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Packet Analysis For Network Forensics: A Comprehensive Survey, Leslie F. Sikos
Packet Analysis For Network Forensics: A Comprehensive Survey, Leslie F. Sikos
Research outputs 2014 to 2021
Packet analysis is a primary traceback technique in network forensics, which, providing that the packet details captured are sufficiently detailed, can play back even the entire network traffic for a particular point in time. This can be used to find traces of nefarious online behavior, data breaches, unauthorized website access, malware infection, and intrusion attempts, and to reconstruct image files, documents, email attachments, etc. sent over the network. This paper is a comprehensive survey of the utilization of packet analysis, including deep packet inspection, in network forensics, and provides a review of AI-powered packet analysis methods with advanced network traffic …
Rdtids: Rules And Decision Tree-Based Intrusion Detection System For Internet-Of-Things Networks, Mohammad Amine Ferrag, Leandros Maglaras, Ahmed Ahmim, Makhlouf Derdour, Helge Janicke
Rdtids: Rules And Decision Tree-Based Intrusion Detection System For Internet-Of-Things Networks, Mohammad Amine Ferrag, Leandros Maglaras, Ahmed Ahmim, Makhlouf Derdour, Helge Janicke
Research outputs 2014 to 2021
This paper proposes a novel intrusion detection system (IDS), named RDTIDS, for Internet-of-Things (IoT) networks. The RDTIDS combines different classifier approaches which are based on decision tree and rules-based concepts, namely, REP Tree, JRip algorithm and Forest PA. Specifically, the first and second method take as inputs features of the data set, and classify the network traffic as Attack/Benign. The third classifier uses features of the initial data set in addition to the outputs of the first and the second classifier as inputs. The experimental results obtained by analyzing the proposed IDS using the CICIDS2017 dataset and BoT-IoT dataset, attest …