Detecting and Classifying Malware in Network Traffic

Akshithaa Parvathavardhini K.P; Nizar Banu P.K

doi:10.34256/ijcci2423

Akshithaa Parvathavardhini K.P Department of Computer Science CHRIST (Deemed to be University), Bangalore, Karnataka 560029, India
Nizar Banu P.K Department of Computer Science CHRIST (Deemed to be University), Bangalore, Karnataka 560029, India

Keywords: Android malware, Malware analysis, Malware category, Malware family, Classification, API call, Cyber threat, Behavioural analysis

Abstract

The range of threats of Android malware has grown due to the widespread use of Android devices. The intricacy and diversity of malware is always changing, making it difficult for conventional signature-based detection techniques to stay current. In this regard, network traffic analysis is a viable method for identifying and categorizing Android malware. Modern cybersecurity plans now include detecting and categorizing malware in network traffic as a vital component, given the increasing reliance of organizations for communication and data exchange over interconnected networks. The foundation of modern society is now the interchange of information over networked systems. The integrity and security of networked systems are seriously jeopardized by malware, which is one of the many cybersecurity dangers that digital infrastructures are exposed to due to their interconnection.

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