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Dr Leslie Sikos

Lecturer

Staff Member Details
Telephone: +61 8 6304 5189
Email: l.sikos@ecu.edu.au
Campus: Joondalup  
Room: JO18.418C  
ORCID iD: https://orcid.org/0000-0003-3368-2215

Leslie is a lecturer in computing and security in the School of Science, and a researcher at the Institute for Securing Digital Futures and at CyberCRC.

Current Teaching

  • CSI3351 Cybersecurity Incident Detection and Response
  • CSG2305 Computer Forensics

Background

Leslie F Sikos, PhD, SMIEEE, MACS CP, is a computer scientist specialising in network forensics and cybersecurity applications powered by artificial intelligence and data science. He has worked both in academia and the industry, and has 20+ industry certificates; he is a ThreatConnect Analyst and an AccessData Certified Investigator, holds the Splunk User Behavior Analytics and the Autopsy Basics and Hands-On Certificates, and completed the OSForensics Triage Certification. He is an active member of the research community as an author, editor, reviewer, conference organiser, and speaker. His community engagement includes public talks, media appearances on ABC News, and articles in professional magazines. He is a reviewer at flagship journals in cybersecurity, such as Computers & Security, Crime Science, and IEEE Transactions on Dependable and Secure Computing. He is a volume editor of Springer’s Advanced Information & Knowledge Processing and Intelligent Systems Reference Library book series. As an invited expert, he reviews book proposals in computer science for Springer. Dr Sikos published more than 20 books; his most influential books are AI in Cybersecurity and Data Science in Cybersecurity and Cyberthreat Intelligence.

Professional Memberships

  • Since 2017 - Association for Computing Machinery, ACM (Member)
  • Since 2017 - Institute of Electrical and Electronics Engineers, IEEE (Member; since 2020, Senior Member)
    • IEEE Computer Society’s Technical Committee on Security and Privacy (Member)
    • IEEE Special Interest Group on Big Data for Cyber Security and Privacy (Founding member)
  • Since 2019 - Australian Computer Society, ACS (member; since 2020, certified professional member)
  • Since 2020 – Australian Information Security Association, AISA (Member)

Research Areas and Interests

  • Cybersecurity
  • Data Science
  • Artificial Intelligence
  • Digital Forensics

Qualifications

  • Doctor of Philosophy, The Flinders University of South Australia, 2018.

Research

Recent Research Grants

  • In-Circuit Forensic Analysis of IoT Memory Modules,  Cyber Security Research Centre Ltd,  Cyber Security Research Centre PhD Scholarship,  2020 - 2023,  $180,000.
  • Honeypot Deployment Architecture,  Cyber Security Research Centre Ltd,  Cyber Security Research Centre Ltd,  2019 - 2021,  $130,000.

Recent Publications (within the last five years)

Books

  • Sikos, L., (2017), Description Logics in Multimedia Reasoning., Cham, Switzerland, Springer, DOI: 10.1007/978-3-319-54066-5.

Book Chapters

  • Sikos, L., (2020), The Formal Representation of Cyberthreats for Automated Reasoning. Data Science in Cybersecurity and Cyberthreat Intelligence, 1-12, Cham, Switzerland, Springer, DOI: https://doi.org/10.1007/978-3-030-38788-4_1.
  • Flotyński, J., Malamos, AG., Brutzman, D., Hamza-Lup, FG., Polys, NF., Sikos, L., Walczak, K., (2020), Recent Advances in Web3D Semantic Modeling. Recent Advances in 3D Imaging, Modeling, and Reconstruction, 23–49, Hershey, United States of America, IGI Global , DOI: 10.4018/978-1-5225-5294-9.ch002.
  • Sikos, L., Philp, D., Howard, C., Voigt, S., Stumptner, M., Mayer, W., (2019), Knowledge Representation of Network Semantics for Reasoning-Powered Cyber-Situational Awareness. AI in Cybersecurity,  Cham, Switzerland, Springer, DOI: 10.1007/978-3-319-98842-9_2.
  • Sikos, L., (2018), Ontology-Based Structured Video Annotation for Content-Based Video Retrieval via Spatiotemporal Reasoning. Bridging the Semantic Gap in Image and Video Analysis, 97–122, Cham, Switzerland, Springer, DOI: 10.1007/978-3-319-73891-8_6.

