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2 articles for “False Data Injection Attacks”
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Enhancing Smart Grid Security: Machine Learning Approaches for Detecting Anomalies
Abstract: The integration of Information and Communication Technology (ICT) with traditional electric grids has led to the development of smart grids. However, this integration has also increased the risk of anomalies, such as cyber-attacks, metering fraud, electricity theft etc. False Data Injection Attacks are a class of cyber-attacks against power grid monitoring systems, where adversaries can inject false data to manipulate the grid’s operation. Metering frauds pertain to malicious customers com- …
Published in Trends in Electrical Engineering · Vol. 14, Issue 2, 2024 · pp. 10–19 Read article
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Cybersecurity in Web Automation: A Machine Learning Approach to Lightweight Intrusion Detection
Abstract: Launch-Attack is a lightweight and practical threat-detection framework designed specifically for smaller web-automation environments, including setups that rely on tools such as Selenium. Rather than aiming to replace large enterprise-grade security platforms, the framework focuses on offering an accessible option for developers, testers, and researchers who need real-time monitoring without the heavy resource demands of traditional systems. The model relies on machine-learning techniques implemented through Scikit-learn, enabling it to detect …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 1, 2026 · pp. 34–40 Read article