Emerging Security Threats in Modern Digital Computing Systems: A Power Management Perspective

Design of computing systems — from pocket-sized smart phones to massive cloud based data-centers — have one common daunting challenge : minimizing the power consumption. In this effort, power management sector is undergoing a rapid and profound transformation to promote clean and energy proportional computing. At the hardware end of system design, there is proliferation of specialized, feature rich and complex power management hardware components. Similarly, in the software design layer complex power management suites are growing rapidly. Concurrent to this development, there has been an upsurge in the integration of third-party components to counter the pressures of shorter time-to-market. These trends collectively raise serious concerns about trust and security of power management solutions. In recent times, problems such as overheating, performance degradation and poor battery life, have dogged the mobile devices market, including the infamous recall of Samsung Note 7. Power outage in the data-center of a major airline left innumerable passengers stranded, with thousands of canceled flights costing over 100 million dollars. This research examines whether such events of unintentional reliability failure, can be replicated using targeted attacks by exploiting the security loopholes in the complex power management infrastructure of a computing system. At its core, this research answers an imminent research question: How can system designers ensure secure and reliable operation of third-party power management units? Specifically, this work investigates possible attack vectors, and novel non-invasive detection and defense mechanisms to safeguard system against malicious power attacks. By a joint exploration of the threat model and techniques to seamlessly detect and protect against power attacks, this project can have a lasting impact, by enabling the design of secure and cost-effective next generation hardware platforms

Design and Programming Methods for Reconfigurable Multi-Core Architectures using a Network-on-Chip-Centric Approach

A current trend in the semiconductor industry is the use of Multi-Processor Systems-on-Chip (MPSoCs) for a wide variety of applications such as image processing, automotive, multimedia, and robotic systems. Most applications gain performance advantages by executing parallel tasks on multiple processors due to the inherent parallelism. Moreover, heterogeneous structures provide high performance/energy efficiency, since application-specific processing elements (PEs) can be exploited. The increasing number of heterogeneous PEs leads to challenging communication requirements. To overcome this challenge, Networks-on-Chip (NoCs) have emerged as scalable on-chip interconnect. Nevertheless, NoCs have to deal with many design parameters such as virtual channels, routing algorithms and buffering techniques to fulfill the system requirements. This thesis highly contributes to the state-of-the-art of FPGA-based MPSoCs and NoCs. In the following, the three major contributions are introduced. As a first major contribution, a novel router concept is presented that efficiently utilizes communication times by performing sequences of arithmetic operations on the data that is transferred. The internal input buffers of the routers are exchanged with processing units that are capable of executing operations. Two different architectures of such processing units are presented. The first architecture provides multiply and accumulate operations which are often used in signal processing applications. The second architecture introduced as Application-Specific Instruction Set Routers (ASIRs) contains a processing unit capable of executing any operation and hence, it is not limited to multiply and accumulate operations. An internal processing core located in ASIRs can be developed in C/C++ using high-level synthesis. The second major contribution comprises application and performance explorations of the novel router concept. Models that approximate the achievable speedup and the end-to-end latency of ASIRs are derived and discussed to show the benefits in terms of performance. Furthermore, two applications using an ASIR-based MPSoC are implemented and evaluated on a Xilinx Zynq SoC. The first application is an image processing algorithm consisting of a Sobel filter, an RGB-to-Grayscale conversion, and a threshold operation. The second application is a system that helps visually impaired people by navigating them through unknown indoor environments. A Light Detection and Ranging (LIDAR) sensor scans the environment, while Inertial Measurement Units (IMUs) measure the orientation of the user to generate an audio signal that makes the distance as well as the orientation of obstacles audible. This application consists of multiple parallel tasks that are mapped to an ASIR-based MPSoC. Both applications show the performance advantages of ASIRs compared to a conventional NoC-based MPSoC. Furthermore, dynamic partial reconfiguration in terms of relocation and security aspects are investigated. The third major contribution refers to development and programming methodologies of NoC-based MPSoCs. A software-defined approach is presented that combines the design and programming of heterogeneous MPSoCs. In addition, a Kahn-Process-Network (KPN) –based model is designed to describe parallel applications for MPSoCs using ASIRs. The KPN-based model is extended to support not only the mapping of tasks to NoC-based MPSoCs but also the mapping to ASIR-based MPSoCs. A static mapping methodology is presented that assigns tasks to ASIRs and processors for a given KPN-model. The impact of external hardware components such as sensors, actuators and accelerators connected to the processors is also discussed which makes the approach of high interest for embedded systems

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

Reliability and Security Assessment of Modern Embedded Devices

L'abstract è presente nell'allegato / the abstract is in the attachmen

Remote dynamic partial reconfiguration: A threat to Internet-of-Things and embedded security applications

The advent of the Internet of Things has motivated the use of Field Programmable Gate Array (FPGA) devices with Dynamic Partial Reconfiguration (DPR) capabilities for dynamic non-invasive modifications to circuits implemented on the FPGA. In particular, the ability to perform DPR over the network is essential in the context of a growing number of Internet of Things (IoT)-based and embedded security applications. However, the use of remote DPR brings with it a number of security threats that could lead to potentially catastrophic consequences in practical scenarios. In this paper, we demonstrate four examples where the remote DPR capability of the FPGA may be exploited by an adversary to launch Hardware Trojan Horse (HTH) attacks on commonly used security applications. We substantiate the threat by demonstrating remotely-launched attacks on Xilinx FPGA-based hardware implementations of a cryptographic algorithm, a true random number generator, and two processor-based security applications - namely, a software implementation of a cryptographic algorithm and a cash dispensing scheme. The attacks are launched by on-the-fly transfer of malicious FPGA configuration bitstreams over an Ethernet connection to perform DPR and leak sensitive information. Finally, we comment on plausible countermeasures to prevent such attack

