authentication is the fundamental defense against any illegitimate access to a computing device or any sensitive online applications. Due to recent trends of emerging security threats, authentication using only a single factor is not reliable to provide adequate protection for these devices and applications. Hence, to facilitate continuous protection of computing devices and other critical online services from an un-authorized access, multi-factor authentication emerges as a viable option. Many authentication mechanisms with varying degrees of accuracy and portability are available for different types of computing devices connected with various communicating media. As a consequence, several existing and well-known multi-factor authentication strategies have already been utilized to enhance the security of various applications. Keeping this in mind, this research is focused on designing a robust and scalable framework for authenticating a legitimate user efficiently through a subset of available authentication modalities along with their several features (authentication factors) in time-varying operating environments (devices, media and surrounding conditions) on a regular basis. This paper highlights the creation of a trustworthy framework to quantify different authentication factors in terms of selection of different types of devices and media. In addition, a novel adaptive selection strategy for the available authentication factors incorporating the trustworthy values, previous history of selection as well as surrounding conditions is proposed in the paper. Selection through adaptive strategy ensures the incorporation of the existing environmental conditions within the selection of authentication factors and provides better diversity in the selection of these factors.

Design and implementation of Negative Authentication System

Springer

Modern society is mostly dependent on online activities like official or social communications, fund transfers and so on. Unauthorized system access is one of the utmost concerns than ever before in cyber systems. For any cyber system, robust authentication is an absolute necessity for ensuring security and reliable access to all type of transactions. However, more than 80% of the current authentication systems are password based, and surprisingly, they are prone to direct and indirect cracking via guessing or side channel attacks. The inspiration of Negative Authentication System (NAS) is based on the negative selection algorithm. In NAS, the password-based authentication data for valid users are termed as password profile or self-region (positive profile); any element other than the self-region is defined as non-self-region in the same representative space. The anti-password detectors are generated which covers most of the non-self-region. There are also some uncovered regions left in the non-self-region for inducing uncertainty to the attackers. In this work, we describe the design and implementation of three approaches of NAS and its efficacy over the other authentication methods. These three approaches represent three different ways to achieve obfuscation of password points with non-password space. The experiments are conducted with both real and simulated password profiles to justify the efficiency of different implementations of NAS.

G-NAS: A Grid-Based Approach for Negative Authentication

Symposium on Computational Intelligence in Cyber Security (CICS) at IEEE Symposium Series on Computational Intelligence (SSCI)

Surveys show that more than 80% authentication systems are password based and these systems are increasingly under direct and indirect attacks. In an effort to protect the Positive Authentication System (PAS), the negative authentication concept was introduced [9]. Here, the representation space of password profile is called self-region; any element outside this self-region is defined as the non-self-region. Then anti-password detectors (clusters) are generated covering most of the non-selfregion while leaving some space uncovered to reduce detector generation time and obfuscation. In this work, we investigate a Grid–based NAS approach, called G-NAS, where anti-password detectors are generated deterministically. This approach allows faster detector generation compared to previous NAS approaches. We reported some experimental results of G-NAS using different real-world password datasets. Results demonstrate the efficiency of the proposed approach and exhibited significant improvements compared to NAS approaches. . It appears to be more robust and scalable with respect to the size of password profiles and able to update of detector sets on-the-fly.

Human-Cognition- Based CAPTCHAs

IEEE

CAPTCHAs play a significant role in differentiating humans and machines in any Web-based authentication process. With technological advances in text recognition and image extraction, it's now possible to extract the characters shown in a CAPTCHA with satisfactory accuracy. CAPTCHAs were introduced to cope with the immense threat to online authentication systems, but interpreting them becomes harder for regular Internet users every day. The authors' alternative CAPTCHA provides a variety of mathematical, logical, and inference problems that only humans can understand and answer correctly. The proposed framework supports question diversity and a user-friendly interface. The authors' informal user study evaluates the developed system's performance with different backgrounds. The study shows the efficacy of the implemented system with a good level of user satisfaction.

