activity
20182021
most citedA Survey on Centrality Metrics and Their Implications in Network Resilience

119 citations · 326 across the 21 of their papers we have counts for

collaborators

21 papers

cs.CR2021

Quantifying Cybersecurity Effectiveness of Software Diversity

Huashan Chen, Richard B. Garcia-Lebron, Zheyuan Sun +2

The deployment of monoculture software stacks can cause a devastating damage even by a single exploit against a single vulnerability. Inspired by the resilience benefit of biologic…

cs.GT2021★ 2 cited

Foureye: Defensive Deception based on Hypergame Theory Against Advanced Persistent Threats

Zelin Wan, Jin-Hee Cho, Mu Zhu +3

Defensive deception techniques have emerged as a promising proactive defense mechanism to mislead an attacker and thereby achieve attack failure. However, most game-theoretic defen…

cs.CR2021★ 13 cited

Game-Theoretic and Machine Learning-based Approaches for Defensive Deception: A Survey

Mu Zhu, Ahmed H. Anwar, Zelin Wan +3

Defensive deception is a promising approach for cyber defense. Via defensive deception, the defender can anticipate attacker actions; it can mislead or lure attacker, or hide real…

cs.LG2020

Multidimensional Uncertainty-Aware Evidential Neural Networks

Yibo Hu, Yuzhe Ou, Xujiang Zhao +2

Traditional deep neural networks (NNs) have significantly contributed to the state-of-the-art performance in the task of classification under various application domains. However,…

cs.SI2020★ 119 cited

A Survey on Centrality Metrics and Their Implications in Network Resilience

Zelin Wan, Yash Mahajan, Beom Woo Kang +2

Centrality metrics have been used in various networks, such as communication, social, biological, geographic, or contact networks. In particular, they have been used in order to st…

cs.LG2020★ 53 cited

Uncertainty Aware Semi-Supervised Learning on Graph Data

Xujiang Zhao, Feng Chen, Shu Hu +1

Thanks to graph neural networks (GNNs), semi-supervised node classification has shown the state-of-the-art performance in graph data. However, GNNs have not considered different ty…

cs.CR2020★ 3 cited

Diversity-By-Design for Dependable and Secure Cyber-Physical Systems: A Survey

Qisheng Zhang, Abdullah Zubair Mohammed, Zelin Wan +2

Diversity-based security approaches have been studied for several decades since the 1970's. The concept of diversity-by-design emerged in the 1980's and, since then, diversity-base…

cs.CR2020★ 1 cited

Vulnerability-Aware Resilient Networks: Software Diversity-based Network Adaptation

Qisheng Zhang, Jin-Hee Cho, Terrence J. Moore +1

By leveraging the principle of software polyculture to ensure security in a network, we proposed a vulnerability-based software diversity metric to determine how a network topology…

cs.CR2020★ 6 cited

Proactive Defense for Internet-of-Things: Integrating Moving Target Defense with Cyberdeception

Mengmeng Ge, Jin-Hee Cho, Dong Seong Kim +2

Resource constrained Internet-of-Things (IoT) devices are highly likely to be compromised by attackers because strong security protections may not be suitable to be deployed. This…

cs.CR2020★ 45 cited

Online Social Deception and Its Countermeasures for Trustworthy Cyberspace: A Survey

Zhen Guo, Jin-Hee Cho, Ing-Ray Chen +3

We are living in an era when online communication over social network services (SNSs) have become an indispensable part of people's everyday lives. As a consequence, online social…

cs.LG2019★ 13 cited

Quantifying Classification Uncertainty using Regularized Evidential Neural Networks

Xujiang Zhao, Yuzhe Ou, Lance Kaplan +2

Traditional deep neural nets (NNs) have shown the state-of-the-art performance in the task of classification in various applications. However, NNs have not considered any types of…

cs.LG2019

Deep Learning for Predicting Dynamic Uncertain Opinions in Network Data

Xujiang Zhao, Feng Chen, Jin-Hee Cho

Subjective Logic (SL) is one of well-known belief models that can explicitly deal with uncertain opinions and infer unknown opinions based on a rich set of operators of fusing mult…

cs.NI2019★ 17 cited

Toward Proactive, Adaptive Defense: A Survey on Moving Target Defense

Jin-Hee Cho, Dilli P. Sharma, Hooman Alavizadeh +6

Reactive defense mechanisms, such as intrusion detection systems, have made significant efforts to secure a system or network for the last several decades. However, the nature of r…

cs.CR2019★ 1 cited

Modeling and Analysis of Integrated Proactive Defense Mechanisms for Internet-of-Things

Mengmeng Ge, Jin-Hee Cho, Bilal Ishfaq +1

As a solution to protect and defend a system against inside attacks, many intrusion detection systems (IDSs) have been developed to identify and react to them for protecting a syst…

cs.CR2019

Optimal Deployments of Defense Mechanisms for the Internet of Things

Mengmeng Ge, Jin-Hee Cho, Charles A. Kamhoua +1

Internet of Things (IoT) devices can be exploited by the attackers as entry points to break into the IoT networks without early detection. Little work has taken hybrid approaches t…

cs.CR2019★ 41 cited

Metrics Towards Measuring Cyber Agility

Jose David Mireles, Eric Ficke, Jin-Hee Cho +2

In cyberspace, evolutionary strategies are commonly used by both attackers and defenders. For example, an attacker's strategy often changes over the course of time, as new vulnerab…

cs.CY2019

Rating Reliability and Bias in News Articles: Does AI Assistance Help Everyone?

Benjamin D. Horne, Dorit Nevo, John O'Donovan +2

With the spread of false and misleading information in current news, many algorithmic tools have been introduced with the aim of assessing bias and reliability in written content.…

stat.AP2018★ 1 cited

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

Pang Du, Zheyuan Sun, Huashan Chen +2

The accurate measurement of security metrics is a critical research problem because an improper or inaccurate measurement process can ruin the usefulness of the metrics, no matter…

cs.NI2018★ 2 cited

FRVM: Flexible Random Virtual IP Multiplexing in Software-Defined Networks

Dilli P. Sharma, Dong Seong Kim, Seunghyun Yoon +3

Network address shuffling is one of moving target defense (MTD) techniques that can invalidate the address information attackers have collected based on the current network IP conf…

cs.SI2018

Is Uncertainty Always Bad?: Effect of Topic Competence on Uncertain Opinions

Jin-Hee Cho, Sibel Adalı

The proliferation of information disseminated by public/social media has made decision-making highly challenging due to the wide availability of noisy, uncertain, or unverified inf…

cs.CR2018★ 9 cited

Intrusion Detection Systems for Networked Unmanned Aerial Vehicles: A Survey

Gaurav Choudhary, Vishal Sharma, Ilsun You +3

Unmanned Aerial Vehicles (UAV)-based civilian or military applications become more critical to serving civilian and/or military missions. The significantly increased attention on U…