相关论文: Towards Increasing Trust In Expert Evidence Derive…

Digital systems find it challenging to keep up with cybersecurity threats. The daily emergence of more than 560,000 new malware strains poses significant hazards to the digital ecosystem. The traditional malware detection methods fail to…

The increasingly sophisticated environment in which attackers operate makes software security an even greater challenge in open-source projects, where malicious packages are prevalent. Static analysis tools, such as Malcontent, are highly…

Perimeter-based detection is no longer sufficient for mitigating the threat posed by malicious software. This is evident as antivirus (AV) products are replaced by endpoint detection and response (EDR) products, the latter allowing…

As malware continues to become more complex and harder to detect, Malware Analysis needs to continue to evolve to stay one step ahead. One promising key area approach focuses on using system calls and API Calls, the core communication…

Malware detection increasingly relies on AI systems that integrate signature-based detection with machine learning. However, these components are typically developed and combined in isolation, missing opportunities to reduce data complexity…

As our professional, social, and financial existences become increasingly digitized and as our government, healthcare, and military infrastructures rely more on computer technologies, they present larger and more lucrative targets for…

Background: Evaluation of the quality of research software is a challenging and relevant issue, still not sufficiently addressed by the scientific community. Methods: Our contribution begins by defining, precisely but widely enough, the…

The mass production of complex software has made it impossible to manually test it for security vulnerabilities. Automated security testing tools come in a variety of flavors, function at various stages of software development, and target…

Given the ever-increasing prevalence of technology in modern life, there is a corresponding increase in the likelihood of digital devices being pertinent to a criminal investigation or civil litigation. As a direct consequence, the number…

The popularity of Android OS has made it an appealing target to malware developers. To evade detection, including by ML-based techniques, attackers invest in creating malware that closely resemble legitimate apps. In this paper, we propose…

As any scientific discipline, the software engineering (SE) research community strives to contribute to the betterment of the target population of our research: software producers and consumers. We will only achieve this betterment if we…

We aim to conduct a systematic mapping in the area of testing ML programs. We identify, analyze and classify the existing literature to provide an overview of the area. We followed well-established guidelines of systematic mapping to…

Due to its critical role in cybersecurity, digital forensics has received significant attention from researchers and practitioners alike. The ever increasing sophistication of modern cyberattacks is directly related to the complexity of…

Despite the tremendous advances that have been made in the last decade on developing useful machine-learning applications, their wider adoption has been hindered by the lack of strong assurance guarantees that can be made about their…

Applying deep learning to malware detection has drawn great attention due to its notable performance. With the increasing prevalence of cyberattacks targeting IoT devices, there is a parallel rise in the development of malware across…

For the dramatic increase of Android malware and low efficiency of manual check process, deep learning methods started to be an auxiliary means for Android malware detection these years. However, these models are highly dependent on the…

In recent years, many studies have applied wearable devices to capture psychophysiological data from software developers. However, the current literature lacks investigations that classify the studies and point out gaps to be explored. This…

Today a lot of digital evidences for crime investigation includes a geospatial component. This data comes from various sources such as smartphones, tablets, navigation systems, digital camera with global positioning system (GPS), etc. The…

Machine-learning models have been recently used for detecting malicious Android applications, reporting impressive performances on benchmark datasets, even when trained only on features statically extracted from the application, such as…

Financial forensics has an important role in the field of finance to detect and investigate the occurrence of finance related crimes like money laundering. However, as with other forms of criminal activities, the forensics analysis of such…