An Adaptive Approach Towards the Selection of Multi-factor Authentication

IEEE

Authentication is the fundamental defense against any illegitimate access to a computing device or any sensitive online applications. Due to recent trends of emerging security threats, authentication using only a single factor is not reliable to provide adequate protection for these devices and applications. Hence, to facilitate continuous protection of computing devices and other critical online services from an un-authorized access, multi-factor authentication emerges as a viable option. Many authentication mechanisms with varying degrees of accuracy and portability are available for different types of computing devices connected with various communicating media. As a consequence, several existing and well-known multi-factor authentication strategies have already been utilized to enhance the security of various applications. Keeping this in mind, this research is focused on designing a robust and scalable framework for authenticating a legitimate user efficiently through a subset of available authentication modalities along with their several features (authentication factors) in time-varying operating environments (devices, media and surrounding conditions) on a regular basis. This paper highlights the creation of a trustworthy framework to quantify different authentication factors in terms of selection of different types of devices and media. In addition, a novel adaptive selection strategy for the available authentication factors incorporating the trustworthy values, previous history of selection as well as surrounding conditions is proposed in the paper. Selection through adaptive strategy ensures the incorporation of the existing environmental conditions within the selection of authentication factors and provides better diversity in the selection of these factors.

Design and implementation of Negative Authentication System

Springer

Modern society is mostly dependent on online activities like official or social communications, fund transfers and so on. Unauthorized system access is one of the utmost concerns than ever before in cyber systems. For any cyber system, robust authentication is an absolute necessity for ensuring security and reliable access to all type of transactions. However, more than 80% of the current authentication systems are password based, and surprisingly, they are prone to direct and indirect cracking via guessing or side channel attacks. The inspiration of Negative Authentication System (NAS) is based on the negative selection algorithm. In NAS, the password-based authentication data for valid users are termed as password profile or self-region (positive profile); any element other than the self-region is defined as non-self-region in the same representative space. The anti-password detectors are generated which covers most of the non-self-region. There are also some uncovered regions left in the non-self-region for inducing uncertainty to the attackers. In this work, we describe the design and implementation of three approaches of NAS and its efficacy over the other authentication methods. These three approaches represent three different ways to achieve obfuscation of password points with non-password space. The experiments are conducted with both real and simulated password profiles to justify the efficiency of different implementations of NAS.

G-NAS: A Grid-Based Approach for Negative Authentication

Symposium on Computational Intelligence in Cyber Security (CICS) at IEEE Symposium Series on Computational Intelligence (SSCI)

Surveys show that more than 80% authentication systems are password based and these systems are increasingly under direct and indirect attacks. In an effort to protect the Positive Authentication System (PAS), the negative authentication concept was introduced [9]. Here, the representation space of password profile is called self-region; any element outside this self-region is defined as the non-self-region. Then anti-password detectors (clusters) are generated covering most of the non-selfregion while leaving some space uncovered to reduce detector generation time and obfuscation. In this work, we investigate a Grid–based NAS approach, called G-NAS, where anti-password detectors are generated deterministically. This approach allows faster detector generation compared to previous NAS approaches. We reported some experimental results of G-NAS using different real-world password datasets. Results demonstrate the efficiency of the proposed approach and exhibited significant improvements compared to NAS approaches. . It appears to be more robust and scalable with respect to the size of password profiles and able to update of detector sets on-the-fly.

An Adaptive Approach for Active Multi-factor Authentication in an Identity Eco-System

9th Cyber and Information Security Research Conference

Human-Cognition- Based CAPTCHAs

IEEE

CAPTCHAs play a significant role in differentiating humans and machines in any Web-based authentication process. With technological advances in text recognition and image extraction, it's now possible to extract the characters shown in a CAPTCHA with satisfactory accuracy. CAPTCHAs were introduced to cope with the immense threat to online authentication systems, but interpreting them becomes harder for regular Internet users every day. The authors' alternative CAPTCHA provides a variety of mathematical, logical, and inference problems that only humans can understand and answer correctly. The proposed framework supports question diversity and a user-friendly interface. The authors' informal user study evaluates the developed system's performance with different backgrounds. The study shows the efficacy of the implemented system with a good level of user satisfaction.

