Biblio
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A Threat Model and Security Recommendations for IoT Sensors in Connected Vehicle Networks. 2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring). :1—5.
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2022. Intelligent transportation systems, such as connected vehicles, are able to establish real-time, optimized and collision-free communication with the surrounding ecosystem. Introducing the internet of things (IoT) in connected vehicles relies on deployment of massive scale sensors, actuators, electronic control units (ECUs) and antennas with embedded software and communication technologies. Combined with the lack of designed-in security for sensors and ECUs, this creates challenges for security engineers and architects to identify, understand and analyze threats so that actions can be taken to protect the system assets. This paper proposes a novel STRIDE-based threat model for IoT sensors in connected vehicle networks aimed at addressing these challenges. Using a reference architecture of a connected vehicle, we identify system assets in connected vehicle sub-systems such as devices and peripherals that mostly involve sensors. Moreover, we provide a prioritized set of security recommendations, with consideration to the feasibility and deployment challenges, which enables practical applicability of the developed threat model to help specify security requirements to protect critical assets within the sensor network.
Analysis of ICMetrics Features/Technology for Wearable Devices IOT Sensors. 2017 Seventh International Conference on Emerging Security Technologies (EST). :175–178.
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2017. This paper investigates the suitability of employing various measurable features derived from multiple wearable devices (Apple Watch), for the generation of unique authentication and encryption keys related to the user. This technique is termed as ICMetrics. The ICMetrics technology requires identifying the suitable features in an environment for key generation most useful for online services. This paper presents an evaluation of the feasibility of identifying a unique user based on desirable feature set and activity data collected over short and long term and explores how the number of samples being factored into the ICMetrics system affects uniqueness of the key.