Machine Learning for Traffic Analysis: A Review
Nour Alqudah, Qussai Yaseen
Abstract
Traffic analysis has many purposes such as evaluating the performance and security of network operations and management. Therefore, network traffic analysis is considered vital for improving networks operation and security. This paper discusses different machine learning approaches for traffic analysis. Increased network traffic and the development of artificial intelligence require new ways to detect intrusions, analyze malware behavior, and categorize Internet traffic and other security aspects. Machine learning (ML) shows effective capabilities in solving network problems. A review of the techniques used in the traffic analysis is presented in this paper.
Topics & Concepts
Computer scienceTraffic analysisMalwareNetwork securityComputer securityMalware analysisNetwork traffic controlThe InternetTraffic generation modelCategorizationTraffic classificationArtificial intelligenceMachine learningComputer networkWorld Wide WebNetwork packetNetwork Security and Intrusion DetectionInternet Traffic Analysis and Secure E-votingAdvanced Malware Detection Techniques