Related papers: Towards Increasing Trust In Expert Evidence Derive…

Forensic science is usually taken to mean the application of a broad spectrum of scientific tools to answer questions of interest to the legal system. Despite such popular television series as CSI: Crime Scene Investigation and its…

Software plays a central role in scientific discovery. Improving how we develop and use software for research can have both broad and deep impacts on a spectrum of challenges and opportunities society faces today. The emergence of Research…

Malware detection is a constant challenge in cybersecurity due to the rapid development of new attack techniques. Traditional signature-based approaches struggle to keep pace with the sheer volume of malware samples. Machine learning offers…

Understanding how data quality aligns with regulatory requirements in machine learning (ML) systems presents a critical challenge for practitioners navigating the evolving EU regulatory landscape. To address this, we first propose a…

The ever increasing volume of data in digital forensic investigation is one of the most discussed challenges in the field. Usually, most of the file artefacts on seized devices are not pertinent to the investigation. Manually retrieving…

The frequency and harmfulness of cyber-attacks are increasing every day, and with them also the amount of data that the cyber-forensics analysts need to collect and analyze. In this paper, we propose a formal analysis process that allows an…

The rapid growth of Cloud Computing and Internet of Things (IoT) has significantly increased the interconnection of computational resources, creating an environment where malicious software (malware) can spread rapidly. To address this…

[Context and motivation]: Understanding and interpreting regulatory norms and inferring software requirements from them is a critical step towards regulatory compliance, a matter of significant importance in various industrial sectors.…

With the increasing extent of malware attacks in the present day along with the difficulty in detecting modern malware, it is necessary to evaluate the effectiveness and performance of Deep Neural Networks (DNNs) for malware classification.…

Machine learning has become an appealing signature-less approach to detect and classify malware because of its ability to generalize to never-before-seen samples and to handle large volumes of data. While traditional feature-based…

This paper examines the problems faced by Law Enforcement in searching large quantities of electronic evidence. It examines the use of ontologies as the basis for new forensic software filters and provides a proof of concept tool based on…

Case-hindering, multi-year digital forensic evidence backlogs have become commonplace in law enforcement agencies throughout the world. This is due to an ever-growing number of cases requiring digital forensic investigation coupled with the…

Android is the predominant mobile operating system for the past few years. The prevalence of devices that can be powered by Android magnetized not merely application developers but also malware developers with criminal intention to design…

Man-at-the-end (MATE) attackers have full control over the system on which the attacked software runs, and try to break the confidentiality or integrity of assets embedded in the software. Both companies and malware authors want to prevent…

Malware is being increasingly threatening and malware detectors based on traditional signature-based analysis are no longer suitable for current malware detection. Recently, the models based on machine learning (ML) are developed for…

This paper introduces a standardized model card framework specifically designed for digital and web forensics. Building upon established model card methodologies and recent work on abstract models for digital forensic analysis, this paper…

Industry practitioners care about small improvements in malware detection accuracy because their models are deployed to hundreds of millions of machines, meaning a 0.1\% change can cause an overwhelming number of false positives. However,…

Background: High-level system testing of applications that use data from e-Government services as input requires test data that is real-life-like but where the privacy of personal information is guaranteed. Applications with such strong…

Mobile malware has been growing in scale and complexity as smartphone usage continues to rise. Android has surpassed other mobile platforms as the most popular whilst also witnessing a dramatic increase in malware targeting the platform. A…

In recent years, there has been a significant surge in malware attacks, necessitating more advanced preventive measures and remedial strategies. While several successful AI-based malware classification approaches exist categorized into…