Dr Sheng Wen
- Faculty of Science, Engineering & Technology
- School of Software and Electrical Engineering
- Department of Computer Science and Software Engineering
- EN511e Hawthorn campus
Sheng Wenreceived his PhD degree from Deakin University, Melbourne, in October 2014. Currently he has been working fill-time as a senior lecturer in Swinburne University of Technology. Before this, he first worked as a research fellow and then a Lecturer in Computer Science in the School of Information Technology in Deakin University from the year of 2015. Dr. Wen manages several research projects in the last three years. Since late 2014, Dr. Wen has received over 3 million Australia Dollars’ funding from both academia and industries. Dr. Wen is also leading a medium-size research team (around 15 members) in cybersecurity area. This team includes Dr. Wen, 6 PhD students in Swinburne as managing supervisors and 6 Honours students, plus one external senior researcher as collaborator (Dr. Mohammod S. Haghighi in University of Teheran). The team focuses on the research of social network analysis and system security. In the last six years, as an excellent early career researcher, Dr Sheng Wen has published more than 50 high-quality papers in the last six years, including 35 journal articles (25 ERA A/A* journal papers and 11 IEEE Transactions journal papers) and 18 conference articles (top conferences like IEEE ICDCS) in the fields of information security, epidemic modelling and source identification. His representative research outcomes have been mainly published on top journals, such as IEEE Transactions on Computers (TC), IEEE Transactions on Parallel and Distributed Systems (TPDS), IEEE Transactions on Dependable and Secure Computing (TDSC), IEEE Transactions on Information Security and Forensics (TIFS), and IEEE Communication Survey and Tutorials (CST). Dr. Wen has also been actively providing services to the research community. For example, he is on the editorial board of Journals: 1) Soft Computing (Springer, IF=2.472), 2) Ad Hoc & Sensor Wireless Networks (Elsevier, IF=0.487), 3) International Journal of Computer and Applications (Flayer, IF=0.22). He has been invited to be Chair Committee members for CSS 2017, SocialSec 2017, MONAMI 2017, WMNC 2015, CSS 2015, IEEE BigDataService 2015, and GPC 2015. He also served as PC member for a number of International Conferences, such as Trustcom 2014, NSS 2014, SmartComp 2014, Trustcom 2015, ACISP 2016, AICCSA 2015, CSS 2012, DependSys 2015, HPCC 2015, ICA3PP 2015, ICA3PP 2011, ISICA 2015, NSS 2015, SNAMS 2015, SocialSec 2015, SocialSec 2016, DependSys 2016, TrustCom 2016, IEEE ICC 2016, IEEE Globalcom 2016, etc.
IP Network Resilience and Security; Software Security
PhD candidate and honours supervision
Higher degrees by research
Accredited to supervise Masters & Doctoral students as Principal Supervisor.
Available to supervise honours students.
Fields of Research
- Computer System Security - 080303
- Distributed Computing - 080500
- Information Systems - 080600
IP Network Resilience and Security;Software Security
Also published as: Wen, Sheng; Wen, S.
This publication listing is provided by Swinburne Research Bank. If you are the owner of this profile, you can update your publications using our online form.
Recent research grants awarded
- 2019: Adversarial Deep Learning in Malware Detection *; DATA61
- 2019: Building Trust with Distributed Ledgers for Digital Platforms *; DATA61
- 2019: Detecting Firmware Vulnerabilities in Smart Home Devices *; ARC Linkage Projects Scheme
- 2019: UbiSENSE (ubiquitous sensing) for Cities (D61 Challenge: E01) (A scalable way of evaluating the security of commercial IoT devices) *; DATA61
- 2018: Blockchain Lab Phase 1 Project (Artchain) *; ArtChain Global Pty Ltd
- 2018: Blockchain Lab Phase 2 Project (Artchain) *; ArtChain Global Pty Ltd
- 2018: Developing an effective defence to cyber-reputation manipulation attacks *; ARC Linkage Projects Scheme
- 2018: Smart Contracts for AML/CTF Reporting Obligations *; AUSTRAC_PT
- 2017: Adversarial Machine Learning for Cyber *; Commonwealth Scientific & Industrial Research Organisation (CSIRO)
- 2017: Deep Learning for Cyber *; Commonwealth Scientific & Industrial Research Organisation (CSIRO)
* Chief Investigator
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