Explore innovative cyber security project ideas tailored for BTech, MTech, and PhD final year students. These major projects focus on advanced topics, equipping students with practical skills and knowledge to address current and emerging cyber threats.
This project explores attack & defense methods in cyber-physical power systems (CPPS). It details three-level security strategies, analyzes cyber and physical attack modes, and discusses potential threats and future advancements in CPPS security.
This project develops a deep learning model to detect cyber-attacks in smart power systems using PMU data. The model, tested with 37 case studies, outperforms current methods with a 93.6% detection rate and 93.91% accuracy.
This project assesses power system reliability under cyber-attacks on wind farm EMS/SCADA systems. Using Bayesian models, it evaluates attack success rates and impacts on system reliability from wind turbine failures in IEEE simulations.
This project analyzes power system reliability considering cyber threats to SCADA/EMS. Using Bayesian Networks and Monte Carlo Simulations, it models attack paths, assesses vulnerabilities, and evaluates system reliability impacts from cyberattacks.
This project develops a deep learning model to detect zero-day hijacking attacks on power grid controllers. It uses regular data to simulate normal behavior, identifying anomalies with over 99.9% accuracy and minimal false positives.