Abstract
Security is now becoming a well-established challenge for integrated circuits (ICs). Various types of IC attacks have been reported, including reverse engineering IPs, dumping on-chip data, and controlling/modifying IC operation. IEEE 1149.1, commonly known as Joint Test Action Group (JTAG), is a standard for providing test access to an IC. JTAG is primarily used for IC manufacturing test, but also for in-field debugging and failure analysis since it gives access to internal subsystems of the IC. Because the JTAG needs to be left intact and operational after fabrication, it inevitably provides a "backdoor" that can be exploited outside its intended use. This paper proposes machine learning-based approaches to detect illegitimate use of the JTAG. Specifically, JTAG operation is characterized using various features that are then classified as either legitimate or attack. Experiments using the OpenSPARC T2 platform demonstrate that the proposed approaches can classify legitimate JTAG operation and known attacks with significantly high accuracy. Experiments also demonstrate that unknown and disguised attacks can be detected with high accuracy as well (99% and 94%, respectively).

Abstract
Source routing (SR) minimum cost forwarding (MCF) – SRMCF – is a reactive, energy-efficient routing protocol proposed to improve the existent MCF methods utilized in heterogeneous wireless sensor networks (WSN). This paper presents an analytical analysis with experimental support that demonstrates the effectiveness of the proposed protocol. SRMCF stems from SR concepts and MCF methods exploited in ad hoc WSNs, where all unicast communications (between sensor nodes and the base station, or vice versa) use minimum cost paths. The protocol utilized in the present work was updated and now also handles link and node failures. Theoretical analysis and simulations show that the final protocol exhibits better throughput and energy consumption than MCF. Memory requirements for the routing table in the base station are also analyzed. Experimental results in a real scenario were obtained for implementations of both protocols, MCF and SRMCF, deployed in a small network of TelosB motes. Results show that SRMCF presents a 33% higher throughput and 24% less energy consumption than MCF. Extensive © 2019 River Publishers

Abstract
A new wearable data capture system for gait analysis is being developed. It consists of a pantyhose with embedded conductive yarns interconnecting customized sensing electronic devices that capture inertial and electromyographic signals and send aggregated information to a personal computer through a wireless link. The use of conductive yarns to build the myoelectric electrodes and the interconnections of the wired sensors network as well as the topology and functionality of the sensor modules are presented. © The Institution of Engineering and Technology 2017.

Abstract
This chapter presents a one-way method for synchronization at the media access control (MAC) layer of nodes and a circuit based on that in a wearable sensor network. The proposed approach minimizes the time skew with an accuracy of half of clock cycle in average. The work is intended to be used in a router integrated circuit (IC) designed for wearable systems. In particular, we address the need for good time synchronization in the simultaneous acquisition of surface electromyographic signals of several muscles. In our main application case, the electrodes are embedded in patient clothes connected to sensor nodes (SNs) equipped with analog-to-digital converters. The SNs are connected together in a network using conducting yarns embedded in the clothes. In the context of such wearable sensor networks, the main contributions of this work are the evaluation of existing protocols for synchronization, the description of a simpler, resource-efficient synchronization protocol, and its analysis, including the determination of the average local and global clock skew and of the synchronization probability in the presence of link failures. Both theoretical analysis and experimental results, in wired wearable networks, show that the proposed protocol has a better performance than precision time protocol (PTP), a standard timing protocol for both single and multihop situations. The proposed approach is simpler, requires no calculations, and exchanges fewer messages. Experimental results obtained with an implementation of the protocol in 0.35 µm complementary metal oxide semiconductor (CMOS) technology show that this approach keeps the one-hop average clock skew around 4.6 ns and peak-to-peak skew around 50 ns for a system clock frequency of 20 MHz. © The Institution of Engineering and Technology 2017.

Abstract
This chapter addresses a wearable body area network (BAN) system for both medical and nonmedical applications, especially those including a large number of sensors at BAN scale (<250), embedded in textile and with high data rate (<9+9 MHz) communication demands. The overall system includes an on-body central processing module (CPM) connected to a computer via a wireless link and a wearable sensor network. Due to the fixed location of the sensors and the possibility of using conductive yarns in textiles, a wired network has been considered for the wearable components. Employing conductive yarns instead of using wireless links provides a more reliable communication, higher data rates and throughput, and less power consumption. The wearable unit is composed of two types of circuits, the sensor nodes (SNs) and a base station (BS), all connected to each other with conductive yarns forming a mesh topology with the base node at the center. The reliability analysis shows that communication in a multi-hop connection of sensors in mesh topology is more reliable than in the conventional star topology. From the standpoint of the network, each SN is a four port router capable of handling packets from destination nodes to the BS. The end-to-end communication uses packet switching for packet delivery from SNs to the BS or in the reverse direction, or between SNs. The communication module has been implemented in a low power field programmable gate arrays (FPGA) and a microcontroller. The maximum data rate of the system is 9+9 Mbps while supporting tens of sensors, which is much more than current BAN applications need. The suitability of the proposed system for utilization in real applications has been demonstrated experimentally. © The Institution of Engineering and Technology 2017.

Abstract
Integrate-and-fire (IFN) model of a biological neuron is an amplitude-to-time conversion technique that encodes information in the time-spacing between action potentials (spikes). In principle, this encoding scheme can be used to modulate signals in an impulse radio ultra wide-band (IR-UWB) transmitter, making it suitable for low-power applications, such as in wireless sensor networks (WSN) and biomedical monitoring. This paper then proposes an architecture based on IFN encoding method applied to a UWB transceiver scenario, referred to herein as impulse-radio integrate-and-fire (IRIF) transceiver, followed by a system-level study to attest its effectiveness. The transmitter is composed of an integrate-and-fire modulator, a digital controller and memory block, followed by a UWB pulse generator and filter. At the receiver side, a low-noise amplifier, a squarer, a low-pass filter and a comparator form an energy-detection receiver. A processor reconstructs the original signal at the receiver, and the quality of the synthesized signal is then verified in terms of effective number of bits (ENOB). Finally, a link budget is performed. (C) 2019 Published by Elsevier GmbH.