A Study on Deep Learning Methods Used for Intrusion Detection and Prevention

A Study on Deep Learning Methods Used for Intrusion Detection and Prevention

Sonali V. R. P. Reddy1, Nadine Dias2

1Student, Information Technology Department, Goa College of Engineering, Farmagudi, Goa.

2Assistant professor, Information Technology Department, Goa College of Engineering, Farmagudi, Goa.

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Abstract - Cyberattacks are growing swiftly as the Internet grows, and the situation of cyber security is not encouraging. The availability of vital services is disrupted by denial-of-service (DoS) attacks, one of the most dangerous security risks facing the Internet today. The range of attack strategies and the amount of real-time traffic that has to be analysed provide a barrier to DoS detection. This study report describes key literature surveys about detecting and preventing denial of service (DoS) attacks using different deep learning methods.

Key Words:  Deep Learning, Intrusion Detection, Intrusion Prevention, Network, TensorFlow.