b'Shouhuai Xu'

research

∙ 09/09/2023

Characterizing Cyber Attacks against Space Systems with Missing Data: Framework and Case Study

Cybersecurity of space systems is an emerging topic, but there is no sin...

0 Ekzhin Ear, et al. ∙

research

∙ 07/10/2023

Towards Automated Cyber Range Design: Characterizing and Matching Demands to Supplies

Cyber ranges mimic real-world cyber environments and are in high demand....

0 Ekzhin Ear, et al. ∙

research

∙ 02/22/2023

PAD: Towards Principled Adversarial Malware Detection Against Evasion Attacks

Machine Learning (ML) techniques facilitate automating malicious softwar...

0 Deqiang Li, et al. ∙

research

∙ 07/13/2022

A Coupling Approach to Analyzing Games with Dynamic Environments

The theory of learning in games has extensively studied situations where...

0 Brandon C. Collins, et al. ∙

research

∙ 03/15/2022

SoK: Why Have Defenses against Social Engineering Attacks Achieved Limited Success?

Social engineering attacks are a major cyber threat because they often s...

0 Theodore Longtchi, et al. ∙

research

∙ 12/15/2021

Quantifying Cybersecurity Effectiveness of Dynamic Network Diversity

The deployment of monoculture software stacks can have devastating conse...

0 Huashan Chen, et al. ∙

research

∙ 11/19/2021

Quantifying Cybersecurity Effectiveness of Software Diversity

The deployment of monoculture software stacks can cause a devastating da...

0 Huashan Chen, et al. ∙

research

∙ 09/20/2021

Can We Leverage Predictive Uncertainty to Detect Dataset Shift and Adversarial Examples in Android Malware Detection?

The deep learning approach to detecting malicious software (malware) is ...

0 Deqiang Li, et al. ∙

research

∙ 08/02/2021

Towards Making Deep Learning-based Vulnerability Detectors Robust

Automatically detecting software vulnerabilities in source code is an im...

0 Zhen Li, et al. ∙

research

∙ 02/25/2021

Data-Driven Characterization and Detection of COVID-19 Themed Malicious Websites

COVID-19 has hit hard on the global community, and organizations are wor...

0 Mir Mehedi Ahsan Pritom, et al. ∙

research

∙ 02/25/2021

Characterizing the Landscape of COVID-19 Themed Cyberattacks and Defenses

COVID-19 (Coronavirus) hit the global society and economy with a big sur...

0 Mir Mehedi Ahsan Pritom, et al. ∙

research

∙ 10/09/2020

On the Security of Group Communication Schemes

Secure group communications are a mechanism facilitating protected trans...

0 Shouhuai Xu, et al. ∙

research

∙ 10/09/2020

Cybersecurity Dynamics: A Foundation for the Science of Cybersecurity

Cybersecurity Dynamics is new concept that aims to achieve the modeling,...

0 Shouhuai Xu, et al. ∙

research

∙ 07/09/2020

Human Cognition through the Lens of Social Engineering Cyberattacks

Social engineering cyberattacks are a major threat because they often pr...

0 Rosana Montanez Rodriguez, et al. ∙

research

∙ 07/06/2020

Computational Complexity Characterization of Protecting Elections from Bribery

The bribery problem in election has received considerable attention in t...

0 Lin Chen, et al. ∙

research

∙ 05/24/2020

SoK: Arms Race in Adversarial Malware Detection

Malicious software (malware) is a major cyber threat that shall be tackl...

0 Deqiang Li, et al. ∙

research

∙ 04/15/2020

Enhancing Deep Neural Networks Against Adversarial Malware Examples

Machine learning based malware detection is known to be vulnerable to ad...

0 Deqiang Li, et al. ∙

research

∙ 01/22/2020

Preventive and Reactive Cyber Defense Dynamics with Ergodic Time-dependent Parameters Is Globally Attractive

Cybersecurity dynamics is a mathematical approach to modeling and analyz...

0 Yujuan Han, et al. ∙

research

∙ 01/08/2020

VulDeeLocator: A Deep Learning-based Fine-grained Vulnerability Detector

Automatically detecting software vulnerabilities is an important problem...

0 Zhen Li, et al. ∙

research

∙ 01/08/2020

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

Fine-grained software vulnerability detection is an important and challe...

0 Deqing Zou, et al. ∙

research

∙ 10/05/2019

A Case Study on Using Deep Learning for Network Intrusion Detection

Deep Learning has been very successful in many application domains. Howe...

0 Gabriel C. Fernandez, et al. ∙

research

∙ 09/18/2019

Analyzing Root Causes of Intrusion Detection False-Negatives: Methodology and Case Study

Intrusion Detection Systems (IDSs) are a necessary cyber defense mechani...

0 Eric Ficke, et al. ∙

research

∙ 08/13/2019

A Survey on Ethereum Systems Security: Vulnerabilities, Attacks and Defenses

The blockchain technology is believed by many to be a game changer in ma...

0 Huashan Chen, et al. ∙

research

∙ 06/12/2019

Metrics Towards Measuring Cyber Agility

In cyberspace, evolutionary strategies are commonly used by both attacke...

0 Jose David Mireles, et al. ∙

research

∙ 12/19/2018

Enhancing Robustness of Deep Neural Networks Against Adversarial Malware Samples: Principles, Framework, and AICS'2019 Challenge

Malware continues to be a major cyber threat, despite the tremendous eff...

0 Deqiang Li, et al. ∙

research

∙ 11/27/2018

Node Diversification in Complex Networks by Decentralized Coloring

We develop a decentralized coloring approach to diversify the nodes in a...

0 Richard Garcia-Lebron, et al. ∙

research

∙ 11/12/2018

Efficient Public Blockchain Client for Lightweight Users

Public blockchains provide a decentralized method for storing transactio...

0 Lei Xu, et al. ∙

research

∙ 11/07/2018

Election with Bribed Voter Uncertainty: Hardness and Approximation Algorithm

Bribery in election (or computational social choice in general) is an im...

0 Lin Chen, et al. ∙

research

∙ 09/24/2018

Statistical Estimation of Malware Detection Metrics in the Absence of Ground Truth

The accurate measurement of security metrics is a critical research prob...

0 Pang Du, et al. ∙

research

∙ 09/18/2018

HashTran-DNN: A Framework for Enhancing Robustness of Deep Neural Networks against Adversarial Malware Samples

Adversarial machine learning in the context of image processing and rela...

6 Deqiang Li, et al. ∙

research

∙ 07/18/2018

SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities

The detection of software vulnerabilities (or vulnerabilities for short)...

0 Zhen Li, et al. ∙

research

∙ 01/05/2018

VulDeePecker: A Deep Learning-Based System for Vulnerability Detection

The automatic detection of software vulnerabilities is an important rese...

0 Zhen Li, et al. ∙

research

∙ 08/08/2014

An Evasion and Counter-Evasion Study in Malicious Websites Detection

Malicious websites are a major cyber attack vector, and effective detect...

0 Li Xu, et al. ∙

Shouhuai Xu

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