Journal Articles

  • Sikos, L., Philp, D., (2020), Provenance-Aware Knowledge Representation: A Survey of Data Models and Contextualized Knowledge Graphs. Data Science and Engineering, 5(3), 293-316, DOI: 10.1007/s41019-020-00118-0.
  • Rashid, B., Ahmed, M., Sikos, L., Haskell-Dowland, P., (2020), A Novel Penalty-Based Wrapper Objective Function for Feature Selection in Big Data using Cooperative Co-Evolution. IEEE Access, 8(2020), 150113-150129, DOI: 10.1109/ACCESS.2020.3016679.
  • Sadik, S., Ahmed, M., Sikos, L., Islam, AN., (2020), Toward a Sustainable Cybersecurity Ecosystem. Computers, 9(3), 1-17, DOI: 10.3390/computers9030074.
  • Sikos, L., (2020), Packet Analysis for Network Forensics: A Comprehensive Survey. Forensic Science International: Digital Investigation, 32(March 2020), article number 200892, DOI: 10.1016/j.fsidi.2019.200892.
  • Rashid, B., Ahmed, M., Sikos, L., Haskell-Dowland, P., (2020), Cooperative co-evolution for feature selection in Big Data with random feature grouping. Journal of Big Data, 7(1), Article number 107, DOI: 10.1186/s40537-020-00381-y.
  • Sikos, L., (2020), AI in Digital Forensics: Ontology Engineering for Cybercrime Investigations. WIREs Forensic Science, 2020(article in press), Article number e1394, DOI: 10.1002/wfs2.1394.
  • Sikos, L., (2018), VidOnt: a Core Reference Ontology for Reasoning over Video Scenes. Journal of Information and Telecommunication, 2(2), 192–204, UK, DOI: 10.1080/24751839.2018.1437696.
  • Sikos, L., (2017), A Novel Ontology for 3D Semantics: Ontology-Based 3D Model Indexing and Content-Based Video Retrieval Applied to the Medical Domain. International Journal of Metadata Semantics and Ontologies, 12(1), 59–70, DOI: 10.1504/IJMSO.2017.087702.
  • Sikos, L., (2016), RDF-Powered Semantic Video Annotation Tools with Concept Mapping to Linked Data for Next-Generation Video Indexing: A Comprehensive Review. Multimedia Tools and Applications, 76(12), 14437–14460, DOI: 10.1007/s11042-016-3705-7.

