# Smart Devices Security Enhancement via Power Supply Monitoring +
## 1 Introduction  
Successful attacks targeting Internet of Things (IoT) smart devices have been reported [1; 2; 3] in many research works presented in recent years. This raises significant security issues and sets new challenges. The security issues concern the personal safety of civilians and the security of their equipment, as well as the protection of other digital infrastructures from a potential botnet attack. On the other hand, there are challenges in confronting successful attacks originating frombotnets populated of hijacked IoT devices. The number of attacks is increasing exponentially each year, in analogy to the vulnerabilities they exploit, and most of the time, with unpredictable results. The characteristics of the attacks vary significantly from attack to attack and from time to time. The warnings for the severity of the attacks [4] indicate that there is a need for solutions addressing attacks from birth. Moreover, following protocols similar to the pandemic spread of a biological virus, there is a need to quarantine infected IoT devices, thus prohibiting the spread of the infection and thus the formation of the botnet. However, this is difficult since there is no previous knowledge of a new virus, or the vulnerabilities of a smart device. Finally, since there is physical access to smart devices, there is even the threat of software alteration just by swapping the device's memory card.  
In addition to the previously mentioned security issues, there is the need to monitor normal operation of our equipment. This includes operation time, power dissipation and many more. It is desirable to detect any anomaly on time in order to avoid electrification or permanent destruction of our equipment. Issues like electronic ageing, physical degradation of materials, etc., may create significant difference in characteristics of operation without being evident in due time.  
This work is an extended version of [5] and presents a new concept for the identification of an anomaly created by a virus attack to an IoT device or by the damage of a capacitor in the electronic device. The work leverages lessons learned from side-channel attack technique and specifically, power analysis [6]. This implies that power analysis may serve as a unique signature of the executed code. Since an IoT device executes usually only one well defined task, it turns out that the behaviours (operation) of an executed code may be easily analyzed [7]. Furthermore, since this behaviour is defined by the processing components of the device utilized by the executed code, then the overall power dissipation during normal operation varies in an explicit range. Thus, during normal operation, we expect the device's power dissipation to be found in this safe range. Since such a device may have several operation modes (e.g., normal operation, update, sleep mode, etc.) it is possible to extend the safe range to include several ranges, forming clusters of operation. Thus, any power deviation, caused by either increased traffic to the network or an internal anomaly (Trojan hardware or software virus) is expected to be detected.  
This work is organized as follows. In Section 2, an exploration of related work is offered and in Section 3, the proposed approach to detect an IoT device's anomalous operation is presented. Then, in Sections 4 and 5, the experiments and the results from the implementation of a prototype are presented. Finally, in Section 6, the paper is concluded.