Biblio

Data security is the main challenge in Internet of Things (IoT) applications. Security strength and the immunity to security attacks depend mainly on the available power budget. The power-security level trade-off is the main challenge for low power IoT applications, especially, energy limited IoT applications. In this paper, multiple encryption modes that provide different power consumption and security level values are hardware implemented. In other words, some modes provide high security levels at the expense of high power consumption and other modes provide low power consumption with low security level. Dynamic Partial Reconfiguration (DPR) is utilized to adaptively configure the hardware security module based on the available power budget. For example, for a given power constraint, the DPR controller configures the security module with the security mode that meets the available power constraint. ZC702 evaluation board is utilized to implement the proposed encryption modes using DPR. A Lightweight Authenticated Cipher (ACORN) is the most suitable encryption mode for low power IoT applications as it consumes the minimum power and area among the selected candidates at the expense of low throughput. The whole DPR system is tested with a maximum dynamic power dissipation of 10.08 mW. The suggested DPR system saves about 59.9% of the utilized LUTs compared to the individual implementation of the selected encryption modes.

With the increase in signal's bandwidth, the conventional analog to digital converters (ADCs), operating on the basis of Shannon/Nyquist theorem, are forced to work at very high rates leading to low dynamic range and high power consumptions. This paper here tells about one Analog to Information converter developed based on compressive sensing techniques. The high sampling rates, which is the main drawback for ADCs, is being successfully reduced to 4 times lower than the conventional rates. The system is also accompanied with the advantage of low power dissipation.