A Survey of Techniques for Improving Security of GPUs

Graphics processing unit (GPU), although a powerful performance-booster, also has many security vulnerabilities. Due to these, the GPU can act as a safe-haven for stealthy malware and the weakest `link' in the security `chain'. In this paper, we present a survey of techniques for analyzing and improving GPU security. We classify the works on key attributes to highlight their similarities and differences. More than informing users and researchers about GPU security techniques, this survey aims to increase their awareness about GPU security vulnerabilities and potential countermeasures

Framework of Hardware Trojan Detection Leveraging Structural Checking Tool

Since there is a significant demand for obtaining third-party soft Intellectual Property (IP) by first-party integrated circuit (IC) vendors, it is becoming easier for adversaries to insert malicious logic known as hardware Trojans into designs. Due to this, vendors need to find ways to screen the third-party IPs for possible security threats and then mitigate them. The development of the Structural Checking (SC) tool provides a solution to this issue. This tool analyzes the structure of an unknown soft IP design and creates a network of all the signals within the design and how they are connected to each other. In addition, these signals will be assigned with assets. Assets describe the central role of a signal in the entire design. These assets are then used to create asset patterns, which will be crucial for this thesis research. Previous research on SC tool focuses on Trojan detection by comparing and matching an unknown design to a trusted design in a Golden Reference Library. In this thesis research, another method of Trojan detection has been implemented in the SC tool, which focuses on recognizing specific asset patterns that mainly exist in Trojan-infested designs. These specific asset patterns can then be used to check against unknown designs for Trojans without using a Golden Reference Library. This thesis improves this method by creating a new framework for easily identifying the unique Trojan asset patterns

ENABLING IOT AUTHENTICATION, PRIVACY AND SECURITY VIA BLOCKCHAIN

Although low-power and Internet-connected gadgets and sensors are increasingly integrated into our lives, the optimal design of these systems remains an issue. In particular, authentication, privacy, security, and performance are critical success factors. Furthermore, with emerging research areas such as autonomous cars, advanced manufacturing, smart cities, and building, usage of the Internet of Things (IoT) devices is expected to skyrocket. A single compromised node can be turned into a malicious one that brings down whole systems or causes disasters in safety-critical applications. This dissertation addresses the critical problems of (i) device management, (ii) data management, and (iii) service management in IoT systems. In particular, we propose an integrated platform solution for IoT device authentication, data privacy, and service security via blockchain-based smart contracts. We ensure IoT device authentication by blockchain-based IC traceability system, from its fabrication to its end-of-life, allowing both the supplier and a potential customer to verify an IC’s provenance. Results show that our proposed consortium blockchain framework implementation in Hyperledger Fabric for IC traceability achieves a throughput of 35 transactions per second (tps). To corroborate the blockchain information, we authenticate the IC securely and uniquely with an embedded Physically Unclonable Function (PUF). For reliable Weak PUF-based authentication, our proposed accelerated aging technique reduces the cumulative burn-in cost by ∼ 56%. We also propose a blockchain-based solution to integrate the privacy of data generated from the IoT devices by giving users control of their privacy. The smart contract controlled trust-base ensures that the users have private access to their IoT devices and data. We then propose a remote configuration of IC features via smart contracts, where an IC can be programmed repeatedly and securely. This programmability will enable users to upgrade IC features or rent upgraded IC features for a fixed period after users have purchased the IC. We tailor the hardware to meet the blockchain performance. Our on-die hardware module design enforces the hardware configuration’s secure execution and uses only 2,844 slices in the Xilinx Zedboard Zynq Evaluation board. The blockchain framework facilitates decentralized IoT, where interacting devices are empowered to execute digital contracts autonomously

Network Interface Design for Network-on-Chip

In the culture of globalized integrated circuit (IC, a.k.a chip) production, the use of Intellectual Property (IP) cores, computer aided design tools (CAD) and testing services from un-trusted vendors are prevalent to reduce the time to market. Unfortunately, the globalized business model potentially creates opportunities for hardware tampering and modification from adversary, and this tampering is known as hardware Trojan (HT). Network-on-chip (NoC) has emerged as an efficient on-chip communication infrastructure. In this work, the security aspects of NoC network interface (NI), one of the most critical components in NoC will be investigated and presented. Particularly, the NI design, hardware attack models and countermeasures for NI in a NoC system are explored. An OCP compatible NI is implemented in an IBM0.18ìm CMOS technology. The synthesis results are presented and compared with existing literature. Second, comprehensive hardware attack models targeted for NI are presented from system level to circuit level. The impact of hardware Trojans on NoC functionality and performance are evaluated. Finally, a countermeasure method is proposed to address the hardware attacks in NIs