An Adaptive Approach Towards the Selection of Multi-factor Authentication

IEEE

Authentication is the fundamental defense against any illegitimate access to a computing device or any sensitive online applications. Due to recent trends of emerging security threats, authentication using only a single factor is not reliable to provide adequate protection for these devices and applications. Hence, to facilitate continuous protection of computing devices and other critical online services from an un-authorized access, multi-factor authentication emerges as a viable option. Many authentication mechanisms with varying degrees of accuracy and portability are available for different types of computing devices connected with various communicating media. As a consequence, several existing and well-known multi-factor authentication strategies have already been utilized to enhance the security of various applications. Keeping this in mind, this research is focused on designing a robust and scalable framework for authenticating a legitimate user efficiently through a subset of available authentication modalities along with their several features (authentication factors) in time-varying operating environments (devices, media and surrounding conditions) on a regular basis. This paper highlights the creation of a trustworthy framework to quantify different authentication factors in terms of selection of different types of devices and media. In addition, a novel adaptive selection strategy for the available authentication factors incorporating the trustworthy values, previous history of selection as well as surrounding conditions is proposed in the paper. Selection through adaptive strategy ensures the incorporation of the existing environmental conditions within the selection of authentication factors and provides better diversity in the selection of these factors.

Design and implementation of Negative Authentication System

Springer

Modern society is mostly dependent on online activities like official or social communications, fund transfers and so on. Unauthorized system access is one of the utmost concerns than ever before in cyber systems. For any cyber system, robust authentication is an absolute necessity for ensuring security and reliable access to all type of transactions. However, more than 80% of the current authentication systems are password based, and surprisingly, they are prone to direct and indirect cracking via guessing or side channel attacks. The inspiration of Negative Authentication System (NAS) is based on the negative selection algorithm. In NAS, the password-based authentication data for valid users are termed as password profile or self-region (positive profile); any element other than the self-region is defined as non-self-region in the same representative space. The anti-password detectors are generated which covers most of the non-self-region. There are also some uncovered regions left in the non-self-region for inducing uncertainty to the attackers. In this work, we describe the design and implementation of three approaches of NAS and its efficacy over the other authentication methods. These three approaches represent three different ways to achieve obfuscation of password points with non-password space. The experiments are conducted with both real and simulated password profiles to justify the efficiency of different implementations of NAS.

G-NAS: A Grid-Based Approach for Negative Authentication

Symposium on Computational Intelligence in Cyber Security (CICS) at IEEE Symposium Series on Computational Intelligence (SSCI)

Surveys show that more than 80% authentication systems are password based and these systems are increasingly under direct and indirect attacks. In an effort to protect the Positive Authentication System (PAS), the negative authentication concept was introduced [9]. Here, the representation space of password profile is called self-region; any element outside this self-region is defined as the non-self-region. Then anti-password detectors (clusters) are generated covering most of the non-selfregion while leaving some space uncovered to reduce detector generation time and obfuscation. In this work, we investigate a Grid–based NAS approach, called G-NAS, where anti-password detectors are generated deterministically. This approach allows faster detector generation compared to previous NAS approaches. We reported some experimental results of G-NAS using different real-world password datasets. Results demonstrate the efficiency of the proposed approach and exhibited significant improvements compared to NAS approaches. . It appears to be more robust and scalable with respect to the size of password profiles and able to update of detector sets on-the-fly.

An Adaptive Approach for Active Multi-factor Authentication in an Identity Eco-System

9th Cyber and Information Security Research Conference

Advances in User Authentication

Springer

This book is dedicated to advances in the field of user authentication. The book covers detailed description of the authentication process as well as types of authentication modalities along with their several features (authentication factors). It discusses the use of these modalities in a time-varying operating environment, including factors such as devices, media and surrounding conditions, like light, noise, etc. The book is divided into several parts that cover descriptions of several biometric and non-biometric authentication modalities, single factor and multi-factor authentication systems (mainly, adaptive), negative authentication system, etc. The adaptive strategy ensures the incorporation of the existing environmental conditions on the selection of authentication factors and provides significant diversity in the selection process. The contents of this book will prove useful to practitioners, researchers, and students. The book is suited to be used a text in advanced/graduate courses on User Authentication Modalities. It can also be used as a textbook for professional development and certification coursework for practicing engineers and computer scientists.

Human-Cognition- Based CAPTCHAs

IEEE

CAPTCHAs play a significant role in differentiating humans and machines in any Web-based authentication process. With technological advances in text recognition and image extraction, it's now possible to extract the characters shown in a CAPTCHA with satisfactory accuracy. CAPTCHAs were introduced to cope with the immense threat to online authentication systems, but interpreting them becomes harder for regular Internet users every day. The authors' alternative CAPTCHA provides a variety of mathematical, logical, and inference problems that only humans can understand and answer correctly. The proposed framework supports question diversity and a user-friendly interface. The authors' informal user study evaluates the developed system's performance with different backgrounds. The study shows the efficacy of the implemented system with a good level of user satisfaction.

