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The increasing popularity of portable ECG systems and the growing demand for privacy-compliant, energy-efficient real-time analysis require new approaches to signal processing at the point of data acquisition. In this context, the edge…

The fourth industrial revolution leads to an increased use of embedded computation and intercommunication in an industrial environment. While reducing cost and effort for set up, operation and maintenance, and increasing the time to…

Mobile edge computing (MEC) is an emerging technology to transform the cloud-based computing services into the edge-based ones. Autonomous vehicular network (AVNET), as one of the most promising applications of MEC, can feature edge…

The side-channel attack is an attack method based on the information gained about implementations of computer systems, rather than weaknesses in algorithms. Information about system characteristics such as power consumption, electromagnetic…

Side-channel and fault injection attacks reveal secret information by monitoring or manipulating the physical effects of computations involving secret variables. Circuit-level countermeasures help to deter these attacks, and traditionally…

By exploiting the modular RISC-V ISA this paper presents the customization of instruction set with posit\textsuperscript{\texttrademark} arithmetic instructions to provide improved numerical accuracy, well-defined behavior and increased…

Spiking Neural Networks (SNNs) offer high energy efficiency and event-driven computation, ideal for low-power edge AI. Their hardware implementation on FPGAs, however, faces challenges due to heavy computation, large memory use, and limited…

Edge computing efficiently extends the realm of information technology beyond the boundary defined by cloud computing paradigm. Performing computation near the source and destination, edge computing is promising to address the challenges in…

Privacy and security have rapidly emerged as first order design constraints. Users now demand more protection over who can see their data (confidentiality) as well as how it is used (control). Here, existing cryptographic techniques for…

Trusted execution environments in several existing and upcoming CPUs demonstrate the success of confidential computing, with the caveat that tenants cannot securely use accelerators such as GPUs and FPGAs. In this paper, we reconsider the…

Side-channel attacks impose a serious threat to cryptographic algorithms, including widely employed ones, such as AES and RSA. These attacks take advantage of the algorithm implementation in hardware or software to extract secret…

Mobile edge computing (MEC) is a promising approach for enabling cloud-computing capabilities at the edge of cellular networks. Nonetheless, security is becoming an increasingly important issue in MEC-based applications. In this paper, we…

AI-powered edge computing security is moving Intelligent Transportation Systems (ITS) from passive, rule-based protections to proactive, smart, zero-touch, self-sufficient safeguards that neutralize threats in milliseconds. As…

Neural Networks (NNs) have been widely adopted due to their outstanding efficacy and adaptability across computer vision and deep learning applications. The optimization of NNs is necessary to enable their deployment on energy constrained…

Data collection and processing in advanced health monitoring systems are experiencing revolutionary change. In-Sensor Computing (ISC) systems emerge as a promising alternative to save energy on massive data transmission, analog-to-digital…

Side-channel attacks that use machine learning (ML) for signal analysis have become prominent threats to computer security, as ML models easily find patterns in signals. To address this problem, this paper explores using Adversarial Machine…

Side-channel based instruction disassembly has been proposed as a low-cost and non-invasive approach for security applications such as IP infringement detection, code flow analysis, malware detection, and reconstructing unknown code from…

Achieving high performance, energy efficiency, and cost-effectiveness while maintaining architectural flexibility is a critical challenge in the development and deployment of edge AI devices. Monolithic SoC designs struggle with this…

The volume, veracity, variability, and velocity of data produced from the ever-increasing network of sensors connected to Internet pose challenges for power management, scalability, and sustainability of cloud computing infrastructure.…

Edge computing is providing higher class intelligent service and computing capabilities at the edge of the network. The aim is to ease the backhaul impacts and offer an improved user experience, however, the edge artificial intelligence…