NDLI: BlindIDS: Market-Compliant and Privacy-Friendly Intrusion Detection System over Encrypted Traffic

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BlindIDS: Market-Compliant and Privacy-Friendly Intrusion Detection System over Encrypted Traffic

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BlindIDS: Market-Compliant and Privacy-Friendly Intrusion Detection System over Encrypted Traffic

Content Provider	ACM Digital Library
Author	Kheir, Nizar Paindavoine, Marie Sabt, Mohamed Diop, Aïda Canard, Sébastien
Abstract	The goal of network intrusion detection is to inspect network traffic in order to identify threats and known attack patterns. One of its key features is Deep Packet Inspection (DPI), that extracts the content of network packets and compares it against a set of detection signatures. While DPI is commonly used to protect networks and information systems, it requires direct access to the traffic content, which makes it blinded against encrypted network protocols such as HTTPS. So far, a difficult choice was to be made between the privacy of network users and security through the inspection of their traffic content to detect attacks or malicious activities. This paper presents a novel approach that bridges the gap between network security and privacy. It makes possible to perform DPI directly on encrypted traffic, without knowing neither the traffic content, nor the patterns of detection signatures. The relevance of our work is that it preserves the delicate balance in the security market ecosystem. Indeed, security editors will be able to protect their distinctive detection signatures and supply service providers only with encrypted attack patterns. In addition, service providers will be able to integrate the encrypted signatures in their architectures and perform DPI without compromising the privacy of network communications. Finally, users will be able to preserve their privacy through traffic encryption, while also benefiting from network security services. The extensive experiments conducted in this paper prove that, compared to existing encryption schemes, our solution reduces by 3 orders of magnitude the connection setup time for new users, and by 6 orders of magnitude the consumed memory space on the DPI appliance.
Starting Page	561
Ending Page	574
Page Count	14
File Format	PDF
ISBN	9781450349444
DOI	10.1145/3052973.3053013
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-04-02
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Network middleboxes Privacy Intrusion detection Deep packet inspection Security Decryptable searchable encryption
Content Type	Text
Resource Type	Article

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