An Adaptive Approach Towards the Selection of Multi-factor Authentication

IEEE

Authentication is the fundamental defense against any illegitimate access to a computing device or any sensitive online applications. Due to recent trends of emerging security threats, authentication using only a single factor is not reliable to provide adequate protection for these devices and applications. Hence, to facilitate continuous protection of computing devices and other critical online services from an un-authorized access, multi-factor authentication emerges as a viable option. Many authentication mechanisms with varying degrees of accuracy and portability are available for different types of computing devices connected with various communicating media. As a consequence, several existing and well-known multi-factor authentication strategies have already been utilized to enhance the security of various applications. Keeping this in mind, this research is focused on designing a robust and scalable framework for authenticating a legitimate user efficiently through a subset of available authentication modalities along with their several features (authentication factors) in time-varying operating environments (devices, media and surrounding conditions) on a regular basis. This paper highlights the creation of a trustworthy framework to quantify different authentication factors in terms of selection of different types of devices and media. In addition, a novel adaptive selection strategy for the available authentication factors incorporating the trustworthy values, previous history of selection as well as surrounding conditions is proposed in the paper. Selection through adaptive strategy ensures the incorporation of the existing environmental conditions within the selection of authentication factors and provides better diversity in the selection of these factors.

Design and implementation of Negative Authentication System

Springer

Modern society is mostly dependent on online activities like official or social communications, fund transfers and so on. Unauthorized system access is one of the utmost concerns than ever before in cyber systems. For any cyber system, robust authentication is an absolute necessity for ensuring security and reliable access to all type of transactions. However, more than 80% of the current authentication systems are password based, and surprisingly, they are prone to direct and indirect cracking via guessing or side channel attacks. The inspiration of Negative Authentication System (NAS) is based on the negative selection algorithm. In NAS, the password-based authentication data for valid users are termed as password profile or self-region (positive profile); any element other than the self-region is defined as non-self-region in the same representative space. The anti-password detectors are generated which covers most of the non-self-region. There are also some uncovered regions left in the non-self-region for inducing uncertainty to the attackers. In this work, we describe the design and implementation of three approaches of NAS and its efficacy over the other authentication methods. These three approaches represent three different ways to achieve obfuscation of password points with non-password space. The experiments are conducted with both real and simulated password profiles to justify the efficiency of different implementations of NAS.

G-NAS: A Grid-Based Approach for Negative Authentication

Symposium on Computational Intelligence in Cyber Security (CICS) at IEEE Symposium Series on Computational Intelligence (SSCI)

Surveys show that more than 80% authentication systems are password based and these systems are increasingly under direct and indirect attacks. In an effort to protect the Positive Authentication System (PAS), the negative authentication concept was introduced [9]. Here, the representation space of password profile is called self-region; any element outside this self-region is defined as the non-self-region. Then anti-password detectors (clusters) are generated covering most of the non-selfregion while leaving some space uncovered to reduce detector generation time and obfuscation. In this work, we investigate a Grid–based NAS approach, called G-NAS, where anti-password detectors are generated deterministically. This approach allows faster detector generation compared to previous NAS approaches. We reported some experimental results of G-NAS using different real-world password datasets. Results demonstrate the efficiency of the proposed approach and exhibited significant improvements compared to NAS approaches. . It appears to be more robust and scalable with respect to the size of password profiles and able to update of detector sets on-the-fly.

An Adaptive Approach for Active Multi-factor Authentication in an Identity Eco-System

9th Cyber and Information Security Research Conference

Advances in User Authentication

Springer

This book is dedicated to advances in the field of user authentication. The book covers detailed description of the authentication process as well as types of authentication modalities along with their several features (authentication factors). It discusses the use of these modalities in a time-varying operating environment, including factors such as devices, media and surrounding conditions, like light, noise, etc. The book is divided into several parts that cover descriptions of several biometric and non-biometric authentication modalities, single factor and multi-factor authentication systems (mainly, adaptive), negative authentication system, etc. The adaptive strategy ensures the incorporation of the existing environmental conditions on the selection of authentication factors and provides significant diversity in the selection process. The contents of this book will prove useful to practitioners, researchers, and students. The book is suited to be used a text in advanced/graduate courses on User Authentication Modalities. It can also be used as a textbook for professional development and certification coursework for practicing engineers and computer scientists.

