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All Journal JOIV : International Journal on Informatics Visualization
Sharif, Khaironi Yatim
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Computer Science & IT

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Application of Artificial Intelligence in Detecting SQL Injection Attacks Augustine, Nwabudike; Md. Sultan, Abu Bakar; Osman, Mohd Hafeez; Sharif, Khaironi Yatim
JOIV : International Journal on Informatics Visualization Vol 8, No 4 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.4.3631

Abstract

SQL injection attacks rank among the most significant threats to data security. While AI and machine learning have advanced considerably, their application in cybersecurity remains relatively undeveloped. This work mainly aims to solve the IT-related challenge of insufficient knowledge bases and tools for security practitioners to monitor and mitigate SQL Injection attacks with AI/ML techniques. The study uses a mixed-methods approach to evaluate how well different AI and ML algorithms identify SQL injection attacks by combining algorithmic evaluation with empirical investigation. Datasets of well-known SQL injection attack patterns and AI/ML models intended for cybersecurity anomaly detection are among the resources underexplored; these findings show the potential for boosting detection capabilities by deploying ML and AI-based security solutions; specific algorithms have demonstrated success rates of up to 80% in detecting SQL injections. Despite this promising performance, around 75% of survey participants acknowledged a decrease in harmful content, with a similar number highlighting increased efficiency in their roles as security researchers or incident responders. Nevertheless, the tool’s adoption among cybersecurity professionals remains under 30%. This underscores a gap between the capabilities these technologies offer and their current level of adoption among professionals. This will help lay the groundwork for future work in identifying the best solutions and providing potential approaches to incorporating AI/ML into cybersecurity frameworks. The implications of this study indicate that adopting robust defenses against SQL injection and other cyber threats could increase many folds if we continue to research and implement AI ML. technologies.
Optimizing Linked List-based Smart Contract on Ethereum with IPFS for E-book Management System Mohammadan Makhtar, Maznun Arifa; Admodisastro, Novia; Mat Isa, Mohd Anuar; Abdullah, Daniel Hafiz; Sharif, Khaironi Yatim
JOIV : International Journal on Informatics Visualization Vol 8, No 3-2 (2024): IT for Global Goals: Building a Sustainable Tomorrow
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.3-2.3481

Abstract

People are now widely adopting digital assets in various applications, integrating them into almost every aspect of their lives. Electronic books, or e-books, are one of the digital assets that result from the transformation of physical reading material into the digital world. Nowadays, blockchain is used in many industries because it provides immutable and transparent records. E-book publishers may take this opportunity to adopt blockchain technology for e-book data management. However, blockchain storage is limited; thus, storing the e-book files in blockchain is not recommended. A decentralized storage system, such as InterPlanetary Files Systems (IPFS), is an alternative way to store large files like e-books. IPFS can facilitate the storage of e-book files while the metadata is stored in the blockchain. The e-book metadata should be stored in a structured way for effective search and retrieval. E-book metadata could be added, deleted, and updated occasionally. Nevertheless, some data structures often struggle with dynamic collections of records. This paper proposes a linked list-based smart contract on Ethereum that integrates with IPFS for the e-book management system. We demonstrate the implementation of a linked list smart contract for insertion, deletion, update, retrieval, and traversal of the e-book’s metadata. The result shows that a linked list-based smart contract with IPFS could offer a robust solution for e-book data management. This solution provides more opportunities to explore further security and cryptography approaches toward a secure e-book management system.
Co-Authors Abdullah, Daniel Hafiz Admodisastro, Novia Augustine, Nwabudike Mat Isa, Mohd Anuar Md. Sultan, Abu Bakar Mohammadan Makhtar, Maznun Arifa Osman, Mohd Hafeez