Traditional authentication in radio-frequency (RF) systems enable secure data communication within a network through techniques such as digital signatures and hash-based message authentication codes (HMAC), which suffer from key-recovery attacks. State-of-the-art Internet of Things networks such as Nest also use open authentication (OAuth 2.0) protocols that are vulnerable to cross-site-recovery forgery (CSRF), which shows that these techniques may not prevent an adversary from copying or modeling the secret IDs or encryption keys using invasive, side channel, learning or software attacks. Physical unclonable functions (PUFs), on the other hand, can exploit manufacturing process variations to uniquely identify silicon chips which makes a PUF-based system extremely robust and secure at low cost, as it is practically impossible to replicate the same silicon characteristics across dies. Taking inspiration from human communication, which utilizes inherent variations in the voice signatures to identify a certain speaker, we present RF-PUF: a deep neural network-based framework that allows real-time authentication of wireless nodes, using the effects of inherent process variation on RF properties of the wireless transmitters (Tx), detected through in-situ machine learning at the receiver (Rx) end. The proposed method utilizes the already-existing asymmetric RF communication framework and does not require any additional circuitry for PUF generation or feature extraction. The burden of device identification is completely shifted to the gateway Rx, similar to the operation of a human listener's brain. Simulation results involving the process variations in a standard 65-nm technology node, and features such as local oscillator offset and I-Q imbalance detected with a neural network having 50 neurons in the hidden layer indicate that the framework can distinguish up to 4800 Tx(s) with an accuracy of 99.9% [≈99% for 10000 Tx(s)] under varying channel conditions, and without the need for traditional preambles. The proposed scheme can be used as a stand-alone security feature, or as a part of traditional multifactor authentication.

This article presents a broad review on optical, radio-frequency (RF), microwave (MW), millimeter wave (mmW) and terahertz (THz) biosensors. Biomatter-wave interaction modalities are considered over a wide range of frequencies and applications such as detection of cancer biomarkers, biotin, neurotransmitters and heart rate are presented in detail. By treating biological tissue as a dielectric substance, having a unique dielectric signature, it can be characterized by frequency dependent parameters such as permittivity and conductivity. By observing the unique permittivity spectrum, cancerous cells can be distinguished from healthy ones or by measuring the changes in permittivity, concentration of medically relevant biomolecules such as glucose, neurotransmitters, vitamins and proteins, ailments and abnormalities can be detected. In case of optical biosensors, any change in permittivity is transduced to a change in optical properties such as photoluminescence, interference pattern, reflection intensity and reflection angle through techniques like quantum dots, interferometry, surface enhanced raman scattering or surface plasmon resonance. Conversely, in case of RF, MW, mmW and THz biosensors, capacitive sensing is most commonly employed where changes in permittivity are reflected as changes in capacitance, through components like interdigitated electrodes, resonators and microstrip structures. In this paper, interactions of EM waves with biomatter are considered, with an emphasis on a clear demarcation of various modalities, their underlying principles and applications.

Human Body Communication (HBC) has emerged as an alternative to radio wave communication for connecting low power, miniaturized wearable and implantable devices in, on and around the human body. HBC uses the human body as the communication channel between on-body devices. Previous studies characterizing the human body channel has reported widely varying channel response much of which has been attributed to the variation in measurement setup. This calls for the development of a unifying bio-physical model of HBC supported by in-depth analysis and an understanding of the effect of excitation, termination modality on HBC measurements. This paper characterizes the human body channel up to 1MHz frequency to evaluate it as a medium for broadband communication. The communication occurs primarily in the electro-quasistatic (EQS) regime at these frequencies through the subcutaneous tissues. A lumped bio-physical model of HBC is developed, supported by experimental validations that provides insight into some of the key discrepancies found in previous studies. Voltage loss measurements are carried out both with an oscilloscope and a miniaturized wearable prototype to capture the effects of non-common ground. Results show that the channel loss is strongly dependent on the termination impedance at the receiver end, with up to 4dB variation in average loss for different termination in an oscilloscope and an additional 9 dB channel loss with wearable prototype compared to an oscilloscope measurement. The measured channel response with capacitive termination reduces low-frequency loss and allows flat-band transfer function down to 13 KHz, establishing the human body as a broadband communication channel. Analysis of the measured results and the simulation model shows that instruments with $50\Omega$ input impedance (Vector Network Analyzer, Spectrum Analyzer) provides pessimistic estimation of channel loss at low frequencies. Instead (1) high impedance (2) capacitive termination should be used at the receiver end for accurate voltage mode loss measurements of the HBC channel at low frequencies. The experimentally validated bio-physical model shows that capacitive voltage mode termination can improve the low frequency loss by up to 50dB, which helps broadband communication significantly.

