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Acceleration of intrusion detection in encrypted network traffic using heterogeneous hardware

Papadogiannaki Eva, Ioannidis Sotirios

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Extent21 pagesen
TitleAcceleration of intrusion detection in encrypted network traffic using heterogeneous hardwareen
CreatorPapadogiannaki Evaen
CreatorIoannidis Sotiriosen
CreatorΙωαννιδης Σωτηριοςel
Content SummaryMore 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.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Date of Item2023-01-26-
Date of Publication2021-
SubjectNetwork intrusion detectionen
SubjectEncrypted network trafficen
SubjectEncrypted network traffic inspectionen
SubjectNetwork packet metadataen
SubjectIntegrated GPUen
Bibliographic CitationE. Papadogiannaki and S. Ioannidis, “Acceleration of intrusion detection in encrypted network traffic using heterogeneous hardware,” Sensors, vol. 21, no. 4, Feb. 2021, doi: 10.3390/s21041140.en

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