Traditionally, network-based intrusion detection systems (NIDS) monitor network traffic for signs of malicious activities. However, with the growing use of virtual private networks (VPNs) that encrypt network traffic, the NIDS can no longer analyse the encrypted data. This essentially negates any protection offered by the NIDS. Although the encrypted traffic can be decrypted at a network gateway for analysis, this compromises on data confidentiality. In this paper, we propose a detection framework which allows a traditional NIDS to continue functioning, without compromising the confidentiality afforded by the VPN. Our approach uses Shamir's secret-sharing scheme and randomised network proxies to enable detection of malicious activities in encrypted channels. Additionally, this approach is able to detect any malicious attempts to forge network traffic with the intention of evading detection. Our experiments show that the probability of a successful evasion is low, at about 0.98% in the worst case. We implement our approach in a prototype and present some preliminary results. Overall, the proposed approach is able to consistently detect intrusions and does not introduce any additional false positives.

This paper presents some results on multiple error detection and correction based on the Redundant Residue Number System (RRNS). RRNS is often used in parallel processing environments because of its ability to increase the robustness of information passing between the processors. The proposed multiple error correction scheme utilizes the Chinese Remainder Theorem(CRT) together with a novel algorithm that significantly simplifies the error correcting process for integers. An extension of the scheme further reduces the computational complexity without compromising its error correcting capability. Proofs and examples are provided for the coding technique.