Secure Virtualization and Multicore Platforms State-of-the-Art report

SVaM

Securing Real-Time Internet-of-Things

Modern embedded and cyber-physical systems are ubiquitous. A large number of critical cyber-physical systems have real-time requirements (e.g., avionics, automobiles, power grids, manufacturing systems, industrial control systems, etc.). Recent developments and new functionality requires real-time embedded devices to be connected to the Internet. This gives rise to the real-time Internet-of-things (RT-IoT) that promises a better user experience through stronger connectivity and efficient use of next-generation embedded devices. However RT- IoT are also increasingly becoming targets for cyber-attacks which is exacerbated by this increased connectivity. This paper gives an introduction to RT-IoT systems, an outlook of current approaches and possible research challenges towards secure RT- IoT frameworks

Thin Hypervisor-Based Security Architectures for Embedded Platforms

Virtualization has grown increasingly popular, thanks to its benefits of isolation, management, and utilization, supported by hardware advances. It is also receiving attention for its potential to support security, through hypervisor-based services and advanced protections supplied to guests. Today, virtualization is even making inroads in the embedded space, and embedded systems, with their security needs, have already started to benefit from virtualization’s security potential. In this thesis, we investigate the possibilities for thin hypervisor-based security on embedded platforms. In addition to significant background study, we present implementation of a low-footprint, thin hypervisor capable of providing security protections to a single FreeRTOS guest kernel on ARM. Backed by performance test results, our hypervisor provides security to a formerly unsecured kernel with minimal performance overhead, and represents a first step in a greater research effort into the security advantages and possibilities of embedded thin hypervisors. Our results show that thin hypervisors are both possible and beneficial even on limited embedded systems, and sets the stage for more advanced investigations, implementations, and security applications in the future

Architecting a One-to-many Traffic-Aware and Secure Millimeter-Wave Wireless Network-in-Package Interconnect for Multichip Systems

With the aggressive scaling of device geometries, the yield of complex Multi Core Single Chip(MCSC) systems with many cores will decrease due to the higher probability of manufacturing defects especially, in dies with a large area. Disintegration of large System-on-Chips(SoCs) into smaller chips called chiplets has shown to improve the yield and cost of complex systems. Therefore, platform-based computing modules such as embedded systems and micro-servers have already adopted Multi Core Multi Chip (MCMC) architectures overMCSC architectures. Due to the scaling of memory intensive parallel applications in such systems, data is more likely to be shared among various cores residing in different chips resulting in a significant increase in chip-to-chip traffic, especially one-to-many traffic. This one-to-many traffic is originated mainly to maintain cache-coherence between many cores residing in multiple chips. Besides, one-to-many traffics are also exploited by many parallel programming models, system-level synchronization mechanisms, and control signals. How-ever, state-of-the-art Network-on-Chip (NoC)-based wired interconnection architectures do not provide enough support as they handle such one-to-many traffic as multiple unicast trafficusing a multi-hop MCMC communication fabric. As a result, even a small portion of such one-to-many traffic can significantly reduce system performance as traditional NoC-basedinterconnect cannot mask the high latency and energy consumption caused by chip-to-chipwired I/Os. Moreover, with the increase in memory intensive applications and scaling of MCMC systems, traditional NoC-based wired interconnects fail to provide a scalable inter-connection solution required to support the increased cache-coherence and synchronization generated one-to-many traffic in future MCMC-based High-Performance Computing (HPC) nodes. Therefore, these computation and memory intensive MCMC systems need an energy-efficient, low latency, and scalable one-to-many (broadcast/multicast) traffic-aware interconnection infrastructure to ensure high-performance. Research in recent years has shown that Wireless Network-in-Package (WiNiP) architectures with CMOS compatible Millimeter-Wave (mm-wave) transceivers can provide a scalable, low latency, and energy-efficient interconnect solution for on and off-chip communication. In this dissertation, a one-to-many traffic-aware WiNiP interconnection architecture with a starvation-free hybrid Medium Access Control (MAC), an asymmetric topology, and a novel flow control has been proposed. The different components of the proposed architecture are individually one-to-many traffic-aware and as a system, they collaborate with each other to provide required support for one-to-many traffic communication in a MCMC environment. It has been shown that such interconnection architecture can reduce energy consumption and average packet latency by 46.96% and 47.08% respectively for MCMC systems. Despite providing performance enhancements, wireless channel, being an unguided medium, is vulnerable to various security attacks such as jamming induced Denial-of-Service (DoS), eavesdropping, and spoofing. Further, to minimize the time-to-market and design costs, modern SoCs often use Third Party IPs (3PIPs) from untrusted organizations. An adversary either at the foundry or at the 3PIP design house can introduce a malicious circuitry, to jeopardize an SoC. Such malicious circuitry is known as a Hardware Trojan (HT). An HTplanted in the WiNiP from a vulnerable design or manufacturing process can compromise a Wireless Interface (WI) to enable illegitimate transmission through the infected WI resulting in a potential DoS attack for other WIs in the MCMC system. Moreover, HTs can be used for various other malicious purposes, including battery exhaustion, functionality subversion, and information leakage. This information when leaked to a malicious external attackercan reveals important information regarding the application suites running on the system, thereby compromising the user profile. To address persistent jamming-based DoS attack in WiNiP, in this dissertation, a secure WiNiP interconnection architecture for MCMC systems has been proposed that re-uses the one-to-many traffic-aware MAC and existing Design for Testability (DFT) hardware along with Machine Learning (ML) approach. Furthermore, a novel Simulated Annealing (SA)-based routing obfuscation mechanism was also proposed toprotect against an HT-assisted novel traffic analysis attack. Simulation results show that,the ML classifiers can achieve an accuracy of 99.87% for DoS attack detection while SA-basedrouting obfuscation could reduce application detection accuracy to only 15% for HT-assistedtraffic analysis attack and hence, secure the WiNiP fabric from age-old and emerging attacks

