World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
8858
World Ranking
7907
National Ranking
250

Overview

Jun Zhang is affiliated with the Swinburne University of Technology in Australia and has contributed extensively to the field of computer science, with a primary focus on cybersecurity, artificial intelligence, and network security.

Their research spans multiple subfields of computer science, including:

  • Artificial Intelligence
  • Information Systems
  • Computer Networks and Communications
  • Signal Processing
  • Computer Vision and Pattern Recognition

Jun Zhang's work concentrates on topics such as:

  • Advanced Malware Detection Techniques
  • Network Security and Intrusion Detection
  • Software Engineering Research
  • Internet Traffic Analysis and Secure E-voting
  • Spam and Phishing Detection
  • Privacy-Preserving Technologies in Data
  • Security and Verification in Computing

Frequent co-authors in Jun Zhang's publications include:

  • Yang Xiang (23 collaborations)
  • Chao Chen (12 collaborations)
  • Lei Pan (11 collaborations)
  • Leo Yu Zhang (10 collaborations)
  • Shigang Liu (7 collaborations)

Jun Zhang has published numerous papers in well-known academic venues. The most common publication venues include:

  • arXiv (Cornell University) - 9 publications
  • ACM Computing Surveys - 4 publications
  • IEEE Transactions on Dependable and Secure Computing - 4 publications
  • Computers & Security - 3 publications
  • Neural Computing and Applications - 2 publications

Notable recent papers authored by or including Jun Zhang are:

  • "Deep Learning Based Attack Detection for Cyber-Physical System Cybersecurity: A Survey", 2021, IEEE/CAA Journal of Automatica Sinica
  • "Software Vulnerability Detection Using Deep Neural Networks: A Survey", 2020, Proceedings of the IEEE
  • "Security and privacy in 6G networks: New areas and new challenges", 2020, Digital Communications and Networks
  • "A Survey of Android Malware Detection with Deep Neural Models", 2020, ACM Computing Surveys
  • "Cyber Threat Intelligence Mining for Proactive Cybersecurity Defense: A Survey and New Perspectives", 2023, IEEE Communications Surveys & Tutorials

Jun Zhang's expertise lies primarily within computer science, with 145 publications contributing to this broad field. Their work integrates areas of advanced malware detection, network intrusion detection, privacy-preserving methods, and secure communication technologies.

Best Publications

  • Hybrid threshold adaptable quantum secret sharing scheme with reverse Huffman-Fibonacci-tree coding

    Hong Lai;Jun Zhang;Ming Xing Luo;Lei Pan

  • Network Traffic Classification Using Correlation Information

    Jun Zhang;Yang Xiang;Yu Wang;Wanlei Zhou

  • Robust network traffic classification

    Jun Zhang;Xiao Chen;Yang Xiang;Wanlei Zhou

  • Software Vulnerability Detection Using Deep Neural Networks: A Survey

    Guanjun Lin;Sheng Wen;Qing-Long Han;Jun Zhang

  • Detecting and Preventing Cyber Insider Threats: A Survey

    Liu Liu;Olivier De Vel;Qing-Long Han;Jun Zhang

  • Deep Learning Based Attack Detection for Cyber-Physical System Cybersecurity: A Survey

    Jun Zhang;Lei Pan;Qing-Long Han;Chao Chen

  • Security and privacy in 6G networks: New areas and new challenges

    Minghao Wang;Tianqing Zhu;Tao Zhang;Jun Zhang

  • Data-Driven Cybersecurity Incident Prediction: A Survey

    Nan Sun;Jun Zhang;Paul Rimba;Shang Gao

  • Android HIV: A Study of Repackaging Malware for Evading Machine-Learning Detection

    Xiao Chen;Chaoran Li;Derui Wang;Sheng Wen

  • A Survey of Android Malware Detection with Deep Neural Models

    Junyang Qiu;Jun Zhang;Wei Luo;Lei Pan

  • Internet Traffic Classification by Aggregating Correlated Naive Bayes Predictions

    Jun Zhang;Chao Chen;Yang Xiang;Wanlei Zhou

  • Cross-Project Transfer Representation Learning for Vulnerable Function Discovery

    Guanjun Lin;Jun Zhang;Wei Luo;Lei Pan

  • Twitter spam detection based on deep learning

    Tingmin Wu;Shigang Liu;Jun Zhang;Yang Xiang

  • Statistical Features-Based Real-Time Detection of Drifted Twitter Spam

    Chao Chen;Yu Wang;Jun Zhang;Yang Xiang

  • 6 million spam tweets: A large ground truth for timely Twitter spam detection

    Chao Chen;Jun Zhang;Xiao Chen;Yang Xiang

  • An Effective Network Traffic Classification Method with Unknown Flow Detection

    Jun Zhang;Chao Chen;Yang Xiang;Wanlei Zhou

  • A Performance Evaluation of Machine Learning-Based Streaming Spam Tweets Detection

    Chao Chen;Jun Zhang;Yi Xie;Yang Xiang

  • Addressing the class imbalance problem in Twitter spam detection using ensemble learning

    Shigang Liu;Yu Wang;Jun Zhang;Chao Chen

  • Modeling Propagation Dynamics of Social Network Worms

    Sheng Wen;Wei Zhou;Jun Zhang;Yang Xiang

  • Internet Traffic Classification Using Constrained Clustering

    Yu Wang;Yang Xiang;Jun Zhang;Wanlei Zhou

Frequent Co-Authors

Yang Xiang
Yang Xiang Swinburne University of Technology
Wanlei Zhou
Wanlei Zhou City University of Macau
Josef Pieprzyk
Josef Pieprzyk Commonwealth Scientific and Industrial Research Organisation
Mehmet A. Orgun
Mehmet A. Orgun Macquarie University
Qing-Long Han
Qing-Long Han Swinburne University of Technology
Surya Nepal
Surya Nepal Commonwealth Scientific and Industrial Research Organisation
Mohammad Mehedi Hassan
Mohammad Mehedi Hassan King Saud University
Yong Xiang
Yong Xiang Deakin University
Chin-Chen Chang
Chin-Chen Chang Feng Chia University
Abdulhameed Alelaiwi
Abdulhameed Alelaiwi King Saud University

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