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Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication. PubDate:
Feb. 2022
Issue No:Vol. 68, No. 1 (2022)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication. PubDate:
Feb. 2022
Issue No:Vol. 68, No. 1 (2022)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication. PubDate:
Feb. 2022
Issue No:Vol. 68, No. 1 (2022)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:
Kim Fung Tsang;
Pages: 1 - 1 Abstract: Kim-Fung Tsang, Editor-in-Chief (EiC) of the IEEE Transactions on Consumer Electronics PubDate:
Feb. 2022
Issue No:Vol. 68, No. 1 (2022)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:
Fernando Pescador;Saraju P. Mohanty;
Pages: 2 - 4 Abstract: In a recent Special Section published in IEEE Transactions on Consumer Electronics we introduced smart electronics [1]. We presented a set of papers which were selected after rigorous review with a scope of artificial intelligence (AI) or machine learning (ML) approaches used for various levels of system abstractions, from device-level to system-level. In one school of thought energy-smart, security-smart, and response-smart are 3 dimensions of smart electronic systems. PubDate:
Feb. 2022
Issue No:Vol. 68, No. 1 (2022)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:
Vinay C. Patil;Sandip Kundu;
Pages: 5 - 13 Abstract: Improving the reliability of energy distribution systems is a major concern to multiple parties as they are not only critical infrastructure themselves, but also affect other connected infrastructure. Smart Grids have been proposed to leverage the advantages of Internet of Things (IoT) to allow smarter management and faster recovery of energy distribution systems against disruptions. However, Smart Grid applications require a reliable, lightweight and fast authentication system to realize their potential in a secure manner. In this work, we propose a Strong PUF (physically unclonable function) system that can meet the stringent resource and performance constraints imposed by a Smart Grid operational environment. Our results indicate that the proposed mechanism produces a Strong PUF with close to ideal normalized uniqueness of 50 % and an accuracy of 50 % to modeling attacks using the best known machine learning algorithms. Additionally, our scheme has a low hardware overhead cost of $750~ mu m^{2}$ in 45 nm technology and a sub-1 ms key generation time, ensuring the entire system is fast and lightweight. PubDate:
Feb. 2022
Issue No:Vol. 68, No. 1 (2022)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:
Amit M. Joshi;Prateek Jain;Saraju P. Mohanty;
Pages: 14 - 22 Abstract: Consumer technologies have changed human life through various products for smart healthcare management. The evaluation of Internet-of-Medical-Things (IoMT) has provided the closed loop control system for point of care mechanism. The hardware security of medical devices has drawn the attention where any security breach could have catastrophic impact. The paper discusses iGLU 3.0 which includes security model of glucose measurement device along with insulin pump of IoMT framework. The novel glucose-insulin model has been proposed for glucose control of diabetes patient. The physical unclonable function (PUF) based security solution is developed for non-invasive glucometer iGLU and insulin pump for safe insulin secretion. PUF based Hardware-Assisted Security (HAS) is helpful to mitigate challenges which are present in automatic insulin delivery with iGLU. PubDate:
Feb. 2022
Issue No:Vol. 68, No. 1 (2022)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:
Nidish Vashistha;Muhammad Monir Hossain;Md Rakib Shahriar;Farimah Farahmandi;Fahim Rahman;Mark M. Tehranipoor;
Pages: 23 - 37 Abstract: Counterfeit electronic devices can cause a significant revenue loss and brand value damage to the original component manufacturers (OCM). In addition, they can instigate serious safety and security issues in critical military and space applications. These devices can be injected by untrusted entities in the supply chain, such as outsourced foundries, distributors, PCB assemblers, and system integrators. Existing methods for device authenticity verification are either destructive, require an advanced electrical test or physical inspection infrastructure. Furthermore, the existing database query-based verification systems by OCMs provide an illusion of authenticity verification by looking for a device record in their online system. In reality, a customer may have bought a cloned or recycled copy of an electronic device and may find a valid record in the OCM verification system. This paper presents a blockchain-centric solution to address these limitations to verify electronic devices. A detailed study is presented to transform an existing supply chain into a trustworthy distributed ledger framework called eChain (electronic Chain). eChain generates device provenance records from blockchain that users can utilize to classify authentic and counterfeit ICs. A fully functional prototype of eChain is developed to demonstrate the feasibility and efficacy of the proposed solution. PubDate:
