Security and Privacy Vulnerabilities in Human Activity Recognition systems

Vasiliki Liagkou, Sofia Sakka, Chrysostomos D. Stylios · 2022

Human activity recognition systems (HARS) should allow the secure and trustworthy exchange of sensitive data between several kinds of participating parties with different aims and claims, regarding security, data protection, and trust issues. Initially in this work, a security flaw has been identified in a complete medical IoT application using wearable devices and smart sensors. Then, we list the security vulnerabilities and attempt to make suggestions on the prevention of security flaws that may appear during the implementation of HARS and we analyze a specific attack, the Man in the Middle attack, where a third malicious entity interferes with communication between two entities and is associated with key exchange protocols. Moreover, we discuss various design considerations for protecting the data that is transmitted and stored from different sources like smart wearables, mobile phones, and cloud applications by using cryptographic and privacy-preserving techniques. Finally, we show how the use of the OAuth2.0 protocol can ensure that only authenticated users interact with the HARS.

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