Remote dynamic partial reconfiguration: A threat to Internet-of-Things and embedded security applications

The advent of the Internet of Things has motivated the use of Field Programmable Gate Array (FPGA) devices with Dynamic Partial Reconfiguration (DPR) capabilities for dynamic non-invasive modifications to circuits implemented on the FPGA. In particular, the ability to perform DPR over the network is essential in the context of a growing number of Internet of Things (IoT)-based and embedded security applications. However, the use of remote DPR brings with it a number of security threats that could lead to potentially catastrophic consequences in practical scenarios. In this paper, we demonstrate four examples where the remote DPR capability of the FPGA may be exploited by an adversary to launch Hardware Trojan Horse (HTH) attacks on commonly used security applications. We substantiate the threat by demonstrating remotely-launched attacks on Xilinx FPGA-based hardware implementations of a cryptographic algorithm, a true random number generator, and two processor-based security applications - namely, a software implementation of a cryptographic algorithm and a cash dispensing scheme. The attacks are launched by on-the-fly transfer of malicious FPGA configuration bitstreams over an Ethernet connection to perform DPR and leak sensitive information. Finally, we comment on plausible countermeasures to prevent such attack

Ingress of threshold voltage-triggered hardware trojan in the modern FPGA fabric–detection methodology and mitigation

The ageing phenomenon of negative bias temperature instability (NBTI) continues to challenge the dynamic thermal management of modern FPGAs. Increased transistor density leads to thermal accumulation and propagates higher and non-uniform temperature variations across the FPGA. This aggravates the impact of NBTI on key PMOS transistor parameters such as threshold voltage and drain current. Where it ages the transistors, with a successive reduction in FPGA lifetime and reliability, it also challenges its security. The ingress of threshold voltage-triggered hardware Trojan, a stealthy and malicious electronic circuit, in the modern FPGA, is one such potential threat that could exploit NBTI and severely affect its performance. The development of an effective and efficient countermeasure against it is, therefore, highly critical. Accordingly, we present a comprehensive FPGA security scheme, comprising novel elements of hardware Trojan infection, detection, and mitigation, to protect FPGA applications against the hardware Trojan. Built around the threat model of a naval warship’s integrated self-protection system (ISPS), we propose a threshold voltage-triggered hardware Trojan that operates in a threshold voltage region of 0.45V to 0.998V, consuming ultra-low power (10.5nW), and remaining stealthy with an area overhead as low as 1.5% for a 28 nm technology node. The hardware Trojan detection sub-scheme provides a unique lightweight threshold voltage-aware sensor with a detection sensitivity of 0.251mV/nA. With fixed and dynamic ring oscillator-based sensor segments, the precise measurement of frequency and delay variations in response to shifts in the threshold voltage of a PMOS transistor is also proposed. Finally, the FPGA security scheme is reinforced with an online transistor dynamic scaling (OTDS) to mitigate the impact of hardware Trojan through run-time tolerant circuitry capable of identifying critical gates with worst-case drain current degradation

A survey on hardware-based malware detection approaches

This paper delves into the dynamic landscape of computer security, where malware poses a paramount threat. Our focus is a riveting exploration of the recent and promising hardware-based malware detection approaches. Leveraging hardware performance counters and machine learning prowess, hardware-based malware detection approaches bring forth compelling advantages such as real-time detection, resilience to code variations, minimal performance overhead, protection disablement fortitude, and cost-effectiveness. Navigating through a generic hardware-based detection framework, we meticulously analyze the approach, unraveling the most common methods, algorithms, tools, and datasets that shape its contours. This survey is not only a resource for seasoned experts but also an inviting starting point for those venturing into the field of malware detection. However, challenges emerge in detecting malware based on hardware events. We struggle with the imperative of accuracy improvements and strategies to address the remaining classification errors. The discussion extends to crafting mixed hardware and software approaches for collaborative efficacy, essential enhancements in hardware monitoring units, and a better understanding of the correlation between hardware events and malware applications

Built-In Return-Oriented Programs in Embedded Systems and Deep Learning for Hardware Trojan Detection

Microcontrollers and integrated circuits in general have become ubiquitous in the world today. All aspects of our lives depend on them from driving to work, to calling our friends, to checking our bank account balance. People who would do harm to individuals, corporations and nation states are aware of this and for that reason they seek to find or create and exploit vulnerabilities in integrated circuits. This dissertation contains three papers dealing with these types of vulnerabilities. The first paper talks about a vulnerability that was found on a microcontroller, which is a type of integrated circuit. The final two papers deal with hardware trojans. Hardware trojans are purposely added to the design of an integrated circuit in secret so that the manufacturer doesn’t know about it. They are used to damage the integrated circuit, leak confidential information, or in other ways alter the circuit. Hardware trojans are a major concern for anyone using integrated circuits because an attacker can alter a circuit in almost any way if they are successful in inserting one. A known method to prevent hardware trojan insertion is discussed and a type of circuit for which this method does not work is revealed. The discussion of hardware trojans is concluded with a new way to detect them before the integrated circuit is manufactured. Modern deep learning models are used to detect the portions of the hardware trojan called triggers that activate them