Cyber Security of Traffic Signal Control Systems with Connected Vehicles

Our world is becoming increasingly connected through smart technologies. The same trend is emerging in transportation systems, wherein connected vehicles (CVs) and transportation infrastructure are being connected through advanced wireless communication technologies. CVs have great potential to improve a variety of mobility applications, including traffic signal control (TSC), a critical component in urban traffic operations. CV-based TSC (CV-TSC) systems use trajectory data to make more informed control decisions, therefore can accommodate real-time traffic fluctuations more efficiently. However, vehicle-infrastructure connectivity opens new doors to potential cyber attacks. Malicious attackers can potentially send falsified trajectory data to CV-TSC systems and influence signal control decisions. The benefit of CV-TSC systems can be realized only if the systems are secure in cyberspace. Although many CV-TSC systems have been developed within the past decade, few consider cyber security in their system design. It remains unclear exactly how vulnerable CV-TSC systems are, how cyber attacks may be perpetrated, and how engineers can mitigate cyber attacks and protect CV-TSC systems. Therefore, this dissertation aims to systematically understand the cyber security problems facing CV-TSC systems under falsified data attacks and provide a countermeasure to safeguard CV-TSC systems. These objectives are accomplished through four studies. The first study evaluates the effects of falsified data attacks on TSC systems. Two TSC systems are considered: a conventional actuated TSC system and an adaptive CV-TSC system. Falsified data attacks are assumed to change the input data to these systems and therefore influence control decisions. Numerical examples show that both systems are vulnerable to falsified data attacks. The second study investigates how falsified data attacks may be perpetrated in a realistic setting. Different from prior research, this study considers a more realistic but challenging black-box attack scenario, in which the signal control model is unavailable to the attacker. Under this constraint, the attacker has to learn the signal control model using a surrogate model. The surrogate model predicts signal timing plans based on critical traffic features extracted from CV data. The attacker can generate falsified CV data (i.e., falsified vehicle trajectories) to alter the values of critical traffic features and thus influence signal control decisions. In the third study, a data-driven method is proposed to protect CV-TSC systems from falsified data attacks. Falsified trajectories are behaviorally distinct from normal trajectories because they must accomplish a certain attack goal; thus, the problem of identifying falsified trajectories is considered an abnormal trajectory identification problem. A trajectory-embedding model is developed to generate vector representations of trajectory data. The similarity (distance) between each pair of trajectories can be computed based on these vector representations. Hierarchical clustering is then applied to identify abnormal (i.e., falsified) trajectories. In the final study, a testing platform is built upon a virtual traffic simulator and real-world transportation infrastructure in Mcity. The testing platform integrates the attack study and defense study in a unified framework and is used to evaluate the real-world impact of cyber attacks on CV-TSC systems and the effectiveness of defense strategies.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162931/1/edhuang_1.pd

All-optical wavelength-tunable narrow-linewidth fiber laser

Parameter regulations of narrow-linewidth fiber lasers in frequency domain has drawn considerable interests for widespread applications in the light quantum computing, precise coherent detection, and generation of micro-waves. All-optical methods provide compact, precise and fast accesses to achieving these lasers with wavelength-tunability. Here, the optical-thermal effects of graphene is utilized to precisely control operations of free-running lasers with a tuning speed of 140 MHz/ms. Assisted by the single-longitude-mode operation and linewidth suppression of stimulated Brillouin backscattering, we obtain an optical-controllable ~750 Hz fiber laser with a wavelength-tuning range of 3.7 nm

Multiscale Mesh Deformation Component Analysis with Attention-based Autoencoders

Deformation component analysis is a fundamental problem in geometry processing and shape understanding. Existing approaches mainly extract deformation components in local regions at a similar scale while deformations of real-world objects are usually distributed in a multi-scale manner. In this paper, we propose a novel method to exact multiscale deformation components automatically with a stacked attention-based autoencoder. The attention mechanism is designed to learn to softly weight multi-scale deformation components in active deformation regions, and the stacked attention-based autoencoder is learned to represent the deformation components at different scales. Quantitative and qualitative evaluations show that our method outperforms state-of-the-art methods. Furthermore, with the multiscale deformation components extracted by our method, the user can edit shapes in a coarse-to-fine fashion which facilitates effective modeling of new shapes.Comment: 15 page

Towards Bridging the Gap between Control and Self-Adaptive System Properties

Two of the main paradigms used to build adaptive software employ different types of properties to capture relevant aspects of the system's run-time behavior. On the one hand, control systems consider properties that concern static aspects like stability, as well as dynamic properties that capture the transient evolution of variables such as settling time. On the other hand, self-adaptive systems consider mostly non-functional properties that capture concerns such as performance, reliability, and cost. In general, it is not easy to reconcile these two types of properties or identify under which conditions they constitute a good fit to provide run-time guarantees. There is a need of identifying the key properties in the areas of control and self-adaptation, as well as of characterizing and mapping them to better understand how they relate and possibly complement each other. In this paper, we take a first step to tackle this problem by: (1) identifying a set of key properties in control theory, (2) illustrating the formalization of some of these properties employing temporal logic languages commonly used to engineer self-adaptive software systems, and (3) illustrating how to map key properties that characterize self-adaptive software systems into control properties, leveraging their formalization in temporal logics. We illustrate the different steps of the mapping on an exemplar case in the cloud computing domain and conclude with identifying open challenges in the area

Ginseng and Anticancer Drug Combination to Improve Cancer Chemotherapy: A Critical Review

Ginseng, a well-known herb, is often used in combination with anticancer drugs to enhance chemotherapy. Its wide usage as well as many documentations are often cited to support its clinical benefit of such combination therapy. However the literature based on objective evidence to make such recommendation is still lacking. The present review critically evaluated relevant studies reported in English and Chinese literature on such combination. Based on our review, we found good evidence from in vitro and in vivo animal studies showing enhanced antitumor effect when ginseng is used in combination with some anticancer drugs. However, there is insufficient clinical evidence of such benefit as very few clinical studies are available. Future research should focus on clinically relevant studies of such combination to validate the utility of ginseng in cancer

Defining security requirements through misuse actions

An important aspect of security requirements is the understanding and listing of the possible threats to the system. Only then can we decide what specific defense mechanisms to use. We show here an approach to list all threats by considering each action in each use case and analyzing how it can be subverted by an internal or external attacker. From this list we can deduce what policies are necessary to prevent or mitigate the threats. These policies can then be used as guidelines for design. The proposed method can include formal design notations for validation and verification.1st International Workshop on Advanced Software Engineering: Expanding the Frontiers of Software Technology - Session 3: Software Development ProcessRed de Universidades con Carreras en Informática (RedUNCI

Experimental realization of a highly secure chaos communication under strong channel noise

A one-way coupled spatiotemporally chaotic map lattice is used to contruct cryptosystem. With the combinatorial applications of both chaotic computations and conventional algebraic operations, our system has optimal cryptographic properties much better than the separative applications of known chaotic and conventional methods. We have realized experiments to pratice duplex voice secure communications in realistic Wired Public Switched Telephone Network by applying our chaotic system and the system of Advanced Encryption Standard (AES), respectively, for cryptography. Our system can work stably against strong channel noise when AES fails to work.Comment: 15 pages, 5 figure