An Adaptive Approach for Active Multi-Factor Authentication

9th Annual Symposium on Information Assurance

Multi-Factor Authentication (MFA) is the current trend to genuinely identify authorized users through the active authentication process using passwords, biometrics, cognitive behavior, etc. As new and improved authentication modalities of various types are becoming available, these are opening up options for security researchers to devise solutions facilitating continuous authentication to online systems. This paper focuses on describing a framework for continuous authentication where authentication modalities are selected adaptively by sensing the users’ operating environment (the device and communication media, and historical data). Empirical studies are conducted with varying environmental parameters and the performance of the adaptive MFA is compared with other selection strategies. The empirical results appear promising, which reflects that such a multi-factor decision support technique can be applied to real-world identity management and authentication systems.

Human-Cognition- Based CAPTCHAs

IEEE

CAPTCHAs play a significant role in differentiating humans and machines in any Web-based authentication process. With technological advances in text recognition and image extraction, it's now possible to extract the characters shown in a CAPTCHA with satisfactory accuracy. CAPTCHAs were introduced to cope with the immense threat to online authentication systems, but interpreting them becomes harder for regular Internet users every day. The authors' alternative CAPTCHA provides a variety of mathematical, logical, and inference problems that only humans can understand and answer correctly. The proposed framework supports question diversity and a user-friendly interface. The authors' informal user study evaluates the developed system's performance with different backgrounds. The study shows the efficacy of the implemented system with a good level of user satisfaction.

An Adaptive Approach Towards the Selection of Multi-factor Authentication

IEEE

Authentication is the fundamental defense against any illegitimate access to a computing device or any sensitive online applications. Due to recent trends of emerging security threats, authentication using only a single factor is not reliable to provide adequate protection for these devices and applications. Hence, to facilitate continuous protection of computing devices and other critical online services from an un-authorized access, multi-factor authentication emerges as a viable option. Many authentication mechanisms with varying degrees of accuracy and portability are available for different types of computing devices connected with various communicating media. As a consequence, several existing and well-known multi-factor authentication strategies have already been utilized to enhance the security of various applications. Keeping this in mind, this research is focused on designing a robust and scalable framework for authenticating a legitimate user efficiently through a subset of available authentication modalities along with their several features (authentication factors) in time-varying operating environments (devices, media and surrounding conditions) on a regular basis. This paper highlights the creation of a trustworthy framework to quantify different authentication factors in terms of selection of different types of devices and media. In addition, a novel adaptive selection strategy for the available authentication factors incorporating the trustworthy values, previous history of selection as well as surrounding conditions is proposed in the paper. Selection through adaptive strategy ensures the incorporation of the existing environmental conditions within the selection of authentication factors and provides better diversity in the selection of these factors.

Design and implementation of Negative Authentication System

Springer

Modern society is mostly dependent on online activities like official or social communications, fund transfers and so on. Unauthorized system access is one of the utmost concerns than ever before in cyber systems. For any cyber system, robust authentication is an absolute necessity for ensuring security and reliable access to all type of transactions. However, more than 80% of the current authentication systems are password based, and surprisingly, they are prone to direct and indirect cracking via guessing or side channel attacks. The inspiration of Negative Authentication System (NAS) is based on the negative selection algorithm. In NAS, the password-based authentication data for valid users are termed as password profile or self-region (positive profile); any element other than the self-region is defined as non-self-region in the same representative space. The anti-password detectors are generated which covers most of the non-self-region. There are also some uncovered regions left in the non-self-region for inducing uncertainty to the attackers. In this work, we describe the design and implementation of three approaches of NAS and its efficacy over the other authentication methods. These three approaches represent three different ways to achieve obfuscation of password points with non-password space. The experiments are conducted with both real and simulated password profiles to justify the efficiency of different implementations of NAS.

