Back close

Predictive Threat Evaluation in Complex IT Systems

Start Date: Wednesday, Jun 18,2014

School: School of Engineering, Coimbatore

Project Incharge:Dr. M. Sethumadhavan
Co-Project Incharge:Prashant Nair R., Kandasamy Muniasamy
Funded by:DRDO
Predictive Threat Evaluation in Complex IT Systems

COTS Security Incident and Event Management (SIEM) Systems process log events based on built-in rules and identify actionable incidents. These primarily identify known attacks. Using Machine Learning techniques such as Naive Bayes and AdaBoost algorithms, we aim to predict new attacks probabilistically for wired and wireless networks. The Machine Learning-based prediction system in tandem with an SIEM system to predict an attack before it actually occurs. Evaluate the effectiveness of the ML system comparing with the SIEM system in network attack prediction

Related Projects

Development of Entropy alloys and detemination of their Mechanical Properties including Hardness and wear rate
Development of Entropy alloys and detemination of their Mechanical Properties including Hardness and wear rate
Malware detection using FPGA, Sandboxing and Machine Learning
Malware detection using FPGA, Sandboxing and Machine Learning
Synthesis of Nanostructured Transition Metal Oxide Thin Film Coatings on Steel Substrates by Dip Coating for Corrosion and Wear Resistance Applications
Synthesis of Nanostructured Transition Metal Oxide Thin Film Coatings on Steel Substrates by Dip Coating for Corrosion and Wear Resistance Applications
Design of a Compact and High Efficient Rectenna for RF Energy Harvesting
Design of a Compact and High Efficient Rectenna for RF Energy Harvesting
Measurement of burning velocities of hydrocarbon hydrogen mixtures and application to premixed laminar burner design
Measurement of burning velocities of hydrocarbon hydrogen mixtures and application to premixed laminar burner design
Admissions Apply Now