Dr Owen Lo is a Research Fellow at Edinburgh Napier University. Owen graduated obtained a 1st Honours (Class Medal Award) degree in Computer Networks and Distributed Systems at Edinburgh Napier University before continuing to complete a PhD at the same institute on the topic of e-Health. Some awards Owen has received include: Young Software Engineer of the Year Award (Lumison Prize)(2010), Team Prize Raytheon Cyber Challenge Award (2011) and Student of the Year ENU Award (2012).
During his PhD, Owen contributed to the Data Capture and Auto Identification Reference (DACAR) Project – a project funded in part by EPSRC and TSB – which aimed to create a secure cloud-based information sharing platform for patient data in healthcare environments. His work on the DACAR project includes the development of a Patient Simulator and an electronic version of the Early Warning Score system used to perform risk assessment on patients. The Patient Simulator was designed to simulate the vital physiological signs of a human patient (heart rate, blood pressure, respirator rate, oxygen levels and breath rate) while the electronic EWS allowed for automated risk assessment based on the parameters observed in a patient. The Patient Simulator and electronic EWS system proved instrumental in demonstrating and evaluating the capabilities of the DACAR e-Health platform in the context of secure input, processing and output of clinical data.
Following on from the DACAR project, Owen also worked on the development of a consumer transaction simulator which was designed to evaluate a secret sharing engine used by the company Payfont. The secret sharing engine used by Payfont had capability of applying numerous sharing algorithms including Shamir’s Secret Sharing (SS), Perfect Secret Sharing (PSS), Information Dispersal Algorithm (IDA) and Computational Secret Sharing (CSS). The simulator developed for this work allowed one to create different scenarios to determine which algorithm was most functional relative to the performance of data to be fragmented.
During his time as a researcher at Edinburgh Napier University, Owen has also contributed to the successful spin-out of two companies: Symphonic Software and Cyan Forensics. For Symphonic Software, Owen helped develop an information sharing engine used for the secure and trusted sharing of information between different sectors including finance, healthcare, social care and law enforcement. His work on Symphonic Software also involved research on the OAuth 2.0 protocol used by digital identity providers (e.g. Facebook, Google, LinkedIn and so on). His work on Cyan Forensics included the development of a fully-featured contraband detection software used to rapidly determine if an individual is suspected of storing illegal data on a computer. The contraband detection software was designed specifically to be used by digital forensics experts within the law enforcement sector.
More recently, Owen has successfully worked on collaboration projects with business and industry partners including Morgan Stanley and Keysight Technologies. His collaboration with Morgan Stanley focused on insider threats and investigated machine learning techniques to assess how one may determine if an employee was a threat to the organisation. In his most recent work, his collaboration with Keysight Technologies has involved research on the topic of side channel analysis and vulnerabilities related to IoT devices. His work on side channel analysis involved applying a technique known as power analysis to block based cryptographic algorithms including Advanced Encryption Standard (AES) and PRESENT. His results has shown that both algorithms are susceptible to information leakage (i.e. the private key may be revealed) under certain conditions which results in the compromised security of both algorithms. Lastly, Owen’s research into IoT security has demonstrated numerous vulnerabilities with consumer ready devices including network service vulnerabilities and Bluetooth Low Energy vulnerabilities.