相关论文: Algorithmic Diversity for Software Security

Regenerating codes are a class of codes for distributed storage networks that provide reliability and availability of data, and also perform efficient node repair. Another important aspect of a distributed storage network is its security.…

Android malware still represents the most significant threat to mobile systems. While Machine Learning systems are increasingly used to identify these threats, past studies have revealed that attackers can bypass these detection mechanisms…

In its Vision and Strategy for Software for Science, Engineering, and Education the NSF states that it will invest in activities that: "Recognize that software strategies must include the secure and reliable deployment and operation of…

Growing cybersecurity risks in the power grid require that utilities implement a variety of security mechanism (SM) composed mostly of VPNs, firewalls, or other custom security components. While they provide some protection, they might…

Preventing data exfiltration from computer systems typically depends on perimeter defences, but these are becoming increasingly fragile. Instead we suggest an approach in which each at-risk document is supplemented by many fake versions of…

Diversification in a set of solutions has become a hot research topic in the evolutionary computation community. It has been proven beneficial for optimisation problems in several ways, such as computing a diverse set of high-quality…

In recent years, the number of cyber attacks has grown rapidly. An effective way to reduce the attack surface and protect software is adoption of methodologies that apply security at each step of the software development lifecycle. While…

The technical skill or ability of an individual is different to person in software developments of projects. So, it is necessary to identify the talent and attitude of an individual contribution can be uniformly distributed to the different…

Multi-variant execution (MVX) systems amplify the effectiveness of software diversity techniques. The key idea is to run multiple diversified program variants in lockstep while providing them with the same input and monitoring their…

Many existing deep learning models are vulnerable to adversarial examples that are imperceptible to humans. To address this issue, various methods have been proposed to design network architectures that are robust to one particular type of…

This paper introduces a novel approach for the automated selection of software protections to mitigate MATE risks against critical assets within software applications. We formalize the key elements involved in protection decision-making -…

We propose a novel approach to improving software security called Cryptographic Path Hardening, which is aimed at hiding security vulnerabilities in software from attackers through the use of provably secure and obfuscated cryptographic…

We study a proof methodology for verifying the safety of data invariants of highly-available distributed applications that replicate state. The proof is (1) modular: one can reason about each individual operation separately, and (2)…

Nowadays most of the malware applications are either packed or protected. This techniques are applied especially to evade signature based detectors and also to complicate the job of reverse engineers or security analysts. The time one must…

Motivated by the transformative impact of deep neural networks (DNNs) in various domains, researchers and anti-virus vendors have proposed DNNs for malware detection from raw bytes that do not require manual feature engineering. In this…

Neural networks are known to be vulnerable to adversarial examples. Carefully chosen perturbations to real images, while imperceptible to humans, induce misclassification and threaten the reliability of deep learning systems in the wild. To…

Many tools and libraries are readily available to build and operate distributed Web applications. While the setup of operational environments is comparatively easy, practice shows that their continuous secure operation is more difficult to…

In multiple domains such as malware detection, automated driving systems, or fraud detection, classification algorithms are susceptible to being attacked by malicious agents willing to perturb the value of instance covariates to pursue…

Dedicated software search engines that index open source software repositories or in-house software assets significantly enhance the chance of finding software components suitable for reuse. However, they still leave the work of evaluating…

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…