Conference Publications

  • Yang, W., Johnstone, M., Sikos, L., Wang, S., (2020), Security and Forensics in the Internet of Things: Research Advances and Challenges. Proceedings - 2020 Workshop on Emerging Technologies for Security in IoT, ETSecIoT 2020, 12-17, Piscataway, USA , Institute of Electrical and Electronics Engineers, Inc., DOI: 10.1109/ETSecIoT50046.2020.00007.
  • Sikos, L., (2019), Knowledge Representation to Support Partially Automated Honeypot Analysis Based on Wireshark Packet Capture Files. Intelligent Decision Technologies 2019: Proceedings of the 11th KES International Conference on Intelligent Decision Technologies (KES-IDT 2019), 345–351, Singapore, Springer, DOI: 10.1007/978-981-13-8311-3_30.
  • Philp, D., Chan, N., Sikos, L., (2019), Decision Support for Network Path Estimation via Automated Reasoning. Intelligent Decision Technologies 2019: Proceedings of the 11th KES International Conference on Intelligent Decision Technologies (KES-IDT 2019), 335–344, Singapore, Springer, DOI: 10.1007/978-981-13-8311-3_29.
  • Cabral, WZ., Valli, C., Sikos, L., Wakeling, S., (2019), Review and Analysis of Cowrie Artefacts and their Potential to be Used Deceptively. Proceedings of 6th Annual Conference on Computational Science & Computational Intelligence, 166-171, Piscataway, USA, Institute of Electrical and Electronics Engineers, Inc., DOI: 10.1109/CSCI49370.2019.00035.
  • Flotyński, J., Brutzman, D., Hamza-Lup, FG., Malamos, A., Polys, N., Sikos, L., Walczak, K., (2019), The Semantic Web3D: Towards Comprehensive Representation of 3D Content on the Semantic Web. 2019 International Conference on 3D Immersion (IC3D) Proceedings, 1-9, Piscataway, USA, IEEE, DOI: 10.1109/IC3D48390.2019.8975906.
  • Sikos, L., (2018), Handling Uncertainty and Vagueness in Network Knowledge Representation for Cyberthreat Intelligence. Proceedings of the 2018 IEEE International Conference on Fuzzy Systems, 6 p., Piscataway, NJ, USA, IEEE, DOI: 10.1109/FUZZ-IEEE.2018.8491686.
  • Sikos, L., Stumptner, M., Mayer, W., Howard, C., Voigt, S., Philp, D., (2018), Automated Reasoning over Provenance-Aware Communication Network Knowledge in Support of Cyber-Situational Awareness. Knowledge Science, Engineering and Management 11th International Conference, KSEM 2018 Changchun, China, August 17–19, 2018 Proceedings, Part II, 132–143, Cham, Switzerland, Springer, DOI: 10.1007/978-3-319-99247-1_12.
  • Sikos, L., Philp, D., Voigt, S., Howard, C., Stumptner, M., Mayer, W., (2018), Provenance-Aware LOD Datasets for Detecting Network Inconsistencies. Joint Proceedings of the International Workshops on Contextualized Knowledge Graphs, and Semantic Statistics co-located with the 17th International Semantic Web Conference, Article 3, Aachen, RWTH.
  • Sikos, L., Stumptner, M., Mayer, W., Howard, C., Voigt, S., Philp, D., (2018), Representing Network Knowledge Using Provenance-Aware Formalisms for Cyber-Situational Awareness. Procedia Computer Science, 126(3-5 September 2018), 29–38, Amsterdam, Science Direct, DOI: 10.1016/j.procs.2018.07.206.
  • Sikos, L., (2017), Utilizing Multimedia Ontologies in Video Scene Interpretation via Information Fusion and Automated Reasoning. 2017 Federated Conference on Computer Science and Information Systems, 91–98, New York, IEEE, DOI: 10.15439/2017F66.
  • Sikos, L., (2017), 3D Model Indexing in Videos for Content-Based Retrieval via X3D-Based Semantic Enrichment and Automated Reasoning. 22nd International Conference on 3D Web Technology, Article No. a19, New York, ACM, DOI: 10.1145/3055624.3075943.
  • Sikos, L., (2017), Spatiotemporal Reasoning for Complex Video Event Recognition in Content-Based Video Retrieval. Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2017, 704–713, Cham, Switzerland, Springer, DOI: 10.1007/978-3-319-64861-3_66.
  • Sikos, L., (2016), Rich Semantics for Interactive 3D Models of Cultural Artifacts. Metadata and Semantics Research, 169–180, Cham, Switzerland, Springer, DOI: 10.1007/978-3-319-49157-8_14.
  • Sikos, L., (2016), A Novel Approach to Multimedia Ontology Engineering for Automated Reasoning over Audiovisual LOD Datasets. Intelligent Information and Database Systems, 3–12, Heidelberg, Germany, Springer, DOI: 10.1007/978-3-662-49381-6_1.
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