Biblio

Bitcoin is popular not only with consumers, but also with cybercriminals (e.g., in ransomware and online extortion, and commercial online child exploitation). Given the potential of Bitcoin to be involved in a criminal investigation, the need to have an up-to-date and in-depth understanding on the forensic acquisition and analysis of Bitcoins is crucial. However, there has been limited forensic research of Bitcoin in the literature. The general focus of existing research is on postmortem analysis of specific locations (e.g. wallets on mobile devices), rather than a forensic approach that combines live data forensics and postmortem analysis to facilitate the identification, acquisition, and analysis of forensic traces relating to the use of Bitcoins on a system. Hence, the latter is the focus of this paper where we present an open source tool for live forensic and postmortem analysing automatically. Using this open source tool, we describe a list of target artifacts that can be obtained from a forensic investigation of popular Bitcoin clients and Web Wallets on different web browsers installed on Windows 7 and Windows 10 platforms.

Electromagnetic noise emitted from running computer displays modulates information about the picture frames being displayed on screen. Attacks have been demonstrated on eavesdropping computer displays by utilising these emissions as a side-channel vector. The accuracy of reconstructing a screen image depends on the emission sampling rate and bandwidth of the attackers signal acquisition hardware. The cost of radio frequency acquisition hardware increases with increased supported frequency range and bandwidth. A number of enthusiast-level, affordable software defined radio equipment solutions are currently available facilitating a number of radio-focused attacks at a more reasonable price point. This work investigates three accuracy influencing factors, other than the sample rate and bandwidth, namely noise removal, image blending, and image quality adjustments, that affect the accuracy of monitor image reconstruction through electromagnetic side-channel attacks.