activity
20142023
most citedVulDeePecker: A Deep Learning-Based System for Multiclass Vulnerability Detection

211 citations · 264 across the 6 of their papers we have counts for

collaborators

6 papers

eess.SY2023

Analysis of Contagion Dynamics with Active Cyber Defenders

Keith Paarporn, Shouhuai Xu

In this paper, we analyze the infection spreading dynamics of malware in a population of cyber nodes (i.e., computers or devices). Unlike most prior studies where nodes are reactiv…

cs.CR202334 cited

PAD: Towards Principled Adversarial Malware Detection Against Evasion Attacks

Deqiang Li, Shicheng Cui, Yun Li +3

Machine Learning (ML) techniques can facilitate the automation of malicious software (malware for short) detection, but suffer from evasion attacks. Many studies counter such attac…

cs.GT20221 cited

A Coupling Approach to Analyzing Games with Dynamic Environments

Brandon C. Collins, Shouhuai Xu, Philip N. Brown

The theory of learning in games has extensively studied situations where agents respond dynamically to each other by optimizing a fixed utility function. However, in real situation…

cs.CR2021

Quantifying Cybersecurity Effectiveness of Dynamic Network Diversity

Huashan Chen, Hasan Cam, Shouhuai Xu

The deployment of monoculture software stacks can have devastating consequences because a single attack can compromise all of the vulnerable computers in cyberspace. This one-vulne…

cs.CR2020211 cited

VulDeePecker: A Deep Learning-Based System for Multiclass Vulnerability Detection

Deqing Zou, Sujuan Wang, Shouhuai Xu +2

Fine-grained software vulnerability detection is an important and challenging problem. Ideally, a detection system (or detector) not only should be able to detect whether or not a…

cs.CR201418 cited

An Evasion and Counter-Evasion Study in Malicious Websites Detection

Li Xu, Zhenxin Zhan, Shouhuai Xu +1

Malicious websites are a major cyber attack vector, and effective detection of them is an important cyber defense task. The main defense paradigm in this regard is that the defende…