Related papers: Demystifying the Vulnerability Propagation and Its…
Recent years have witnessed a rise in real-world data captured with rich structural information that can be conveniently depicted by multi-relational graphs. While inference of continuous node features across a simple graph is rather…
We study cascading failures in a system comprising interdependent networks/systems, in which nodes rely on other nodes both in the same system and in other systems to perform their function. The (inter-)dependence among nodes is modeled…
Industrial applications heavily integrate open-source software libraries nowadays. Beyond the benefits that libraries bring, they can also impose a real threat in case a library is affected by a vulnerability but its community is not active…
We investigate the evolution rules and degree distribution properties of the Software Heritage dataset, a large-scale growing network linking software source-code versions from open-source communities. The network spans more than 40 years…
Vulnerability databases, such as the National Vulnerability Database (NVD), offer detailed descriptions of Common Vulnerabilities and Exposures (CVEs), but often lack information on their real-world impact, such as the tactics, techniques,…
Current software supply chains heavily rely on open-source packages hosted in public repositories. Given the popularity of ecosystems like npm and PyPI, malicious users started to spread malware by publishing open-source packages containing…
An Operating System (OS) combines multiple interdependent software packages, which usually have their own independently developed architectures. When a multitude of independent packages are placed together in an OS, an implicit…
Deep learning-based approaches for software vulnerability prediction currently mainly rely on the original text of software code as the feature of nodes in the graph of code and thus could learn a representation that is only specific to the…
Graph Neural Networks (GNNs) are neural models that leverage the dependency structure in graphical data via message passing among the graph nodes. GNNs have emerged as pivotal architectures in analyzing graph-structured data, and their…
The Maven Central Repository provides an extraordinary source of data to understand complex architecture and evolution phenomena among Java applications. As of September 6, 2018, this repository includes 2.8M artifacts (compiled piece of…
Relation Extraction (RE) is one of the fundamental tasks in Information Extraction and Natural Language Processing. Dependency trees have been shown to be a very useful source of information for this task. The current deep learning models…
This article studies disruption tolerant networks (DTNs) where each node knows the probabilistic distribution of contacts with other nodes. It proposes a framework that allows one to formalize the behaviour of such a network. It generalizes…
The adoption of the distributed paradigm has allowed applications to increase their scalability, robustness and fault tolerance, but it has also complicated their structure, leading to an exponential growth of the applications'…
We present a formal treatment of provenance trees, directed acyclic graphs of artifact registrations anchored immutably on a public blockchain, and introduce the operator trust problem: when a single privileged operator submits all on-chain…
Long-horizon wildfire risk forecasting requires generating probabilistic spatial fields under sparse event supervision while maintaining computational efficiency across multiple prediction horizons. Extending diffusion models to multi-step…
To provide privacy-aware software systems, it is crucial to consider privacy from the very beginning of the development. However, developers do not have the expertise and the knowledge required to embed the legal and social requirements for…
Detecting security vulnerabilities in open-source software is a critical task that is highly regarded in the related research communities. Several approaches have been proposed in the literature for detecting vulnerable codes and…
Research on the vulnerability of electric networks with a complex network approach has produced significant results in the last decade, especially for transmission networks. These studies have shown that there are causal relations between…
In the NP-hard Optimizing PD with Dependencies (PDD) problem, the input consists of a phylogenetic tree $T$ over a set of taxa $X$, a food-web that describes the prey-predator relationships in $X$, and integers $k$ and $D$. The task is to…
Cybersecurity threats are increasingly marked by interdependence, uncertainty, and evolving complexity challenges that traditional assessment methods such as CVSS, STRIDE, and attack trees fail to adequately capture. This paper reviews the…