Associate ProfessorSuranga Seneviratne
Associate Professor in Security
Faculty of Engineering
- Associate Professor in SecurityFaculty of Engineering
RESEARCH INTERESTs
With billions of devices and users worldwide now connected to the internet, and this number increasing exponentially, protecting the security and privacy of internet users has never been more crucial. This is the important area on which Dr Suranga Seneviratne's research focuses.
"While the internet has made our lives easier in many ways, it also comes with some associated risks. In the past few years alone, we've witnessed significant data breaches, botnets in operation, cyberterrorism activities, and distributed denial-of-service attacks at scales never seen before. Ongoing advances in artificial intelligence also equip attackers with increasingly sophisticated tools that can be leveraged to launch novel and resilient attacks.
My research looks at how to secure networked systems and end-user devices from cyberattacks. The main challenge in doing this is the trade-off between usability and security - it's not practical to develop highly secure systems if they impose additional usability overheads on the user.
Cybersecurity has always been an ongoing arms race between attackers and researchers. As security researchers, we need to identify vulnerabilities and potential threats before they are exploited and devise countermeasures when attackers adapt their strategies. I enjoy this continuous challenge of working in network security, and its very dynamic nature.
Some of the applications of my research include more usable authentication systems. For example, I'm currently working on novel and ubiquitous behaviour biometrics that will enable intrusion-free sensing and thus allow users to authenticate without any password or security token.
"I've also developed an app for mobile devices that provides a five-star security rating for apps installed on the device and suggests secure alternatives to any riskier or more vulnerable apps that users have installed.
I have been working in network security since 2011, and I joined the University of Sydney in 2017.
I envision a future where we can use the internet seamlessly and pervasively without worrying about security and privacy."
FUNDED RESEARCH
- GRANTClearSight: LLM Agent Assisted Network Discovery and Mapping Under Partial Network Visibility (DIN SII)NSW Department of Industry1 Jan 2025People funded by this grant:
- Seneviratne S,
- Zomaya A,
- De Alvis C,
- Thilakarathna K
- GRANTUnsupervised User Identification At-Scale Using Multi-Modal Behavioural BiometricsOffice of National Intelligence1 Jan 2025People funded by this grant:
- Seneviratne A,
- Seneviratne S
- GRANTBetrayed by Apps: Automated, Scalable Detection of Mobile App MalpracticesAustralian Research Council (ARC)1 Jan 2022 - 4 Sep 2026People funded by this grant:
- Seneviratne S
- GRANTResilient and Secure Edge Computing for Untrusted Distributed SystemsOffice of National Intelligence1 Jan 2022People funded by this grant:
- Seneviratne S,
- Zomaya A,
- Thilakarathna K
- GRANTResilient and Trustworthy Edge Computing (DIN project)NSW Department of Industry1 Sep 2021People funded by this grant:
- Lee YC,
- Zomaya A,
- Seneviratne S,
- Seneviratne A,
- Kanhere S
- GRANTPrivacy-preserving data access mechanism for resource-constrained healthcare devicesNSW Department of Industry1 Sep 2018People funded by this grant:
- Seneviratne S,
- Jha SK,
- Seneviratne A
- GRANTUnderstanding the Threat Landscape for IoT in AustraliaNSW Department of Industry1 Jul 2018People funded by this grant:
- Seneviratne S,
- Holz R,
- Hassan M,
- Thilakarathna K,
- Zomaya A
- GRANTMultimodal Neural Embeddings for Detecting Counterfeit AppsGoogle LLC1 May 2018People funded by this grant:
- Gudmundsson J,
- Thilakarathna K,
- Seneviratne S
- GRANTInternet-scale Phishing Website Detection Through Deep Feature-based Image Embeddings and ForensicsNSW Department of Industry1 Jan 2018People funded by this grant:
- Seneviratne S,
- Holz R,
- Tao D,
- Hagenbuchner M,
- Wang Z