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Direct Memory Access (DMA) is a state-of-the-art technique to optimize the speed of memory access and to efficiently use processing power during data transfers between the main system and a peripheral device. However, this advanced feature opens security vulnerabilities of access compromise and to manipulate the main memory of the victim host machine. The paper outlines a lightweight process that creates resilience against DMA attacks minimal modification to the configuration of the DMA protocol. The proposed scheme performs device identification of the trusted PCIe devices that have DMA capabilities and constructs a database of profiling time to authenticate the trusted devices before they can access the system. The results show that the proposed scheme generates a unique identifier for trusted devices and authenticates the devices. Furthermore, a machine learning–based real-time authentication scheme is proposed that enables runtime authentication and share the results of the time required for training and respective accuracy. 

With the extensive application of the Direct Memory Access (DMA) technique, the efficiency of data transfer between the peripheral and the host machine has been improved dramatically. However, these optimizations also introduce security vulnerabilities and expose the process of data transmission to DMA attacks that utilize the feature of direct access to steal the data stored in the live memory on the victim system. In this paper, we propose a lightweight scheme to provide resilience to DMA attacks without physical and protocol-level modification. The proposed scheme constructs a unique identifier for each DMA-supported PCIe device based on profiling time and builds a trusted database for authentication. The experimental result shows that the proposed methodology eliminates most of the noise produced in the measuring process for identifier construction and the success rate of authentication is 100% for all the devices. 

Integration of complex and high-speed electronic components in the state of art electric power system enhances the need for improved security infrastructure and resilience against invasive and non-invasive attacks on the smart grid. A modern smart grid system integrates a variety of instruments and standards to achieve cost-effective and time-effective energy measurement and management. As the fundamental component in the smart grid, the smart meter supports real-time monitoring, automatic control, and high-speed communication along with power consumption recording. However, the wide use of smart meters also increases privacy and security concerns. In this paper, we demonstrate the vulnerability of side-channel attacks on secure communication in smart grids for software-based and hardware-based implementations. 

Reconfigurable logic enables architectural updates for embedded devices by providing the ability to reprogram partial or entire device. However, this flexibility can be leveraged by the adversary to compromise the device boot process by modifying the bitstream or the boot process with physical or remote access of device placed in a remote field. We propose a novel multilayer secure boot mechanism for SoCs with a two-stage secure boot process. First stage uses device bound unique response as a key to decrypt application logic. The security function is extended at runtime by integrating intermittent architecture and application locking mechanism to reveal correct functionality. 

The Internet of Things (IoT) are paradigm shift transforming embedded objects into a smart connected device, ready to sense, analyze and communicate information with other devices. Nowadays, IoT devices are widely used in smart home systems and smart grid systems at a high level of integration and automation. However, the increasing tendency of the smart device also leads to a problem of security. The recent exploitations of the connected smart devices’ vulnerabilities reinforce the importance of security implementation and integration at the system level. In this work, we propose some use cases to show the vulnerability of the smart bulb to different attacks.