Review ArticleOpen accessIn the keywordsSecurity Threats to Databases in E-Commerce Systems: A Systematic Literature ReviewNurayn Mesfer AlqahtaniData is a primary by-product of each business. A typical business organization uses a database system to store and manage data. On the other hand, databases are the primary target of hackers and attackers. The existing literature shows that modern database systems are vulnerable to various data breaches, cyberattacks, or malware attacks. Modern business organizations and e-commerce owners look to … …Journal of Computer Science, Vol. 21, Issue 1 · 2 Dec 2024 · 7,291 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCyber Security Threats and Countermeasures using Machine and Deep Learning Approaches: A SurveyManjula M, Venkatesh, Venugopal K. R.Recent advancements in e-business, e-healthcare, e-governance, and online digital transactions have brought valuable benefits. Unfortunately, it raises severe cyber-attacks. Cyberattacks disrupt normal operations, try to retrieve confidential information and defense secrets, and subvert the nation’s defense systems and Internet-connected devices. Cyber security solutions are required to detect, analyze, defend against threats and protect sensitive data from unauthorized access. This study … …Journal of Computer Science, Vol. 19, Issue 1 · 4 Jan 2023 · 9,370 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intrusion Detection System Using Optimized Deep Learning for IoT NetworksChempavathy B., Mouleeswaran S. K.In the rapidly evolving landscape of Internet of Things (IoT) networks, assuring security is paramount. Cyber-attacks on IoT networks are evolving in complexity and scale. Intruders employ diverse tactics, including malware, Denial of Service (DoS) attacks, along with unauthorized access. This research aims to propose an optimized Deep Learning (DL) based Intrusion Detection System (IDS) to bolster security within IoT … …Journal of Computer Science, Vol. 21, Issue 8 · 9 Oct 2025 · 2,993 accessesView PDFCite
Research ArticleOpen accessIn the abstractRule-Based Approach to Detect IoT Malicious FilesFaisal Alsattam, Mousa Al-Akhras, Marwah M. Almasri, Mohammed AlawairdhiThe current immersive increase of cyber-attacks requires constant evolution of the used security solutions. Current malware detection solutions are only able to identify known malwares that were previously detected. They also lack the ability to deeply investigate every file in the system. Therefore, new detection techniques are needed to fill this gab. In this study, a flexible and an effective … …Journal of Computer Science, Vol. 16, Issue 9 · 15 Oct 2020 · 7,345 accessesView PDFCite
Research ArticleOpen accessIn the abstractMalware Detection Based on Hybrid Signature Behaviour Application Programming Interface Call GraphAmmar Ahmed E. Elhadi, Mohd Aizaini Maarof, Ahmed Hamza OsmanProblem statement: A malware is a program that has malicious intent. Nowadays, malware authors apply several sophisticated techniques such as packing and obfuscation to avoid malware detection. That makes zero-day attacks and false positives the most challenging problems in the malware detection field. Approach: In this study, the static and dynamic analysis techniques that are used in malware detection are … …American Journal of Applied Sciences, Vol. 9, Issue 3 · 9 Jan 2012 · 9,144 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAdvanced Persistent Threats (APT)-Attribution-MICTIC Framework ExtensionPedro Ramos BrandaoAnalysis of one of the fundamental parts of the Advanced Persistent Threats (APT) Attacks. The phases of the APTs, their framing with the identification of criminals. Type of attack that normally requires resources only available to the State-State hacking. The importance of Attribution in the analysis of APTS. The unique and differentiating characteristics of this type of attacks compared to … …Journal of Computer Science, Vol. 17, Issue 5 · 19 May 2021 · 8,453 accessesView PDFCite