Published in ACM WISEC, 2017
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Citation: RhongHo Jang, Jeonil Kang, Aziz Mohaisen, DaeHun Nyang, "Highly-accurate rogue access point detection using intentional channel interference: poster." ACM WISEC, 2017.
Published in IEEE INFOCOM, 2017
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Citation: RhongHo Jang, DongGyu Cho, Youngtae Noh, DaeHun Nyang, "RFlow(^mbox+): An SDN-based WLAN monitoring and management framework." IEEE INFOCOM, 2017.
Published in IEEE ICDCS, 2017
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Citation: RhongHo Jang, Jeonil Kang, Aziz Mohaisen, DaeHun Nyang, "Rogue Access Point Detector Using Characteristics of Channel Overlapping in 802.11n." IEEE Computer Society ICDCS, 2017.
Published in ACM WISEC, 2017
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Citation: RhongHo Jang, DongGyu Cho, Aziz Mohaisen, Youngtae Noh, DaeHun Nyang, "Two-level network monitoring and management in WLAN using software-defined networking: poster." ACM WISEC, 2017.
Published in ACM WiSec, 2019
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Citation: Rhongho Jang, Seongkwang Moon, Youngtae Noh, Aziz Mohaisen, DaeHun Nyang, "A cost-effective anomaly detection system using in-DRAM working set of active flows table: poster." ACM WiSec, 2019.
Published in IEEE ICDCS, 2019
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Citation: Rhongho Jang, Seongkwang Moon, Youngtae Noh, Aziz Mohaisen, DaeHun Nyang, "InstaMeasure: Instant Per-flow Detection Using Large In-DRAM Working Set of Active Flows." IEEE ICDCS, 2019.
Published in IEEE Trans. Mob. Comput., 2020
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Citation: Rhongho Jang, Jeonil Kang, Aziz Mohaisen, DaeHun Nyang, "Catch Me If You Can: Rogue Access Point Detection Using Intentional Channel Interference." IEEE Trans. Mob. Comput., 2020.
Published in IEEE INFOCOM, 2020
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Citation: Ahmed Abusnaina, Rhongho Jang, Aminollah Khormali, DaeHun Nyang, David Mohaisen, "DFD: Adversarial Learning-based Approach to Defend Against Website Fingerprinting." IEEE INFOCOM, 2020.
Published in IEEE INFOCOM, 2020
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Citation: Rhongho Jang, DaeHong Min, Seongkwang Moon, David Mohaisen, DaeHun Nyang, "SketchFlow: Per-Flow Systematic Sampling Using Sketch Saturation Event." IEEE INFOCOM, 2020.
Published in IEEE ICDCS, 2020
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Citation: Hisham Alasmary, Ahmed Abusnaina, Rhongho Jang, Mohammed Abuhamad, Afsah Anwar, DaeHun Nyang, David Mohaisen, "Soteria: Detecting Adversarial Examples in Control Flow Graph-based Malware Classifiers." IEEE ICDCS, 2020.
Published in Comput. Secur., 2021
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Citation: Changhun Jung, Jinchun Choi, Rhongho Jang, David Mohaisen, DaeHun Nyang, "A network-independent tool-based usable authentication system for Internet of Things devices." Comput. Secur., 2021.
Published in IEEE DSN (Supplements), 2021
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Citation: Ahmed Abusnaina, Afsah Anwar, Sultan Alshamrani, Abdulrahman Alabduljabbar, Rhongho Jang, DaeHun Nyang, David Mohaisen, "Systemically Evaluating the Robustness of ML-based IoT Malware Detectors." IEEE DSN (Supplements), 2021.
Published in IEEE/ACM Trans. Netw., 2022
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Citation: Jeman Park, Rhongho Jang, Manar Mohaisen, David Mohaisen, "A Large-Scale Behavioral Analysis of the Open DNS Resolvers on the Internet." IEEE/ACM Trans. Netw., 2022.
Published in IEEE Trans. Mob. Comput., 2022
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Citation: Rhongho Jang, Changhun Jung, David Mohaisen, KyungHee Lee, DaeHun Nyang, "A One-Page Text Entry Method Optimized for Rectangle Smartwatches." IEEE Trans. Mob. Comput., 2022.
