An Electromagnetic Side-Channel-Based Security Level Detection Measurement Approach in Content Transfer Remote Mechanisms

Data confidentiality is a very crucial aspect of modern information society in several fields, and particularly critical in case of telemedicine monitoring. Intrusion attempts represent a very serious threat to deal with. Attacks' success strictly depends on the possibility to get relevant information and manage them. Security mechanisms, including secure communication protocols, make the success probability lower. Unfortunately, several times communication protocols lack strong security protections. Assessing security level can be performed at various levels: in this paper, we prove how it is possible to detect if the information flowing is protected by adopting a simple measurement set-up, exploiting the electromagnetic emissions of the communication device to assess the security level of the undergoing information transfer. It can be seen as a side-channel approach, whose purpose is dual: i) prove how electromagnetic side-channel is a very sensitive part and several pieces of information could be retrieved from it (without needing of complicated profile or device access mechanisms); ii) create awareness in the community that weak transfer mechanisms should always be avoided, as they become subject to cyber attacks as the attacker could assess lack of security protocols in such a non-invasive way. This could have high impacting consequences, as data stealing or manipulation and, in high priority situation, as medical treatment subjected to data evidence, this could potentially provoke serious issues in people: a primary example is represented by people affected by neurodegenerative diseases, whose long-term and real-time monitoring is a very crucial aspect. In this framework, obtained results confirm the capability to detect the security level of protocols with an accuracy equal to 1, while the method distinguishes among four different transfer protocols (two secure and two not-secure cases) with a mean accuracy higher than 0.9.