Feb. 2022
Issue No:Vol. 68, No. 1 (2022)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:
Md Nazmul Islam;Sandip Kundu;
Pages: 38 - 46 Abstract: With the continued scaling of transistor feature size, the cost of IC development has been escalating. The economics of semiconductor IC development favors high volume manufacturing, while high volume cannot be attained without developing an IC that serves many applications. Some of these applications are in low-margin Internet of Things (IoT) devices, where an SoC cannot command a high price. Consequently, without the ability to customize IC features after production, its lowest-priced application will determine an IC’s price. This motivates the manufacturers to develop chips with provisions for post-manufacturing IC customization. This paper explores how an IC can be programmed repeatedly and securely using blockchain-based smart contracts to allow users to upgrade or rent features. The availability of such a system could, for example, allow a buyer to upgrade her processor from a low-end to a high-end part by making an additional payment to the manufacturer. Implementing such a system will require remote device management capabilities. Remote device management presents unique design considerations, such as, necessity for transparency of the actions that a device takes on behalf of a user; the requirement of a trusted arbiter; and provision for management of these devices beyond the intended lifespan. To overcome the challenges of transparency, longevity, and the necessity of a trusted arbiter, we propose embedded smart contracts in concert with a blockchain. Our proposed smart contract takes the device feature configuration request as input and outputs the corresponding configuration. To support remote, secure, and authorized updates, we propose an on-die hardware module which communicates with the smart contract and enforces its functionalities. This was prototyped using a programmable system-on-chip working in concert with Ethereum blockchain. The prototype demonstrates the feasibility and practicalit- of the proposed solution. PubDate:
Feb. 2022
Issue No:Vol. 68, No. 1 (2022)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:
Amit Degada;Himanshu Thapliyal;
Pages: 47 - 56 Abstract: Designing a low-energy and secure lightweight cryptographic coprocessor is the primary design constraint for modern wireless Implantable Medical Devices (IMDs). The lightweight cryptographic ciphers are the preferred cryptographic solution for low-energy encryption. This article proposes 2-SPGAL, the 2-phase sinusoidal clocking implementation of Symmetric Pass Gate Adiabatic Logic (SPGAL) for IMDs. The proposed 2-SPGAL is energy-efficient and secure against the Correlation Power Analysis (CPA) attack. The proposed 2-SPGAL was evaluated with the integration of synchronous resonant Power Clock Generators (PCGs): (i) 2N2P-PCG, and (ii) 2N-PCG. The case study implementation of one round of PRESENT-80 encryption using 2-SPGAL, with 2N2P-PCG integrated into the design, shows an average of 47.50% of energy saving compared to its CMOS counterpart, over the frequency range of 50 kHz to 250 kHz. The same 2-SPGAL based case study, with 2N-PCG integrated into the design, shows 51.18% of an average energy saving compared to its CMOS counterpart, over 50 kHz to 250 kHz. Further, the 2-SPGAL based PRESENT-80 one round shows an average energy saving of 16.62% and 28.90% respectively for 2N2P-PCG and 2N-PCG integrated into the design compared to existing 2-phase adiabatic logic called 2-EE-SPFAL. We also subjected PRESENT-80 design of 2-SPGAL and CMOS against CPA attack. The 2-SPGAL, with 2N2P-PCG and 2N-PCG, integrated into one round of PRESENT-80 design protects the encryption key. However, the encryption key was successfully revealed in one round of PRESENT-80 design using CMOS logic. Therefore, the proposed 2-SPGAL logic can be useful to design energy-efficient and CPA resilient Implantable Medical Devices (IMDs). PubDate:
Feb. 2022
Issue No:Vol. 68, No. 1 (2022)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:
J. Y. V. Manoj Kumar;Ayas Kanta Swain;Kamalakanta Mahapatra;Saraju P. Mohanty verify;
