Event-triggered state observers for sparse sensor noise/attacks

This paper describes two algorithms for state reconstruction from sensor measurements that are corrupted with sparse, but otherwise arbitrary, 'noise.' These results are motivated by the need to secure cyber-physical systems against a malicious adversary that can arbitrarily corrupt sensor measurements. The first algorithm reconstructs the state from a batch of sensor measurements while the second algorithm is able to incorporate new measurements as they become available, in the spirit of a Luenberger observer. A distinguishing point of these algorithms is the use of event-triggered techniques to improve the computational performance of the proposed algorithms

Two-Level Lattice Neural Network Architectures for Control of Nonlinear Systems

In this paper, we consider the problem of automatically designing a Rectified Linear Unit (ReLU) Neural Network (NN) architecture (number of layers and number of neurons per layer) with the guarantee that it is sufficiently parametrized to control a nonlinear system. Whereas current state-of-the-art techniques are based on hand-picked architectures or heuristic-based search to find such NN architectures, our approach exploits a given model of the system to design an architecture; as a result, we provide a guarantee that the resulting NN architecture is sufficient to implement a controller that satisfies an achievable specification. Our approach exploits two basic ideas. First, we assume that the system can be controlled by a Lipschitz-continuous state-feedback controller that is unknown but whose Lipschitz constant is upper-bounded by a known constant; then using this assumption, we bound the number of affine functions needed to construct a Continuous Piecewise Affine (CPWA) function that can approximate the unknown Lipschitz-continuous controller. Second, we utilize the authors' recent results on the Two-Level Lattice (TLL) NN architecture, a novel NN architecture that was shown to be parameterized directly by the number of affine functions that comprise the CPWA function it realizes. We also evaluate our method by designing a NN architecture to control an inverted pendulum

Securing state reconstruction under sensor and actuator attacks: Theory and design

This paper discusses the problem of reconstructing the state of a linear time invariant system when some of its actuators and sensors are compromised by an adversarial agent. In the model considered in this paper, the adversarial agent attacks an input (output) by manipulating its value arbitrarily, i.e., we impose no constraints (statistical or otherwise) on how control commands (sensor measurements) are changed by the adversary other than a bound on the number of attacked actuators and sensors In the first part of this paper, we introduce the notion of sparse strong observability and we show that is a necessary and sufficient condition for correctly reconstructing the state despite the considered attacks. In the second half of this work, we propose an observer to harness the complexity of this intrinsically combinatorial problem, by leveraging satisfiability modulo theory solving. Numerical simulations illustrate the effectiveness and scalability of our observer

Secure state estimation against sensor attacks in the presence of noise

We consider the problem of estimating the state of a noisy linear dynamical system when an unknown subset of sensors is arbitrarily corrupted by an adversary. We propose a secure state estimation algorithm, and derive (optimal) bounds on the achievable state estimation error given an upper bound on the number of attacked sensors. The proposed state estimator involves Kalman filters operating over subsets of sensors to search for a sensor subset which is reliable for state estimation. To further improve the subset search time, we propose Satisfiability Modulo Theory-based techniques to exploit the combinatorial nature of searching over sensor subsets. Finally, as a result of independent interest, we give a coding theoretic view of attack detection and state estimation against sensor attacks in a noiseless dynamical system

A Framework for Evaluating Security in the Presence of Signal Injection Attacks

Sensors are embedded in security-critical applications from medical devices to nuclear power plants, but their outputs can be spoofed through electromagnetic and other types of signals transmitted by attackers at a distance. To address the lack of a unifying framework for evaluating the effects of such transmissions, we introduce a system and threat model for signal injection attacks. We further define the concepts of existential, selective, and universal security, which address attacker goals from mere disruptions of the sensor readings to precise waveform injections. Moreover, we introduce an algorithm which allows circuit designers to concretely calculate the security level of real systems. Finally, we apply our definitions and algorithm in practice using measurements of injections against a smartphone microphone, and analyze the demodulation characteristics of commercial Analog-to-Digital Converters (ADCs). Overall, our work highlights the importance of evaluating the susceptibility of systems against signal injection attacks, and introduces both the terminology and the methodology to do so.Comment: This article is the extended technical report version of the paper presented at ESORICS 2019, 24th European Symposium on Research in Computer Security (ESORICS), Luxembourg, Luxembourg, September 201

Cloud-Based Quadratic Optimization with Partially Homomorphic Encryption

This article develops a cloud-based protocol for a constrained quadratic optimization problem involving multiple parties, each holding private data. The protocol is based on the projected gradient ascent on the Lagrange dual problem and exploits partially homomorphic encryption and secure communication techniques. Using formal cryptographic definitions of indistinguishability, the protocol is shown to achieve computational privacy. We show the implementation results of the protocol and discuss its computational and communication complexity. We conclude this article with a discussion on privacy notions

A review of decellularized stem cell matrix: a novel cell expansion system for cartilage tissue engineering

Cell-based therapy is a promising biological approach for the treatment of cartilage defects. Due to the small size of autologous cartilage samples available for cell transplantation in patients, cells need to be expanded to yield a sufficient cell number for cartilage repair. However, chondrocytes and adult stem cells tend to become replicatively senescent once they are expanded on conventional plastic flasks. Many studies demonstrate that the loss of cell properties is concomitant with the decreased cell proliferation capacity. This is a significant challenge for cartilage tissue engineering and regeneration. Despite much progress having been made in cell expansion, there are still concerns over expanded cell size and quality for cell transplantation applications. Recently, in vivo investigations in stem cell niches have suggested the importance of developing an in vitro stem cell microenvironment for cell expansion and tissue-specific differentiation. Our and other investigators’ work indicates that a decellularized stem cell matrix (DSCM) may provide such an expansion system to yield large-quantity and high-quality cells for cartilage tissue engineering and regeneration. This review briefly introduces key parameters in an in vivo stem cell niche and focuses on our recent work on DSCM for its rejuvenating or reprograming effect on various adult stem cells and chondrocytes. Since research in DSCM is still in its infancy, we are only able to discuss some potential mechanisms of DSCM on cell proliferation and chondrogenic potential. Further investigations of the underlying mechanism and in vivo regeneration capacity will allow this approach to be used in clinics

Memory CD8+ T Cells Are Required for Protection from Persistent Hepatitis C Virus Infection

Few hepatitis C virus (HCV) infections resolve spontaneously but those that do appear to afford protective immunity. Second infections are usually shorter in duration and are less likely to persist but mechanisms of virus control in immune individuals have not been identified. In this study we investigated whether memory helper and/or cytotoxic T lymphocytes provide protection in chimpanzees serially reinfected with the virus. Clearance of the first infection took 3–4 mo and coincided with the delayed onset of CD4+ and CD8+ T cell responses. High frequencies of memory T cells targeting multiple HCV proteins were stable over 7 yr of follow-up. Animals were infected for a second time to assess the protective role of memory T cells. In contrast to the prolonged course of the first infection, viremia was terminated within 14 d. Control of this second infection was kinetically linked to rapid acquisition of virus-specific cytolytic activity by liver resident CD8+ T cells and expansion of memory CD4+ and CD8+ T cells in blood. The importance of memory CD8+ T cells in control of HCV infection was confirmed by antibody-mediated depletion of this lymphocyte subset before a third infection. Virus replication was prolonged despite the presence of memory CD4+ T helper cells primed by the two prior infections and was not terminated until HCV-specific CD8+ T cells recovered in the liver. These experiments demonstrate an essential role for memory CD8+ T cells in long-term protection from chronic hepatitis C