G-NAS: A Grid-Based Approach for Negative Authentication

Symposium on Computational Intelligence in Cyber Security (CICS) at IEEE Symposium Series on Computational Intelligence (SSCI)

Surveys show that more than 80% authentication systems are password based and these systems are increasingly under direct and indirect attacks. In an effort to protect the Positive Authentication System (PAS), the negative authentication concept was introduced [9]. Here, the representation space of password profile is called self-region; any element outside this self-region is defined as the non-self-region. Then anti-password detectors (clusters) are generated covering most of the non-selfregion while leaving some space uncovered to reduce detector generation time and obfuscation. In this work, we investigate a Grid–based NAS approach, called G-NAS, where anti-password detectors are generated deterministically. This approach allows faster detector generation compared to previous NAS approaches. We reported some experimental results of G-NAS using different real-world password datasets. Results demonstrate the efficiency of the proposed approach and exhibited significant improvements compared to NAS approaches. . It appears to be more robust and scalable with respect to the size of password profiles and able to update of detector sets on-the-fly.

An Adaptive Approach for Active Multi-factor Authentication in an Identity Eco-System

9th Cyber and Information Security Research Conference

Advances in User Authentication

Springer

This book is dedicated to advances in the field of user authentication. The book covers detailed description of the authentication process as well as types of authentication modalities along with their several features (authentication factors). It discusses the use of these modalities in a time-varying operating environment, including factors such as devices, media and surrounding conditions, like light, noise, etc. The book is divided into several parts that cover descriptions of several biometric and non-biometric authentication modalities, single factor and multi-factor authentication systems (mainly, adaptive), negative authentication system, etc. The adaptive strategy ensures the incorporation of the existing environmental conditions on the selection of authentication factors and provides significant diversity in the selection process. The contents of this book will prove useful to practitioners, researchers, and students. The book is suited to be used a text in advanced/graduate courses on User Authentication Modalities. It can also be used as a textbook for professional development and certification coursework for practicing engineers and computer scientists.

An Adaptive Approach for Active Multi-Factor Authentication

9th Annual Symposium on Information Assurance

Multi-Factor Authentication (MFA) is the current trend to genuinely identify authorized users through the active authentication process using passwords, biometrics, cognitive behavior, etc. As new and improved authentication modalities of various types are becoming available, these are opening up options for security researchers to devise solutions facilitating continuous authentication to online systems. This paper focuses on describing a framework for continuous authentication where authentication modalities are selected adaptively by sensing the users’ operating environment (the device and communication media, and historical data). Empirical studies are conducted with varying environmental parameters and the performance of the adaptive MFA is compared with other selection strategies. The empirical results appear promising, which reflects that such a multi-factor decision support technique can be applied to real-world identity management and authentication systems.

Center for Information Assurnace (CfIA), FedEx Institute of Technology

Research Assistant

Involved in several federal funded projects as a key person through the phases of design, analysis, and implementation. Projects Include: - Negative Authentication funded by IARPA (September 2012- December 2013) - ACT Online funded by FEMA (May 2014 - August 2016) - Puzzle Based Learning funded by NSF (September 2014 - December 2016)urn:li:fs_position:(ACoAAAQyUWMBqQ0mNY7O7VewTQWlfzJWgA0rGmM,569093776)

Center for Information Assurnace (CfIA), FedEx Institute of Technology

Research Assistant

Involved in several federal funded projects as a key person through the phases of design, analysis, and implementation. Projects Include: - Negative Authentication funded by IARPA (September 2012- December 2013) - ACT Online funded by FEMA (May 2014 - August 2016) - Puzzle Based Learning funded by NSF (September 2014 - December 2016)urn:li:fs_position:(ACoAAAQyUWMBqQ0mNY7O7VewTQWlfzJWgA0rGmM,569093776)

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Center for Information Assurnace (CfIA), FedEx Institute of Technology

Research Assistant

Involved in several federal funded projects as a key person through the phases of design, analysis, and implementation. Projects Include: - Negative Authentication funded by IARPA (September 2012- December 2013) - ACT Online funded by FEMA (May 2014 - August 2016) - Puzzle Based Learning funded by NSF (September 2014 - December 2016)urn:li:fs_position:(ACoAAAQyUWMBqQ0mNY7O7VewTQWlfzJWgA0rGmM,569093776)

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Center for Information Assurnace (CfIA), FedEx Institute of Technology

Research Assistant

Involved in several federal funded projects as a key person through the phases of design, analysis, and implementation. Projects Include: - Negative Authentication funded by IARPA (September 2012- December 2013) - ACT Online funded by FEMA (May 2014 - August 2016) - Puzzle Based Learning funded by NSF (September 2014 - December 2016)urn:li:fs_position:(ACoAAAQyUWMBqQ0mNY7O7VewTQWlfzJWgA0rGmM,569093776)