Pages: 57 - 68 Abstract: Consumer electronics hardware is designed and manufactured following a global supply chain which opens doors to their security challenges. Even with the advanced methods of formal verification and coverage analysis, there is still a chance of hiding malicious hardware/software which can degrade performance, leak data, or even stop functionalities. In this work, we present security solution of Network on Chip (NoC) based Multiprocessor System-on-Chip (MPSoC) consumer electronics (CE) systems such as set-top boxes and autonomous vehicles. Most of the existing methods targeted for such systems focus on protection in Network Interfaces (NI) and other software solutions rather than routers against Hardware Trojans (HT) which can be embedded in NoC by a rogue designer. In this work, we propose a 3-tier methodology leading to “Fortified-NoC” to secure the data and resources against different kinds of threats. A Trojan cognizant routing algorithm (TCRA) is proposed which limits the HTs to a particular router that contains them. Data shuffling with Trojan detectability is also used to mislead and identify the HTs. We validated the proposed approach using various experiments. Our proposed method is capable of mitigating the Trojan attacks such as data leakage, performance degradation, denial of service and live locking of data packets at the cost of a little latency and, some extra hardware. It is able to recover more than 80% of lost packets, improve the throughput by $1.3times $ against performance degrading Trojan attacks. PubDate:
Feb. 2022
Issue No:Vol. 68, No. 1 (2022)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:
Sohee Lim;Minwoo Shin;Joonki Paik;
Pages: 69 - 76 Abstract: We present a generative model-based point cloud generation method using deep adversarial local features. The proposed generative adversarial network (GAN) can reduce computational load and increase the accuracy in three-dimensional (3D) acquisition, reconstruction, and rendering processes. To train the proposed GAN, we first optimize the latent space using an autoencoder to extract local features. The training process provides an accurate estimation of local context from the latent variables and robust point cloud generation. The main contribution of this work is a novel deep learning-based 3D point cloud generation, which significantly reduces computational load to render augmented reality (AR) and mixed reality (MR) contents. Additional contribution in the deep learning field is twofold: i) The autoencoder in the proposed network avoids the vanishing gradient problem using hierarchically linked features in different layers, and ii) the complexity of the network is significantly reduced by removing the transformation network that estimates the affine transformation matrix of the point cloud. PubDate:
Feb. 2022
Issue No:Vol. 68, No. 1 (2022)
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Authors:
Shunji Itani;Shunsuke Kita;Yoshinobu Kajikawa;
Pages: 77 - 84 Abstract: In recent years, biometric authentication technology for smartphones has become widespread, with the mainstream methods being fingerprint authentication and face recognition. However, fingerprint authentication cannot be used when hands are wet, and face recognition cannot be used when a person is wearing a mask. Like the face and fingers, the ear as a biometric contains features that enable human identification and has been the subject of research on personal authentication. Authentication systems based on the acoustic transfer function of the pinna (PRTF: Pinna Related Transfer Function) have been investigated. However, the authentication accuracy decreases due to the positional fluctuation across each measurement. In this paper, we propose multimodal personal authentication on smartphones using PRTF. The pinna image and positional sensor information are used with the PRTF, and the effectiveness of the authentication method is examined. Half total error rate (HTER) of 9.3% for single-modal authentication using only PRTF was improved to 1.6% for multimodal authentication using images and sensor data. We demonstrate that the proposed authentication system can compensate for the positional changes in each measurement and improve the robustness. PubDate:
Feb. 2022
Issue No:Vol. 68, No. 1 (2022)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:
Sushanta Gogoi;Rangababu Peesapati;
Pages: 85 - 92 Abstract: Motion Estimation (ME) is the most power consuming module in the video encoder due to its high computational complex operations. So designing an efficient ME hardware without losing coding performance is a major challenge. This paper proposes a low-bit-depth ME technique based on Gray-Coded bit-planes and its hardware implementation using Binary Content Addressable Memory (BCAM). The proposed method significantly reduces the computational burden due to its low-bit-depth representation. The novel BCAM based ME hardware provides faster results because of its on-chip memory computation without compromising other performance parameters. It can process 8K @53.71 fps operated at maximum frequency of 155 MHz with 152.78K NAND equivalent gate count using 90 nm technology library. PubDate:
Feb. 2022
Issue No:Vol. 68, No. 1 (2022)
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