Social networking applications are a treasure trove for forensic examiners. The amount of potential evidence that they hold could sway the course of any investigation. However, the large number of mobile operating systems, their continuous updates, and the constant emergence of new social networking applications in the market, create challenges for forensic practitioners today. This paper hopes to alleviate some of those challenges by conducting a forensic analysis on two popular social networking applications; Instagram and Path on an iPhone 5s mobile device. The analysis process consisted of installing both applications on the device, performing common user activities via these applications, obtaining a forensically sound logical image of the device, and finally conducting manual- and automatic (for result verification)-forensic analysis on the acquired image. The ultimate goal of the analysis was to determine whether the activities conducted through these applications are stored on the mobile device's internal memory or not. The test results show that a portion of the activities is indeed stored in the internal memory. Therefore, the significance, extent, and locations of the stored information were all determined and documented in this paper.

Malware authors attempt in an endless effort to find new methods to evade the malware detection engines. A popular method is the use of obfuscation technologies that change the syntax of malicious code while preserving the execution semantics. This leads to the evasion of signatures that are built based on the code syntax. In this paper, we propose a novel approach to develop an evasion-resistant malware signature. This signature is based on the malware's execution profiles extracted from kernel data structure objects and neither uses malicious code syntax specific information code execution flow information. Thus, proposed signature is more resistant to obfuscation methods and resilient in detecting malicious code variants. To evaluate the effectiveness of the proposed approach, a prototype signature generation tool called SigGENE is developed. The effectiveness of signatures generated by SigGENE evaluated using an experimental root kit-simulation tool that employs techniques commonly found in rootkits. This simulationtool is obfuscated using several different methods. In further experiments, real-world malware samples that have different variants with the same behavior used to verify the real-world applicability of the approach. The experiments show that the proposed approach is effective, not only in generating a signature that detects the malware and its variants and defeats different obfuscation methods, but also, in producing an execution profiles that can be used to characterize different malicious attacks.

The paper describes a distributed brute-force attack on RC5 cipher using Java applets. It introduces a novel model for long-term parallel computing based on the abstraction of solvers with limited lifetime. The associated problems and scheduling policy are discussed. The paper comments on the inherent performance problems of the Java Virtual Machine and presents performance measurements of the cipher breaking applet for several computing platforms. © 1998 John Wiley & Sons, Ltd.