Design of secure and trustworthy system-on-chip architectures using hardware-based root-of-trust techniques

Cyber-security is now a critical concern in a wide range of embedded computing modules, communications systems, and connected devices. These devices are used in medical electronics, automotive systems, power grid systems, robotics, and avionics. The general consensus today is that conventional approaches and software-only schemes are not sufficient to provide desired security protections and trustworthiness. Comprehensive hardware-software security solutions so far have remained elusive. One major challenge is that in current system-on-chip (SoCs) designs, processing elements (PEs) and executable codes with varying levels of trust, are all integrated on the same computing platform to share resources. This interdependency of modules creates a fertile attack ground and represents the Achilles’ heel of heterogeneous SoC architectures. The salient research question addressed in this dissertation is “can one design a secure computer system out of non-secure or untrusted computing IP components and cores?”. In response to this question, we establish a generalized, user/designer-centric set of design principles which intend to advance the construction of secure heterogeneous multi-core computing systems. We develop algorithms, models of computation, and hardware security primitives to integrate secure and non-secure processing elements into the same chip design while aiming for: (a) maintaining individual core’s security; (b) preventing data leakage and corruption; (c) promoting data and resource sharing among the cores; and (d) tolerating malicious behaviors from untrusted processing elements and software applications. The key contributions of this thesis are: 1. The introduction of a new architectural model for integrating processing elements with different security and trust levels, i.e., secure and non-secure cores with trusted and untrusted provenances; 2. A generalized process isolation design methodology for the new architecture model that covers both the software and hardware layers to (i) create hardware-assisted virtual logical zones, and (ii) perform both static and runtime security, privilege level and trust authentication checks; 3. A set of secure protocols and hardware root-of-trust (RoT) primitives to support the process isolation design and to provide the following functionalities: (i) hardware immutable identities – using physical unclonable functions, (ii) core hijacking and impersonation resistance – through a blind signature scheme, (iii) threshold-based data access control – with a robust and adaptive secure secret sharing algorithm, (iv) privacy-preserving authorization verification – by proposing a group anonymous authentication algorithm, and (v) denial of resource or denial of service attack avoidance – by developing an interconnect network routing algorithm and a memory access mechanism according to user-defined security policies. 4. An evaluation of the security of the proposed hardware primitives in the post-quantum era, and possible extensions and algorithmic modifications for their post-quantum resistance. In this dissertation, we advance the practicality of secure-by-construction methodologies in SoC architecture design. The methodology allows for the use of unsecured or untrusted processing elements in the construction of these secure architectures and tries to extend their effectiveness into the post-quantum computing era

Language run-time systems:An overview

The proliferation of high-level programming languages with advanced language features and the need for portability across increasingly heterogeneous and hierarchical architectures require a sophisticated run-time system to manage program execution and available resources. Additional benefits include isolated execution of untrusted code and the potential for dynamic optimisation, among others. This paper provides a high-level overview of language run-time systems with a focus on execution models, support for concurrency and parallelism, memory management, and communication, whilst briefly mentioning synchronisation, monitoring, and adaptive policy control. Two alternative approaches to run-time system design are presented and several challenges for future research are outlined. References to both seminal and recent work are provided

Efficient Learning in Heterogeneous Internet of Things Ecosystems

The Internet of Things (IoT) is a growing network of heterogeneous devices, combining various sensing and computing nodes at different scales, which creates a large volume of data. Many IoT applications use machine learning (ML) algorithms to analyze the data. The high computational complexity of ML workloads poses significant computational challenges to IoT computing platforms, which tend to be less-powerful and resource-constrained devices. Transmitting such large volumes of data to the cloud also have various issues such as scalability, security and privacy. In this dissertation, we propose efficient solutions to perform the ML tasks while decreasing power consumption and improving performance. We first leverage the heterogeneous and interconnected nature of the IoT systems, where IoT applications run on many different architectures (e.g., X86 server or ARM-based edge device) while communicating with each other. We present a cross-platform power and performance prediction technique for intelligent task allocation. The proposed technique estimates the time-variant energy consumption with only 7% error across completely different architectures, enabling the intelligent task allocation that saves the energy consumption of 16.5% for state-of-the-art ML workloads.We next show how to further advance the learning procedures towards real-time and online processing by distributing such learning tasks onto the hierarchy of IoT devices. Our solution leverages brain-inspired high-dimensional (HD) computing to derive a new class oflearning algorithms that can easily run on IoT devices, while providing high accuracy comparable to the state-of-the-arts. We present that the HD-based learning algorithms can cover various real-world problems from conventional classification to other cognitive tasks beyond classical MLs such as DNA pattern matching. We demonstrate that the HD-based learning can enable secure, collaborative learning by efficiently distributing a large volume of learning tasks into heterogeneous computing nodes. We have implemented the proposed learning solution on various platforms while offering superior computing efficiency. For example, our solution achieves 486×and 7× performance improvements for each of the training and inference phases on a low-power ARM processor, as compared to state-of-the-art deep learning