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All Journal Innovation in Research of Informatics (INNOVATICS) International Journal of Informatics and Computing
Selamat, Siti Rahayu
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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An Algorithm for Color-Based Password Authentication to Increase Security Level Selamat, Siti Rahayu; Cai, Soung Young; Hassan, Nor Hafeizah; Yusof, Robiah
INNOVATICS: International Journal on Innovation in Research of Informatics Vol 6, No 1 (2024): March 2024
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v6i1.10396

Abstract

Security level in authentication is essential to decrease the possibility of an account being guessed. Several authentication methods are widely used nowadays, covering digital aspects such as passwords, challenge-response, public and private key / digital certificates, and physical elements such as fingerprints, iris, or retina scanning. This paper aims to focus on solving the problem of the password. This textual authentication consists of many vulnerabilities open to attacks like eavesdropping, dictionary attack, and brute force attack by increasing the level of complexity in the authentication algorithm. In this paper, we proposed a new color-based password authentication algorithm to solve the vulnerabilities in textual authentication. The color-based password authentication algorithm consists of three main processes: color selection, hexadecimal password encryption, and password verification. This research contributes to a new color-based authentication by increasing the complexity of the verification process that can solve the vulnerabilities of textual authentication and harden the level of security in the authentication layer. This color-based authentication algorithm could fully replace textual authentication in the future and is worth using in sensitive data domains such as medical and health or banking institutions.
Advanced Phishing Attack Detection Through Network Forensic Methods and Incident Response Planning Based on Machine Learning Selamat, Siti Rahayu; Rizal, Randi; Nursihab, Cucu; Amien, Nashihun
JICO: International Journal of Informatics and Computing Vol. 1 No. 1 (2025): May 2025
Publisher : IAICO

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Abstract

The widespread use of smartphones has led to an increase in cybercrimes, particularly phishing attacks. Phishing attacks are commonly propagated through email, WhatsApp groups, and other communication channels. The stolen data is then used to commit further crimes, exploiting the victims' personal information. This study addresses the detection of phishing attacks using network forensic methods and incident response planning. Unlike previous approaches that relied solely on Incident Response Plans (IRPs) and Incident Handling methods to react to phishing attacks, this research emphasizes proactive detection. By employing network forensics, suspicious websites can be identified and differentiated from legitimate ones, enabling early detection and prevention of phishing attacks. The results demonstrate that network forensics can significantly enhance the ability to detect phishing sites before they can harm users. In our experiments, we analyzed a dataset of 10,000 websites, identifying 95% of phishing sites with a false positive rate of only 2%. Utilizing the Random Forest machine learning algorithm, we achieved high performance metrics with an accuracy of 96.5%, precision of 97.1%, recall of 95.8%, and an F1-score of 96.4%. This proactive approach not only mitigates the risk of phishing but also provides a robust framework for incident response, ensuring that potential threats are identified and neutralized promptly.
Co-Authors Amien, Nashihun Cai, Soung Young Hassan, Nor Hafeizah Nursihab, Cucu Rizal, Randi Yusof, Robiah