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A Novel Privacy Preserving User Identification Approach For Network Traffic, Nathan Clarke, Fudong Li, Steven Furnell
A Novel Privacy Preserving User Identification Approach For Network Traffic, Nathan Clarke, Fudong Li, Steven Furnell
Research outputs 2014 to 2021
The prevalence of the Internet and cloud-based applications, alongside the technological evolution of smartphones, tablets and smartwatches, has resulted in users relying upon network connectivity more than ever before. This results in an increasingly voluminous footprint with respect to the network traffic that is created as a consequence. For network forensic examiners, this traffic represents a vital source of independent evidence in an environment where anti-forensics is increasingly challenging the validity of computer-based forensics. Performing network forensics today largely focuses upon an analysis based upon the Internet Protocol (IP) address – as this is the only characteristic available. More typically, …
Cyber Blackbox For Collecting Network Evidence, Jooyoung Lee, Sunoh Choi, Yangseo Choi, Jonghyun Kim, Ikkyun Kim, Youngseok Lee
Cyber Blackbox For Collecting Network Evidence, Jooyoung Lee, Sunoh Choi, Yangseo Choi, Jonghyun Kim, Ikkyun Kim, Youngseok Lee
Australian Digital Forensics Conference
In recent years, the hottest topics in the security field are related to the advanced and persistent attacks. As an approach to solve this problem, we propose a cyber blackbox which collects and preserves network traffic on a virtual volume based WORM device, called EvidenceLock to ensure data integrity for security and forensic analysis. As a strategy to retain traffic for long enough periods, we introduce a deduplication method. Also this paper includes a study on the network evidence which is collected and preserved for analyzing the cause of cyber incident. Then, a method is proposed to suggest a starting …