Published in ACM CCS, 2022
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Citation: Changhun Jung, Sian Kim, Rhongho Jang, David Mohaisen, DaeHun Nyang, "A Scalable and Dynamic ACL System for In-Network Defense." ACM CCS, 2022.
Published in NeurIPS, 2022
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Citation: Yao Qiang, Deng Pan, Chengyin Li, Xin Li, Rhongho Jang, Dongxiao Zhu, "AttCAT: Explaining Transformers via Attentive Class Activation Tokens." In the proceedings of NeurIPS, 2022.
Published in IEEE Trans. Dependable Secur. Comput., 2022
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Citation: Ahmed Abusnaina, Mohammed Abuhamad, Hisham Alasmary, Afsah Anwar, Rhongho Jang, Saeed Salem, DaeHun Nyang, David Mohaisen, "DL-FHMC: Deep Learning-Based Fine-Grained Hierarchical Learning Approach for Robust Malware Classification." IEEE Trans. Dependable Secur. Comput., 2022.
Published in IEEE DSN, 2022
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Citation: Dinhnguyen Dao, Rhongho Jang, Changhun Jung, David Mohaisen, DaeHun Nyang, "Minimizing Noise in HyperLogLog-Based Spread Estimation of Multiple Flows." IEEE DSN, 2022.
Published in ACM RAID, 2022
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Citation: Ahmed Abusnaina, Afsah Anwar, Sultan Alshamrani, Abdulrahman Alabduljabbar, RhongHo Jang, DaeHun Nyang, David Mohaisen, "Systematically Evaluating the Robustness of ML-based IoT Malware Detection Systems." ACM RAID, 2022.
Published in ACM CySSS@AsiaCCS, 2022
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Citation: Abdulrahman Alabduljabbar, Runyu Ma, Soohyeon Choi, Rhongho Jang, Songqing Chen, David Mohaisen, "Understanding the Security of Free Content Websites by Analyzing their SSL Certificates: A Comparative Study." ACM CySSS@AsiaCCS, 2022.
Published in IEEE ICCCN, 2023
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Citation: Mohammed Alkinoon, Abdulrahman Alabduljabbar, Hattan Althebeiti, Rhongho Jang, DaeHun Nyang, David Mohaisen, "Understanding the Security and Performance of the Web Presence of Hospitals: A Measurement Study." IEEE ICCCN, 2023.
Published in Springer CSoNet, 2023
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Citation: Soohyeon Choi, Rhongho Jang, DaeHun Nyang, David Mohaisen, "Untargeted Code Authorship Evasion with Seq2Seq Transformation." Springer CSoNet, 2023.
Published in ISOC NDSS, 2023
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Citation: Sian Kim, Changhun Jung, RhongHo Jang, David Mohaisen, DaeHun Nyang, "A Robust Counting Sketch for Data Plane Intrusion Detection." The Internet Society NDSS, 2023.
Published in USENIX Security, 2024
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Published in WISE, 2024
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Published in ISOC NDSS, 2025
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Every Fall, Department of Computer Science, Wayne State University, Last Update, 2024
This course will explore board security topics in the areas of network and operating systems. In particular, this course focus on providing hands-on experience leveraging various security tools, aiming to help students understand real-world security threats. It will cover both offensive and defensive methods in a laboratory environment. Students are expected to finish lab assignments using real-world exploits and defense tools.
Every Winter, Department of Computer Science, Wayne State University, Last Update, 2024
The next-generation hybrid cloud platform is integrated with Network Functions (NFs) across diverse network environments, ushering in a new computing paradigm known as in-network computing (INC). This introductory course on INC offers system and network engineers the opportunity to engage in large-scale system optimization. Participants will learn practical data plane programming skills, gain hands-on experience in hardware programming using software techniques, and explore real-world applications through case studies in data centers, distributed AI/ML systems, security, and more.
Every Winter, Department of Computer Science, Wayne State University, Last Update, 2024
Both basic distributed computing ideas and system designs that support distributed applications will be covered in this course. The following learning outcomes are part of the course: a thorough understanding of the fundamentals of distributed computing, construction of distributed system components, and comprehension of the current state of the art in various areas of distributed systems. This includes studying abstract concepts and practical methods for creating system support for distributed applications.