Shahid Raza is the Director of Cybersecurity unit at RISE Research Institutes of Sweden, where he has been working since 2008. Shahid is also a Full Professor in Mälardalen University Sweden. Shahid’s research interests include but are not limited to security and privacy in IoT, secure interconnection of clouds and IoT, and threat intelligence at the edge of IoT. His work on cybersecurity is published in top journals and conferences and has received 6000+ citations. Shahid has received Industrial PhD degree in 2013 from Mälardalen University Sweden for his work on IoT security in RISE. He also holds a Master of Science degree in cybersecurity from KTH The Royal Institute of Technology (2009). Shahid is currently supervising 4 PhD students and 2 postdocs as the main supervisor, and 2 PhD students as a co-supervisor.
Shahid is also the founder and the project leader of RISE Cyber Range; co-founder of Cybercampus Sweden (cybercampus.se); director of the Swedish National Cybersecurity Research and Innovation Node; coordinator of the Horizon Europe Project CUSTODES, principal investigator (PI) and a Management Board member of H2020 CONCORDIA; technical project leader of H2020 ARCADIAN-IoT and H2020 nIoVe; coordinator of RISE Cybersecurity Competence Platform, Vinnova SIP-IoT SecureCare, H2020 Eurostars SecureIoT, SSF DIET, and SIP-IoT CEBOT; and co-PI of SSF aSSIST, VR SecuringThings, Horizon Europe HARPOCRATES, H2020 ECSEL SECREDAS, and H2020 VEDLIoT.
Personal Web: https://shahidraza.net
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Publikationer
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Publikationer
- Lightweight Security Solutions for the Internet of Things
- Securing Communication in IP-Connected Industrial Wireless Sensor Networks
- Lightweight certificate revocation for low-power IoT with end-to-end security
- AutoCert : Automated TOCTOU-secure digital certification for IoT with combined …
- ShieLD : Shielding Cross-zone Communication within Limited-resourced IoT Device…
- Secure Equality Test Technique using Identity Based Signcryption for Telemedici…
- FL4IoT : IoT Device Fingerprinting and Identification Using Federated Learning