A survey on Effective Machine Learning Techniques in the field of Cyber Security

Main Article Content

Rishin Pandit
Lagan Gupta
Dr. MANIKANDAN K

Abstract

Machine learning techniques have many cybersecurity applications, and they have entered the mainstream in a variety of fields. Examples include threat analysis, anomaly-based intrusion detection of frequent attacks on important infrastructures, malware analysis, particularly for zero-day malware detection, and many others. Machine learning-based detection is being employed by researchers in many cybersecurity solutions as a result of the inefficiency of signature-based methods in identifying zero day attacks or even modest modifications of existing assaults. In this paper, we cover a number of cybersecurity applications for machine learning. We also give a few examples of adversarial assaults on machine learning algorithms that aim to corrupt classifiers' training and test data in order to render them useless.


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Author Biographies

Rishin Pandit

4th year B.tech in CSE Student at VIT Vellore

Lagan Gupta

4th year B.tech in CSE Student at VIT Vellore

Dr. MANIKANDAN K

Associate Professor Sr

School of Computer Science and Engineering

Vellore Institute of Technology

Vellore, Tamil Nadu, India