Towards a Secure and Reliable System

Abstract. In this article we describe a system based on a 32-bit processor, Leon, complete with security features offered by a specific cryptographic AES IP. Hardening is done not only on the principal hardware components but on the operating system as well, with attention for possible interaction between the different levels. The cryptographic IP is protected too to offer good resistance against, for example, fault-based attacks

A System-level Perspective Towards Efficient, Reliable and Secure Neural Network Computing

The Digital Era is now evolving into the Intelligence Era, driven overwhelmingly by the revolution of Deep Neural Network (DNN), which opens the door for intelligent data interpretation, turning the data and information into actions that create new capabilities, richer experiences, and unprecedented economic opportunities, achieving game-changing outcomes spanning from image recognition, natural language processing, self-driving cars to biomedical analysis. Moreover, the emergence of deep learning accelerators and neuromorphic computing further pushes DNN computation from cloud to the edge devices for the low-latency scalable on-device neural network computing. However, such promising embedded neural network computing systems are subject to various technical challenges. First, performing high-accurate inference for complex DNNs requires massive amounts of computation and memory resources, causing very limited energy efficiency for existing computing platforms. Even the brain-inspired spiking neuromorphic computing architecture which originates from the more bio-plausible spiking neural network (SNN) and relies on the occurrence frequency of a large number of electrical spikes to represent the data and perform the computation, is subject to significant limitations on both energy efficiency and processing speed. Second, although many memristor-based DNN accelerators and emerging neuromorphic accelerators have been proposed to improve the performance-per-watt of embedded DNN computing with the highly parallelizable Processing-in-Memory (PIM) architecture, one critical challenge faced by these memristor-based designs is their poor reliability. A DNN weight, which is represented as the memristance of a memristor cell, can be easily distorted by the inherent physical limitations of memristor devices, resulting in significant accuracy degradation. Third, DNN computing systems are also subject to ever-increasing security concerns. Attackers can easily fool a normally trained DNN model by exploiting the algorithmic vulnerabilities of DNN classifiers through adversary examples to mislead the inference results. Moreover, system vulnerabilities in open-sourced DNN computing frameworks such as heap overflow are increasingly exploited to either distort the inference accuracy or corrupt the learning environment. This dissertation focuses on designing efficient, reliable, and secured neural network computing systems. An architecture and algorithm co-design approach is presented to address the aforementioned design pillars from a system-level perspective, namely efficiency, reliability and security. Three case study examples centered around each design pillar, including Single-spike Neuromorphic Accelerator, Fault-tolerant DNN Accelerator, and Mal-DNN: Malicious DNN-powered Stegomalware, are discussed in this dissertation, offering the community an alternative thinking about developing more efficient, reliable and secure deep learning systems

A Survey of the Security Challenges and Requirements for IoT Operating Systems

The Internet of Things (IoT) is becoming an integral part of our modern lives as we converge towards a world surrounded by ubiquitous connectivity. The inherent complexity presented by the vast IoT ecosystem ends up in an insufficient understanding of individual system components and their interactions, leading to numerous security challenges. In order to create a secure IoT platform from the ground up, there is a need for a unifying operating system (OS) that can act as a cornerstone regulating the development of stable and secure solutions. In this paper, we present a classification of the security challenges stemming from the manifold aspects of IoT development. We also specify security requirements to direct the secure development of an unifying IoT OS to resolve many of those ensuing challenges. Survey of several modern IoT OSs confirm that while the developers of the OSs have taken many alternative approaches to implement security, we are far from engineering an adequately secure and unified architecture. More broadly, the study presented in this paper can help address the growing need for a secure and unified platform to base IoT development on and assure the safe, secure, and reliable operation of IoT in critical domains.Comment: 13 pages, 2 figure

Enabling digital grid for industrial revolution: self-healing cyber resilient platform

The key market objectives driving digital grid development are to provide sustainable, reliable and secure network systems that can support variety of applications against any potential cyber attacks. Therefore, there is an urgent demand to accelerate the development of intelligent Software-Defined Networking (SDN) platform that can address the tremendous challenges of data protection for digital resiliency. Modern grid technology tends to adopt distributed SDN controllers for further slicing power grid domain and protect the boundaries of electric data at network edges. To accommodate these issues, this article proposes an intelligent secure SDN controller for supporting digital grid resiliency, considering management coordination capability, to enable self-healing features and recovery of network traffic forwarding during service interruptions. A set of advanced features are employed in grid controllers to configure the network elements in response to possible disasters or link failures. In addition, various SDN topology scenarios are introduced for efficient coordination and configurations of network domains. Finally, to justify the potential advantages of intelligent secure SDN system, a case study is presented to evaluate the requirements of secure digital modern grid networks and pave the path towards the next phase of industry revolution

Secure Massive MIMO Transmission in the Presence of an Active Eavesdropper

In this paper, we investigate secure and reliable transmission strategies for multi-cell multi-user massive multiple-input multiple-output (MIMO) systems in the presence of an active eavesdropper. We consider a time-division duplex system where uplink training is required and an active eavesdropper can attack the training phase to cause pilot contamination at the transmitter. This forces the precoder used in the subsequent downlink transmission phase to implicitly beamform towards the eavesdropper, thus increasing its received signal power. We derive an asymptotic achievable secrecy rate for matched filter precoding and artificial noise (AN) generation at the transmitter when the number of transmit antennas goes to infinity. For the achievability scheme at hand, we obtain the optimal power allocation policy for the transmit signal and the AN in closed form. For the case of correlated fading channels, we show that the impact of the active eavesdropper can be completely removed if the transmit correlation matrices of the users and the eavesdropper are orthogonal. Inspired by this result, we propose a precoder null space design exploiting the low rank property of the transmit correlation matrices of massive MIMO channels, which can significantly degrade the eavesdropping capabilities of the active eavesdropper.Comment: To appear in ICC 1

The transition towards a sustainable energy system in Europe: What role can North Africa's solar resources play?

Securing energy supply and speeding up the transition towards a reliable, sustainable, low-carbon energy system are among the major current and future challenges facing Europe. Importing dispatchable solar electricity from North Africa is considered as a potential and attractive option. Nevertheless, as things currently stand, the European Commission focuses mainly on the exploitation of the existing wind power potential in the North Sea, largely ignoring the solar power potential in the Sahara region of North Africa. After discussing the major challenges and issues facing Europe to achieve the assigned ambitious objectives, the paper emphasises the importance of North Africa's solar resources in helping Europe to successfully address the challenge of decarbonising its electricity system, in particular with regards to the security of supply and sustainability. Within these two major challenges, the paper explores the issues of access, barriers and opportunities. The paper highlights why the EU’s energy and climate goals will not be achievable without adequate grid expansion and grid-scale energy storage facilities, as well as other innovative measures to manage demand and ensure a secure energy supply. In this respect, the paper shows how the import of dispatchable electricity from North Africa via specific HVDC links could play a key role in helping the EU achieve its energy targets in a cost effective way without recourse to significant investments in transmission infrastructure and storage facilities. The paper then attempts to identify and analyze the main barriers that continue to inhibit the export of solar electricity from North Africa to Europe. Finally, to make the project more attractive and achievable in the near future, the paper proposes a systematic approach for setting up energy import scenarios. A promising import scenario is presented where energy import via Italy is shown to be a more viable and effective solution than via Spain.Peer reviewe