Related papers: Responding to Living-Off-the-Land Tactics using Ju…
Memory forensics is an effective methodology for analyzing living-off-the-land malware, including threats that employ evasion, obfuscation, anti-analysis, and steganographic techniques. By capturing volatile system state, memory analysis…
Userland memory forensics has become a critical component of smartphone investigations and incident response, enabling the recovery of volatile evidence such as deleted messages from end-to-end encrypted apps and cryptocurrency…
Living-off-the-land (LOTL) techniques pose a significant challenge to security operations, exploiting legitimate tools to execute malicious commands that evade traditional detection methods. To address this, we present a robust augmentation…
The reliability of cyber forensic evidence acquisition is strongly influenced by the underlying operating systems, Windows, macOS, and Linux - due to inherent variations in file system structures, encryption protocols, and forensic tool…
Volatile memory dump and its analysis is an essential part of digital forensics. Among a number of various software and hardware approaches for memory dumping there are authors who point out that some of these approaches are not resilient…
The increasing popularity of deep learning (DL) models and the advantages of computing, including low latency and bandwidth savings on smartphones, have led to the emergence of intelligent mobile applications, also known as DL apps, in…
Mobile devices implementing Android operating systems inherently create opportunities to present environments that are conducive to anti-forensic activities. Previous mobile forensics research focused on applications and data hiding…
In recent years, enterprises have been targeted by advanced adversaries who leverage creative ways to infiltrate their systems and move laterally to gain access to critical data. One increasingly common evasive method is to hide the…
In high-dimensional robotic path planning, traditional sampling-based methods often struggle to efficiently identify both feasible and optimal paths in complex, multi-obstacle environments. This challenge is intensified in robotic…
New computing paradigms, modern feature-rich programming languages and off-the-shelf software libraries enabled the development of new sophisticated malware families. Evidence of this phenomena is the recent growth of fileless malware…
This paper focuses on conducting forensic data analysis of 2 widely used IMs applications on Android phones WhatsApp and Viber. The tests and analysis were performed with the aim of determining what data and information can be found on the…
IoT devices and sensors have been utilized in a cooperative manner to enable the concept of a smart environment. In these smart settings, abundant data is generated as a result of the interactions between devices and users' day-to-day…
Location sharing applications are becoming increasingly common. These applications allow users to share their own locations and view contacts' current locations on a map. Location applications are commonly used by friends and family members…
The rapid growth of mobile applications has escalated Android malware threats. Although there are numerous detection methods, they often struggle with evolving attacks, dataset biases, and limited explainability. Large Language Models…
The ChatGPT Windows application offers better user interaction in the Windows operating system (OS) by enhancing productivity and streamlining the workflow of ChatGPT's utilization. However, there are potential misuses associated with this…
This Research proposes a Novel Reinforcement Learning (RL) model to optimise malware forensics investigation during cyber incident response. It aims to improve forensic investigation efficiency by reducing false negatives and adapting…
In the past decade, the cyber-crime related to mobile devices has increased. Mobile devices, especially the ones running on Android operating system are particularly interesting to malware creators, as the users often keep the biggest…
Currently, Android malware detection is mostly performed on server side against the increasing number of malware. Powerful computing resource provides more exhaustive protection for app markets than maintaining detection by a single user.…
This paper proposes a simple yet effective jailbreak attack named FlipAttack against black-box LLMs. First, from the autoregressive nature, we reveal that LLMs tend to understand the text from left to right and find that they struggle to…
The Android operating system has become the most popular operating system for smartphones and tablets leading to a rapid rise in malware. Sophisticated Android malware employ detection avoidance techniques in order to hide their malicious…