Human body communication (HBC) utilizes the human body as the communication medium between devices in and around the body, providing an energy-efficient, secure alternative to radio wave communication traditionally used in body area networks (BAN). However, the human antenna effect results in the human body picking up environmental interference affecting HBC transmissions. Most state-of-the-art HBC transceivers utilize narrowband modulation techniques to communicate using frequencies, which are not affected by interference. In this article, we use capacitive termination and voltage mode communication techniques to utilize the human body as a broadband (BB) communication channel enabling as a BB HBC. An integrating dual data rate (I-DDR) receiver utilizing time-domain interference rejection (TD-IR) through integration and periodic sampling is used for interference-robust BB HBC operation. The proposed receiver can achieve higher energy efficiency as it utilizes the full bandwidth of the body for data transmission and does not require any modulation/ demodulation. The BB HBC transceiver is fabricated in the TSMC 65-nm technology. Measurement results show 6.3-pJ/bit energy efficiency at a data rate of 30 Mb/s with -30-dB signal-to-interference ratio (SIR) tolerance, making it 18x energy efficient compared with state-of-the-art HBC transceivers.

Human Body Communication (HBC) utilizes the electrical conductivity properties of the human body to communicate between devices in and around the body. The increased energy-efficiency and security provided by HBC compared to traditional radio wave based communication makes it a promising alternative to communicate between energy constrained wearable and implantable devices around the body.However, HBC requires electrical signals to be transmitted through the body, which makes it essential to have a thorough analysis of the safety aspects of such transmission. This paper looks into the compliance of the current density and electric/magnetic fields generated in different modalities of HBC with the established safety standards. Circuit and Finite Element Method (FEM) based simulations are carried out to quantitatively find the compliance of current density and fields with the established safety limits. The results show the currents and fields in capacitive HBC are orders of magnitude smaller than the specified limits. However, certain excitation modalties in galvanic HBC can result in current densities and fields exceeding the safety limits around the excitation point on the body near the electrode. A study with 7 human subjects (4 male, 3 female) is carried out over a month, using capacitive HBC.The study monitors the change in 5 vital parameters (Heart Rate, Mean Arterial Pressure, Respiration Rate, Peripheral Capillary Oxygen Saturation, Temperature), while wearing a HBC enabled device. Analysis of the acquired data statistically shows no significant change in any of the vital parameters of the subjects, confirming the results of the simulation study.

Mathematically secure cryptographic algorithms, when implemented on a physical substrate, leak critical “side-channel” information, leading to power and electromagnetic (EM) analysis attacks. Circuit-level protections involve switched capacitor, buck converter, or series low-dropout (LDO) regulator-based implementations, each of which suffers from significant power, area, or performance tradeoffs and has only achieved a minimum traces to disclosure (MTD) of $10M$ till date. Utilizing an in-depth white-box model, this work, for the first time, focuses on signature suppression in the current domain, which provides an $Attenuation^{2}$ enhancement in MTD, leading to orders of magnitude improvement in both power and EM side-channel analysis (SCA) immunities. Using a combination of current-domain “signature attenuation” (CDSA) along with local lower level metal routing, the critical correlated information in the crypto current is significantly suppressed before it reaches the supply pin. Especially, to prevent the EM leakage from its source (metal layers carrying the correlated crypto current acting as antennas), this work embraces lower level metal routing of the CDSA embedding the crypto-IP so that the signature becomes highly suppressed before it passes through the higher metal layers (which radiates significantly) to connect to the external pin. The 65-nm CMOS test chip contains both protected and unprotected parallel AES-256 implementations, running at a clock frequency of 50 MHz. Test vector leakage assessment (TVLA) on the protected CDSA-AES, demonstrated with on-chip measurements for the first time, shows that the higher level metal layers leak significantly more compared with the lower level metal routing. Correlational power and EM analysis (CPA/CEMA) attacks on the unprotected implementation were able to extract the secret key within $8k$ and $12k$ traces, respectively, while the protected CDSA-AES could not be broken even after $1B$ encryptions for both power and EM SCA, evaluated both in the time and frequency domains, showing an improvement of $100\times $ over the prior state-of-the-art countermeasures with comparable power and area overheads.