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Research Assistant

Involved in several federal funded projects as a key person through the phases of design, analysis, and implementation. Projects Include: - Negative Authentication funded by IARPA (September 2012- December 2013) - ACT Online funded by FEMA (May 2014 - August 2016) - Puzzle Based Learning funded by NSF (September 2014 - December 2016)urn:li:fs_position:(ACoAAAQyUWMBqQ0mNY7O7VewTQWlfzJWgA0rGmM,569093776)

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Center for Information Assurnace (CfIA), FedEx Institute of Technology

Research Assistant

Involved in several federal funded projects as a key person through the phases of design, analysis, and implementation. Projects Include: - Negative Authentication funded by IARPA (September 2012- December 2013) - ACT Online funded by FEMA (May 2014 - August 2016) - Puzzle Based Learning funded by NSF (September 2014 - December 2016)urn:li:fs_position:(ACoAAAQyUWMBqQ0mNY7O7VewTQWlfzJWgA0rGmM,569093776)

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Center for Information Assurnace (CfIA), FedEx Institute of Technology

Research Assistant

Involved in several federal funded projects as a key person through the phases of design, analysis, and implementation. Projects Include: - Negative Authentication funded by IARPA (September 2012- December 2013) - ACT Online funded by FEMA (May 2014 - August 2016) - Puzzle Based Learning funded by NSF (September 2014 - December 2016)urn:li:fs_position:(ACoAAAQyUWMBqQ0mNY7O7VewTQWlfzJWgA0rGmM,569093776)

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Center for Information Assurnace (CfIA), FedEx Institute of Technology

Research Assistant

Involved in several federal funded projects as a key person through the phases of design, analysis, and implementation. Projects Include: - Negative Authentication funded by IARPA (September 2012- December 2013) - ACT Online funded by FEMA (May 2014 - August 2016) - Puzzle Based Learning funded by NSF (September 2014 - December 2016)urn:li:fs_position:(ACoAAAQyUWMBqQ0mNY7O7VewTQWlfzJWgA0rGmM,569093776)

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Center for Information Assurnace (CfIA), FedEx Institute of Technology

Research Assistant

Involved in several federal funded projects as a key person through the phases of design, analysis, and implementation. Projects Include: - Negative Authentication funded by IARPA (September 2012- December 2013) - ACT Online funded by FEMA (May 2014 - August 2016) - Puzzle Based Learning funded by NSF (September 2014 - December 2016)urn:li:fs_position:(ACoAAAQyUWMBqQ0mNY7O7VewTQWlfzJWgA0rGmM,569093776)

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Center for Information Assurnace (CfIA), FedEx Institute of Technology

Research Assistant

Involved in several federal funded projects as a key person through the phases of design, analysis, and implementation. Projects Include: - Negative Authentication funded by IARPA (September 2012- December 2013) - ACT Online funded by FEMA (May 2014 - August 2016) - Puzzle Based Learning funded by NSF (September 2014 - December 2016)urn:li:fs_position:(ACoAAAQyUWMBqQ0mNY7O7VewTQWlfzJWgA0rGmM,569093776)

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Center for Information Assurnace (CfIA), FedEx Institute of Technology

Research Assistant

Involved in several federal funded projects as a key person through the phases of design, analysis, and implementation. Projects Include: - Negative Authentication funded by IARPA (September 2012- December 2013) - ACT Online funded by FEMA (May 2014 - August 2016) - Puzzle Based Learning funded by NSF (September 2014 - December 2016)urn:li:fs_position:(ACoAAAQyUWMBqQ0mNY7O7VewTQWlfzJWgA0rGmM,569093776)

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Center for Information Assurnace (CfIA), FedEx Institute of Technology

Research Assistant

Involved in several federal funded projects as a key person through the phases of design, analysis, and implementation. Projects Include: - Negative Authentication funded by IARPA (September 2012- December 2013) - ACT Online funded by FEMA (May 2014 - August 2016) - Puzzle Based Learning funded by NSF (September 2014 - December 2016)urn:li:fs_position:(ACoAAAQyUWMBqQ0mNY7O7VewTQWlfzJWgA0rGmM,569093776)

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