Design of effective solutions against insider attacks

• Main Author: Yen, Yi Lin
• Other Authors: Ma Maode
• Format: Final Year Project
• Language: English
• Published: 2018
• Subjects: DRNTU::Engineering::Electrical and electronic engineering::Wireless communication systems; DRNTU::Engineering
• Online Access: http://hdl.handle.net/10356/74862
• Institution: Nanyang Technological University

Cybersecurity is gaining importance as we move towards the 21st century, where technology is embraced and used throughout organizations, governments and businesses across the world. As technology advances, so does the rate of cyber threats as cybercriminals learn and become more sophisticated in their attack strategies. Cyber attacks can happen both externally and internally. With the majority of attacks reported to be from insiders, it is important to be able to detect insider attacks and even prevent it. Network traffic analytics has been found to have many applications in detecting insider attacks, particularly in the area of botnet detection. This project will be looking at detecting botnet traffic by using network traffic analytics, with the aid of Machine Learning techniques.