相关论文: Constraint-Based Software Diversification for Effi…

Modern software deployment process produces software that is uniform and hence vulnerable to large-scale code-reuse attacks, such as Jump-Oriented Programming (JOP) attacks. Compiler-based diversification improves the resilience of software…

Embedded devices are increasingly present in our everyday life. They often process critical information, and hence, rely on cryptographic protocols to achieve security. However, embedded devices remain vulnerable to attackers seeking to…

Software diversity protects against a modern-day exploits such as code-reuse attacks. When an attacker designs a code-reuse attack on an example executable, it relies on replicating the target environment. With software diversity, the…

Network diversity has been widely recognized as an effective defense strategy to mitigate the spread of malware. Optimally diversifying network resources can improve the resilience of a network against malware propagation. This work…

Diversity can significantly increase the resilience of systems, by reducing the prevalence of shared vulnerabilities and making vulnerabilities harder to exploit. Work on software diversity for security typically creates variants of a…

Test-time scaling has emerged as a promising approach for improving code generation by exploring large solution spaces at inference time. However, existing methods often rely on public test cases that are unavailable in practice, or require…

Software protection aims at safeguarding assets embedded in software by preventing and delaying reverse engineering and tampering attacks. This paper presents an architecture and supporting tool flow to renew parts of native applications…

The field of Distributed Constraint Optimization has gained momentum in recent years, thanks to its ability to address various applications related to multi-agent cooperation. Nevertheless, solving Distributed Constraint Optimization…

Diversity coding is a network restoration technique which offers near-hitless restoration, while other state-of-the art techniques are significantly slower. Furthermore, the extra spare capacity requirement of diversity coding is…

Code vulnerability detection is crucial for ensuring the security and reliability of modern software systems. Recently, Large Language Models (LLMs) have shown promising capabilities in this domain. However, notable discrepancies in…

Complex system design problems, such as those involved in aerospace engineering, require the use of numerically costly simulation codes in order to predict the performance of the system to be designed. In this context, these codes are often…

A number of security mechanisms have been proposed to harden programs written in unsafe languages, each of which mitigates a specific type of memory error. Intuitively, enforcing multiple security mechanisms on a target program will improve…

The predictability of program execution provides attackers a rich source of knowledge who can exploit it to spy or remotely control the program. Moving target defense addresses this issue by constantly switching between many diverse…

The ever growing demands of embedded systems to satisfy high computing performance and cost efficiency lead to the trend of using commercial off-the-shelf hardware. However, due to their highly integrated design they are becoming…

Clustering has been a major research topic in the field of machine learning, one to which Deep Learning has recently been applied with significant success. However, an aspect of clustering that is not addressed by existing deep clustering…

WebAssembly has become a crucial part of the modern web, offering a faster alternative to JavaScript in browsers. While boosting rich applications in browser, this technology is also very efficient to develop cryptojacking malware. This has…

Discrete diffusion models are a powerful, emerging paradigm for code generation. They construct programs through iterative refinement of partially corrupted token sequences and enable parallel token refinement. Importantly, this paradigm…

We describe decomposition during search (DDS), an integration of And/Or tree search into propagation-based constraint solvers. The presented search algorithm dynamically decomposes sub-problems of a constraint satisfaction problem into…

In the last few years, a growing body of research has proposed methods, techniques, and tools to support developers in the construction of software that consumes less energy. These solutions leverage diverse approaches such as version…

Compilers are complex, and significant effort has been expended on testing them. Techniques such as random program generation and differential testing have proved highly effective and have uncovered thousands of bugs in production…