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Modern Large Language Model (LLM) systems are assembled from third-party artifacts such as pre-trained weights, fine-tuning adapters, datasets, dependency packages, and container images, fetched through automated pipelines. This speed comes…
The Internet, as a global system of interconnected networks, carries an extensive array of information resources and services. Key requirements include good quality-of-service and protection of the infrastructure from nefarious activity…
Abstract- The vision of the Linked Open Data (LOD) initiative is to provide a distributed model for publishing and meaningfully interlinking open data. The realization of this goal depends strongly on the quality of the data that is…
Integrity and security of the data in database systems are typically maintained with access control policies and firewalls. However, insider attacks -- where someone with an intimate knowledge of the system and administrative privileges…
Market integrity monitoring is difficult because suspicious price/volume behavior can arise from many benign mechanisms, while modern detection systems often rely on opaque models that are hard to audit and communicate. We present AIMM-X,…
Industrial control systems (ICSs) often consist of many legacy devices, which were designed without security requirements in mind. With the increase in cyberattacks targeting critical infrastructure, there is a growing urgency to develop…
The resilience of cyberphysical systems to denial-of-service (DoS) and integrity attacks is studied in this paper. The cyberphysical system is modeled as a linear structured system, and its resilience to an attack is interpreted in a graph…
The use of free and open source software (FOSS) components in all software systems is estimated to be above 90%. With such high usage and because of the heterogeneity of FOSS tools, repositories, developers and ecosystem, the level of…
The Software Bill of Materials (SBOM) has emerged as a promising solution, providing a machine-readable inventory of software components used, thus bolstering supply chain security. This paper presents an extensive study concerning the…
Realistic, large-scale, and well-labeled cybersecurity datasets are essential for training and evaluating Intrusion Detection Systems (IDS). However, they remain difficult to obtain due to privacy constraints, data sensitivity, and the cost…
Large Language Models (LLMs) demonstrate impressive capabilities across various fields, yet their increasing use raises critical security concerns. This article reviews recent literature addressing key issues in LLM security, with a focus…
Researchers in the highly active field of intrusion detection largely rely on public datasets for their experimental evaluations. However, the large number of existing datasets, the discovery of previously unknown flaws therein, and the…
In the distributed and dynamic framework of the Web, data quality is a big challenge. The Linked Open Data (LOD) provides an enormous amount of data, the quality of which is difficult to control. Quality is intrinsically a matter of usage,…
Connected societies require reliable measures to assure the safety, privacy, and security of members. Public safety technology has made fundamental improvements since the first generation of surveillance cameras were introduced, which aims…
Data Availability Sampling (DAS), a central component of Ethereum's roadmap, enables clients to verify data availability without requiring any single client to download the entire dataset. DAS operates by having clients randomly retrieve…
Logistics Information System (LIS) is an interactive system that provides information for logistics managers to monitor and track logistics business. In recent years, with the rise of online shopping, LIS is becoming increasingly important.…
The performance of Large Language Models (LLMs) is determined by their training data. Despite the proliferation of open-weight LLMs, access to LLM training data has remained limited. Even for fully open LLMs, the scale of the data makes it…
Network penetration testing identifies the exploits and vulnerabilities those exist within computer network infrastructure and help to confirm the security measures. The objective of this paper is to explain methodology and methods behind…
Although ransomware has received broad attention in media and research, this evolving threat vector still poses a systematic threat. Related literature has explored their detection using various approaches leveraging Machine and Deep…
The deployment of Large Language Models (LLMs) in robotic systems presents unique safety challenges, particularly in unpredictable environments. Although LLMs, leveraging zero-shot learning, enhance human-robot interaction and…