In this paper we discuss security procedures for constrained IoT devices. We start with the description of a general security architecture along with its basic procedures, then discuss how its elements interact with the constrained communication stack and explore pros and cons of popular security approaches at various layers of the ISO/OSI model. We also discuss a practical example for the establishment of end-to-end secure channels between constrained and unconstrained devices. The proposed method is lightweight and allows the protection of IoT devices through strong encryption and authentication means, so that constrained devices can benefit from the same security functionalities that are typical of unconstrained domains, without however having to execute computationally intensive operations. To make this possible, we advocate using trusted unconstrained nodes for the offloading of computationally intensive tasks. Moreover, our design does not require any modifications to the protocol stacks of unconstrained nodes

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In this paper, we present the implementation and performance evaluation of security functionalities at the link layer of IEEE 802.15.4-compliant IoT devices. Specifically, we implement the required encryption and authentication mechanisms entirely in software and as well exploit the hardware ciphers that are made available by our IoT platform. Moreover, we present quantitative results on the memory footprint, the execution time and the energy consumption of selected implementation modes and discuss some relevant tradeoffs. As expected, we find that hardware-based implementations are not only much faster, leading to latencies shorter than two orders of magnitude compared to software-based security suites, but also provide substantial savings in terms of ROM memory occupation, i.e. up to six times, and energy consumption. Furthermore, the addition of hardware-based security support at the link layer only marginally impacts the network lifetime metric, leading to worst-case reductions of just 2% compared to the case where no security is employed. This is due to the fact that energy consumption is dominated by other factors, including the transmission and reception of data packets and the control traffic that is required to maintain the network structures for routing and data collection. On the other hand, entirely software-based implementations are to be avoided as the network lifetime reduction in this case can be as high as 25%.

The emergence of Internet of Things and the availability of inexpensive sensor devices and platforms capable of wireless communications enable a wide range of applications such as intelligent home and building automation, mobile healthcare, smart logistics, distributed monitoring, smart grids, energy management, asset tracking to name a few. These devices are expected to employ Constrained Application Protocol for the integration of such applications with the Internet, which includes User Datagram Protocol binding with Datagram Transport Layer Security protocol to provide end-to-end security. This paper presents a framework called BlinkToSCoAP, obtained through the integration of three software libraries implementing lightweight versions of DTLS, CoAP and 6LoWPAN protocols over TinyOS. Furthermore, a detailed experimental campaign is presented that evaluates the performance of DTLS security blocks. The experiments analyze BlinkToSCoAP messages exchanged between two Zolertia Z1 devices, allowing evaluations in terms of memory footprint, energy consumption, latency and packet overhead. The results obtained indicate that securing CoAP with DTLS in Internet of Things is certainly feasible without incurring much overhead

Abstract-This paper considers compressed sensing (CS) techniques for signal reconstruction and channel estimation in OFDM-based high-rate ultra wideband (UWB) communication systems. We employ a parallel CS structure that exploits frequency domain sparsity. We also consider multipath UWB channels in both the line-of-sight and non line-of-sight environments. UWB signal detection and channel estimation from sub-Nyquist analog projections is carried out using an optimized orthogonal matching pursuit algorithm and the smoothed ℓ0 algorithm. Simulation results demonstrate significant gains in the form of reliable signal recovery and channel estimation as well as dramatically sub-Nyquist sampling rates for the analog-to-digital converters while maintaining high data rates.