Acceleration of intrusion detection in encrypted network traffic using heterogeneous hardwareAcceleration of intrusion detection in encrypted network traffic using heterogeneous hardware Peer-Reviewed Journal Publication Δημοσίευση σε Περιοδικό με Κριτές 2023-01-262021enThis work was supported by the projects CONCORDIA, CyberSANE, I-BIDAAS, C4IIOT, and SPIDER, funded by the European Commission under Grant Agreements No. 830927, No. 833683, No. 780787, No. 833828, and No. 833685.This paper is an extended version of Papadogiannaki, E.; Deyannis, D.; Ioannidis, S. Head(er)Hunter: Fast Intrusion Detection Using Packet Metadata Signatures. In Proceedings of the 2020 IEEE 25th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), Pisa, Italy, 14–16 September 2020.More than 75% of Internet traffic is now encrypted, and this percentage is constantly increasing. The majority of communications are secured using common encryption protocols such as SSL/TLS and IPsec to ensure security and protect the privacy of Internet users. However, encryption can be exploited to hide malicious activities, camouflaged into normal network traffic. Traditionally, network traffic inspection is based on techniques like deep packet inspection (DPI). Common applications for DPI include but are not limited to firewalls, intrusion detection and prevention systems, L7 filtering, and packet forwarding. With the widespread adoption of network encryption though, DPI tools that rely on packet payload content are becoming less effective, demanding the development of more sophisticated techniques in order to adapt to current network encryption trends. In this work, we present HeaderHunter, a fast signature-based intrusion detection system even for encrypted network traffic. We generate signatures using only network packet metadata extracted from packet headers. In addition, we examine the processing acceleration of the intrusion detection engine using different heterogeneous hardware architectures.http://creativecommons.org/licenses/by/4.0/Sensors214Papadogiannaki_et_al_Sensors_21(4)_2021.pdfChania [Greece]Library of TUC2023-01-26application/pdf2.1 MBfree Papadogiannaki Eva Ioannidis Sotirios Ιωαννιδης Σωτηριος MDPI Network intrusion detection Encrypted network traffic Encrypted network traffic inspection Network packet metadata GPGPUs Integrated GPU OpenCL