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Digital forensic investigation has become more challenging due to the rapid growth in the volume of encountered data. It is difficult for an investigator to examine the entire volume of encountered data manually. Approximate Matching…
Grey literature is essential to software engineering research as it captures practices and decisions that rarely appear in academic venues. However, collecting and assessing it at scale remains difficult because of their heterogeneous…
In high-stakes settings, Machine Learning models that can provide predictions that are interpretable for humans are crucial. This is even more true with the advent of complex deep learning based models with a huge number of tunable…
Predictive systems, in particular machine learning algorithms, can take important, and sometimes legally binding, decisions about our everyday life. In most cases, however, these systems and decisions are neither regulated nor certified.…
The Cloud-Edge continuum enhances application performance by bringing computation closer to data sources. However, it presents considerable challenges in managing resources and determining service placement, as these tasks require…
The number of cyber attacks has increased tremendously in the last few years. This resulted into both human and financial losses at the individual and organization levels. Recently, cyber-criminals are leveraging new skills and capabilities…
Network Forensics (NFs) is a branch of digital forensics which used to detect and capture potential digital crimes over computer networked environments crime. Network Forensic Tools (NFTs) and Network Forensic Processes (NFPs) have…
We present Copyright Detective, the first interactive forensic system for detecting, analyzing, and visualizing potential copyright risks in LLM outputs. The system treats copyright infringement versus compliance as an evidence discovery…
Deep Audio Analyzer is an open source speech framework that aims to simplify the research and the development process of neural speech processing pipelines, allowing users to conceive, compare and share results in a fast and reproducible…
Nonlinear PDEs give rise to complex dynamics that are often difficult to analyze in state space due to their relatively large numbers of degrees of freedom, ill-conditioned operators, and changing spatial and parameter resolution…
In digital forensics and various sectors like medicine and supply chain, blockchains play a crucial role in providing a secure and tamper-resistant system that meticulously records every detail, ensuring accountability. However,…
Visual surveillance systems have become one of the largest data sources of Big Visual Data in real world. However, existing systems for video analysis still lack the ability to handle the problems of scalability, expansibility and…
Smartphones have created a significant impact on the day to day activities of every individual. Now a days a wide range of Smartphone applications are available and it necessitates high computing resources in order to build these…
There is a growing demand for cloud storage services such as Dropbox, Box, Syncplicity and SugarSync. These public cloud storage services can store gigabytes of corporate and personal data in remote data centres around the world, which can…
The ever-increasing workload of digital forensic labs raises concerns about law enforcement's ability to conduct both cyber-related and non-cyber-related investigations promptly. Consequently, this article explores the potential and…
Large language models hold considerable promise for supporting forensic investigations, but their widespread adoption is hindered by a lack of transparency, explainability, and reproducibility. This paper explores how the emerging Model…
The classification of file fragments of various file formats is an essential task in various applications such as firewalls, intrusion detection systems, anti-viruses, web content filtering, and digital forensics. However, the community…
Due to the increasing availability and functionality of image editing tools, many forensic techniques such as digital image authentication, source identification and tamper detection are important for forensic image analysis. In this paper,…
Threshold-free cluster enhancement (TFCE) is widely used for cluster-based inference in neuroimaging, but existing implementations typically rely on discretized approximations that may introduce numerical variability. We present eTFCE, an…
Epistemic protocol specifications allow programs, for settings in which multiple agents act with incomplete information, to be described in terms of how actions are related to what the agents know. They are a variant of the knowledge-based…