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All Journal Journal of Social Science Utilizing Technology International Journal of Integrated Science and Technology Journal of Social Science Utilizing Technology
Lodin, Hedayatullah
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Highly Secure and Easy to Remember Password-Based Authentication Approach Sadat, Sayed Elham; Lodin, Hedayatullah; Ahmadzai, Nazak
Journal of Social Science Utilizing Technology Vol. 2 No. 4 (2024)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v2i4.1505

Abstract

Background. Everyone connected and using the Internet is concerned regarding the security and also the privacy of their sensitive information available on the Internet. As authentication is the fundamental part of security, there are different authentication mechanisms through which the systems can be secured. The password-based authentication mechanism is a cheap and easy method for enforcing authentication in the systems for many years. The weakest aspect in password security is human, as they choose weak and easy to guess passwords or a highly secure and complex password which might be difficult to remember and recover the password. Purpose. In this paper, a password generation system is proposed which generates a password based on the user’s input like, time and location data. The system generates a password that is highly secure, easy to remember, easy to recover, and can effectively defend against Brute force and dictionary attacks. Method. This study utilizes a descriptive quantitative approach to develop a password-based authentication system focused on security and memorability. The population includes digital users needing secure access, with samples drawn from various groups to ensure comprehensive feedback. Data collection involves password strength evaluation tools and user feedback questionnaires. Procedures include developing a password generation algorithm using user inputs, followed by testing its security and conducting usability assessments. Feedback will guide the refinement of the system to enhance user experience and security. Results. The generated passwords using the porposed system have been checked in three online password checkers, which verifies that the system is generating highly secure and crack resistant passwords and the method for recovering the forgotten password was efficient and easy. The system is implemented using PHP scripting language with a user-friendly environment. Conclusion. This paper proposes a password-based authentication system that generates secure and memorable passwords using user input, time, and location data. The passwords were validated through three online checkers, demonstrating high security and resistance to attacks. Future enhancements could include voice recognition to improve security and personalization, making the system more user-friendly while maintaining low costs.
Highly Secure and Easy to Remember Password-Based Authentication Approach Sadat, Sayed Elham; Lodin, Hedayatullah; Ahmadzai, Nazak
Journal of Social Science Utilizing Technology Vol. 2 No. 4 (2024)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v2i4.1505

Abstract

Background. Everyone connected and using the Internet is concerned regarding the security and also the privacy of their sensitive information available on the Internet. As authentication is the fundamental part of security, there are different authentication mechanisms through which the systems can be secured. The password-based authentication mechanism is a cheap and easy method for enforcing authentication in the systems for many years. The weakest aspect in password security is human, as they choose weak and easy to guess passwords or a highly secure and complex password which might be difficult to remember and recover the password. Purpose. In this paper, a password generation system is proposed which generates a password based on the user’s input like, time and location data. The system generates a password that is highly secure, easy to remember, easy to recover, and can effectively defend against Brute force and dictionary attacks. Method. This study utilizes a descriptive quantitative approach to develop a password-based authentication system focused on security and memorability. The population includes digital users needing secure access, with samples drawn from various groups to ensure comprehensive feedback. Data collection involves password strength evaluation tools and user feedback questionnaires. Procedures include developing a password generation algorithm using user inputs, followed by testing its security and conducting usability assessments. Feedback will guide the refinement of the system to enhance user experience and security. Results. The generated passwords using the porposed system have been checked in three online password checkers, which verifies that the system is generating highly secure and crack resistant passwords and the method for recovering the forgotten password was efficient and easy. The system is implemented using PHP scripting language with a user-friendly environment. Conclusion. This paper proposes a password-based authentication system that generates secure and memorable passwords using user input, time, and location data. The passwords were validated through three online checkers, demonstrating high security and resistance to attacks. Future enhancements could include voice recognition to improve security and personalization, making the system more user-friendly while maintaining low costs.
AI-Enabled Traffic Light Control System: An Efficient Model to Manage the Traffic at Intersections using Computer Vision Ayoubi, Majid; Aman, Hasibullah; Akbari, Rohullah; Lodin, Hedayatullah
International Journal of Integrated Science and Technology Vol. 2 No. 8 (2024): August 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i8.2438

Abstract

Traffic congestion is a significant issue with studies indicating it costs cities billions annually and averages 54 hours of wasted time per traveler each year. This situation necessitates the implementation of efficient traffic management systems, especially at intersections. In response to this challenge, our work introduces an artificial intelligence-based system designed to analyze and predict traffic flow using machine learning algorithms and deep learning methods in conjunction with traffic cameras. The model comprises two main components: real-time data collection and predictive modeling. It employs object detection to identify and classify vehicles and adjusts traffic signal timings based on the necessary passage time and predetermined constraints. Additionally, data accumulated during operation facilitates the development of a predictive model for traffic flow over time, allowing for proactive traffic management. Evaluations are done to showcase the accuracy of the model and corresponding simulation and physical implementation further approved the applicability of our approach. Finally, this work aims to enhance urban transportation efficiently, reduce commuting stress, and improve the quality of life for city residents
Co-Authors Ahmadzai, Nazak Akbari, Rohullah Aman, Hasibullah Ayoubi, Majid Sadat, Sayed Elham