World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
64
Citations
12967
World Ranking
2650
National Ranking
1314

Research.com Recognitions

  • 2012 - ACM Distinguished Member
  • 2011 - ACM Senior Member

Overview

Latifur Khan is affiliated with The University of Texas at Dallas in the United States. Their research primarily falls within the field of Computer Science, with a focus on several subfields including Artificial Intelligence, Information Systems, Signal Processing, Computer Networks and Communications, and Sociology and Political Science.

The main topics of Latifur Khan's work include:

  • Advanced Malware Detection Techniques
  • Network Security and Intrusion Detection
  • Information and Cyber Security
  • Domain Adaptation and Few-Shot Learning
  • Topic Modeling
  • Anomaly Detection Techniques and Applications
  • Data Stream Mining Techniques

The scientist has contributed to numerous papers, some of the recent publications include:

  • "VSCL: Automating Vulnerability Detection in Smart Contracts with Deep Learning," 2021, published in the 2021 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)
  • "SACCOS: A Semi-Supervised Framework for Emerging Class Detection and Concept Drift Adaption Over Data Streams," 2020, IEEE Transactions on Knowledge and Data Engineering
  • "Deep Learning on Knowledge Graph for Recommender System: A Survey," 2020, arXiv (Cornell University)
  • "ConfliBERT: A Pre-trained Language Model for Political Conflict and Violence," 2022, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • "Community perceptions of landslide risk and susceptibility: a multi-country study," 2023, Landslides

The scientist frequently publishes in venues such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Dependable and Secure Computing
  • IEEE Access
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Journal of Computer Security

Latifur Khan has collaborated extensively with several researchers, including:

  • Bhavani Thuraisingham
  • Kevin W. Hamlen
  • Anoop Singhal
  • Feng Mi
  • Yang Gao

In addition to journal and conference papers, Latifur Khan has contributed to book publications, including a title with Springer Science+Business Media: "Data and Applications Security and Privacy XXXVI" published in 2022.

Recognition for Latifur Khan's work includes honors such as the ACM Senior Member designation in 2011 and ACM Distinguished Member in 2012.

Best Publications

  • A new intrusion detection system using support vector machines and hierarchical clustering

    Latifur Khan;Mamoun Awad;Bhavani Thuraisingham

  • Classification and Novel Class Detection in Concept-Drifting Data Streams under Time Constraints

    Mohammad M Masud;Jing Gao;L Khan;Jiawei Han

  • A Machine Learning Approach to Android Malware Detection

    Justin Sahs;Latifur Khan

  • Image annotations by combining multiple evidence & wordNet

    Yohan Jin;Latifur Khan;Lei Wang;Mamoun Awad

  • Security Issues for Cloud Computing

    Kevin Hamlen;Murat Kantarcioglu;Latifur Khan;Bhavani Thuraisingham

  • Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory

    Feng Luo;Feng Luo;Yunfeng Yang;Jianxin Zhong;Jianxin Zhong;Haichun Gao;Haichun Gao

  • FUSION: An Online Method for Multistream Classification

    Ahsanul Haque;Zhuoyi Wang;Swarup Chandra;Bo Dong

  • Heuristics-Based Query Processing for Large RDF Graphs Using Cloud Computing

    M. Husain;J. McGlothlin;M. M. Masud;L. Khan

  • Ontology construction for information selection

    L. Khan;Feng Luo

  • Retrieval effectiveness of an ontology-based model for information selection

    Latifur Khan;Dennis McLeod;Eduard Hovy

  • SMV-HUNTER: Large Scale, Automated Detection of SSL/TLS Man-in-the-Middle Vulnerabilities in Android Apps

    David Sounthiraraj;Justin Sahs;Garrett Greenwood;Zhiqiang Lin

  • A Practical Approach to Classify Evolving Data Streams: Training with Limited Amount of Labeled Data

    M.M. Masud;Jing Gao;L. Khan;Jiawei Han

  • Estimating Twitter User Location Using Social Interactions--A Content Based Approach

    Swarup Chandra;Latifur Khan;Fahad Bin Muhaya

  • SAND: semi-supervised adaptive novel class detection and classification over data stream

    Ahsanul Haque;Latifur Khan;Michael Baron

  • Storage and Retrieval of Large RDF Graph Using Hadoop and MapReduce

    Mohammad Farhan Husain;Pankil Doshi;Latifur Khan;Bhavani Thuraisingham

  • Secure knowledge management: confidentiality, trust, and privacy

    E. Bertino;L.R. Khan;R. Sandhu;B. Thuraisingham

  • Decentralized IoT Data Management Using BlockChain and Trusted Execution Environment

    Gbadebo Ayoade;Vishal Karande;Latifur Khan;Kevin Hamlen

  • Facing the reality of data stream classification: coping with scarcity of labeled data

    Mohammad M. Masud;Clay Woolam;Jing Gao;Latifur Khan

  • Classification and Adaptive Novel Class Detection of Feature-Evolving Data Streams

    M. M. Masud;Qing Chen;L. Khan;C. C. Aggarwal

  • Support Vector Machines

    Mamoun Awad;Latifur Khan

  • Classification and Novel Class Detection in Concept-Drifting Data Streams

    Bhavani Thuraisingham;Mohammad Mehedy Masud;Pallabi Parveen;Latifur Khan

Frequent Co-Authors

Bhavani Thuraisingham
Bhavani Thuraisingham The University of Texas at Dallas
Murat Kantarcioglu
Murat Kantarcioglu The University of Texas at Dallas
Jiawei Han
Jiawei Han University of Illinois at Urbana-Champaign
Charu C. Aggarwal
Charu C. Aggarwal IBM (United States)
Jing Gao
Jing Gao Purdue University West Lafayette
Ehab Al-Shaer
Ehab Al-Shaer Carnegie Mellon University
Zhiqiang Lin
Zhiqiang Lin The Ohio State University
Shashi Shekhar
Shashi Shekhar University of Minnesota
Cyrus Shahabi
Cyrus Shahabi University of Southern California
Elisa Bertino
Elisa Bertino Purdue University West Lafayette

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