7,773 research outputs found
A Survey of Techniques for Improving Security of GPUs
Graphics processing unit (GPU), although a powerful performance-booster, also
has many security vulnerabilities. Due to these, the GPU can act as a
safe-haven for stealthy malware and the weakest `link' in the security `chain'.
In this paper, we present a survey of techniques for analyzing and improving
GPU security. We classify the works on key attributes to highlight their
similarities and differences. More than informing users and researchers about
GPU security techniques, this survey aims to increase their awareness about GPU
security vulnerabilities and potential countermeasures
A Forensically Sound Adversary Model for Mobile Devices
In this paper, we propose an adversary model to facilitate forensic
investigations of mobile devices (e.g. Android, iOS and Windows smartphones)
that can be readily adapted to the latest mobile device technologies. This is
essential given the ongoing and rapidly changing nature of mobile device
technologies. An integral principle and significant constraint upon forensic
practitioners is that of forensic soundness. Our adversary model specifically
considers and integrates the constraints of forensic soundness on the
adversary, in our case, a forensic practitioner. One construction of the
adversary model is an evidence collection and analysis methodology for Android
devices. Using the methodology with six popular cloud apps, we were successful
in extracting various information of forensic interest in both the external and
internal storage of the mobile device
A Novel Method for Moving Laterally and Discovering Malicious Lateral Movements in Windows Operating Systems: A Case Study
Lateral movement is a pervasive threat because modern networked systems that provide access to multiple users are far more efficient than their non-networked counterparts. It is a well-known attack methodology with extensive research conducted investigating the prevention of lateral movement in enterprise systems. However, attackers use increasingly sophisticated methods to move laterally that bypass typical detection systems. This research comprehensively reviews the problems in lateral movement detection and outlines common defenses to protect modern systems from lateral movement attacks. A literature review outlines techniques for automatic detection of malicious lateral movement, explaining common attack methods utilized by advanced persistent threats and components built into the Windows operating system that can assist with discovering malicious lateral movement. Finally, a novel approach for moving laterally designed by other security researchers is reviewed and studied, an original process for detecting this method of lateral movement is proposed, and the application of the detection methodology is also expanded
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