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arXiv 2017年

作者： Hosseini, Hossein Xiao, Baicen Clark, Andrew Poovendran, Radha Department of Electrical Engineering University of Washington SeattleWA United States Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA United States

Due to the growth of video data on Internet, automatic video analysis has gained a lot of attention from academia as well as companies such as Facebook, Twitter and Google. In this paper, we examine the robustness of video analysis algorithms in adversarial settings. Specifically, we propose targeted attacks on two fundamental classes of video analysis algorithms, namely video classification and shot detection. We show that an adversary can subtly manipulate a video in such a way that a human observer would perceive the content of the original video, but the video analysis algorithm will return the adversary's desired outputs. We then apply the attacks on the recently released Google Cloud Video Intelligence API. The API takes a video file and returns the video labels (objects within the video), shot changes (scene changes within the video) and shot labels (description of video events over time). Through experiments, we show that the API generates video and shot labels by processing only the first frame of every second of the video. Hence, an adversary can deceive the API to output only her desired video and shot labels by periodically inserting an image into the video at the rate of one frame per second. We also show that the pattern of shot changes returned by the API can be mostly recovered by an algorithm that compares the histograms of consecutive frames. Based on our equivalent model, we develop a method for slightly modifying the video frames, in order to deceive the API into generating our desired pattern of shot changes. We perform extensive experiments with different videos and show that our attacks are consistently successful across videos with different characteristics. At the end, we propose introducing randomness to video analysis algorithms as a countermeasure to our attacks. Copyright © 2017, The Authors. All rights reserved.

关键词： Machine learning

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Minimal Input Selection for Robust Control

arXiv

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arXiv 2017年

作者： Liu, Zhipeng Long, Yao Clark, Andrew Lee, Phillip Bushnell, Linda Kirschen, Daniel Poovendran, Radha Department of Electrical Engineering University of Washington SeattleWA98195 United States Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

This paper studies the problem of selecting a minimum-size set of input nodes to guarantee stability of a networked system in the presence of uncertainties and time delays. Current approaches to input selection in networked dynamical systems focus on nominal systems with known parameter values in the absence of delays. We derive sufficient conditions for existence of a stabilizing controller for an uncertain system that are based on a subset of system modes lying within the controllability subspace induced by the set of inputs. We then formulate the minimum input selection problem and prove that it is equivalent to a discrete optimization problem with bounded submodularity ratio, leading to polynomial-time algorithms with provable optimality bounds. We show that our approach is applicable to different types of uncertainties, including additive and multiplicative uncertainties in the system matrices as well as uncertain time delays. We demonstrate our approach in a numerical case study on the IEEE 39-bus test power system. Copyright © 2017, The Authors. All rights reserved.

关键词： Robust control

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Cloaking the clock: Emulating clock skew in controller area networks

arXiv

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arXiv 2017年

作者： Sagong, Sang Uk Ying, Xuhang Clark, Andrew Bushnell, Linda Poovendran, Radha Department of Electrical Engineering University of Washington SeattleWA98195 United States Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

Automobiles are equipped with Electronic Control Units $ECU$ that communicate via in-vehicle network protocol standards such as Controller Area Network $CAN$. These protocols are designed under the assumption that separating in-vehicle communications from external networks is sufficient for protection against cyber attacks. This assumption, however, has been shown to be invalid by recent attacks in which adversaries were able to infiltrate the in-vehicle network. Motivated by these attacks, intrusion detection systems $IDSs$ have been proposed for in-vehicle networks that attempt to detect attacks by making use of device fingerprinting using properties such as clock skew of an ECU. In this paper, we propose the cloaking attack, an intelligent masquerade attack in which an adversary modifies the timing of transmitted messages in order to match the clock skew of a targeted ECU. The attack leverages the fact that, while the clock skew is a physical property of each ECU that cannot be changed by the adversary, the estimation of the clock skew by other ECUs is based on network traffic, which, being a cyber component only, can be modified by an adversary. We implement the proposed cloaking attack and test it on two IDSs, namely, the current state-of-the-art IDS and a new IDS that we develop based on the widely-used Network Time Protocol $NTP$. We implement the cloaking attack on two hardware testbeds, a prototype and a real connected vehicle, and show that it can always deceive both IDSs. We also introduce a new metric called the Maximum Slackness Index to quantify the effectiveness of the cloaking attack even when the adversary is unable to precisely match the clock skew of the targeted *** Codes 68W01 Copyright © 2017, The Authors. All rights reserved.

关键词： Control system synthesis

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A Submodular Optimization Approach to Leader-Follower Consensus in Networks with Negative Edges

A Submodular Optimization Approach to Leader-Follower Consen...

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American Control Conference

作者： Andrew Clark Qiqiang Hou Linda Bushnell Radha Poovendran Department of Electrical and Computer Engineering Worcester Polytechnic Institute MA 01609 USA Department of Electrical Engineering University of Washington Seattle 98195 USA

ISBN: (纸本)9781509045839

Networked systems often contain both positive and negative interactions between nodes, with the latter often represented as negative edge weights in a graph. Such negative edges may prevent a network from performing cooperative tasks such as achieving consensus, creating a need for new control-theoretic techniques that guarantee performance in the presence of negative edges. This paper considers the problem of selecting leader nodes to maintain a fixed state in order to steer the remaining nodes to a desired state value in networks with negative edges. We present two sufficient conditions that are equivalent to submodular constraints on the set of leader nodes. The first constraint is based on the graph spectrum, while the second is formulated in terms of the determinant of the Laplacian matrix. We prove that both conditions can be formulated as submodular constraints on the set of leader nodes, leading to polynomial-time algorithms with provable approximation guarantees for selecting a minimum-size set of leader nodes to satisfy these conditions. Furthermore, we introduce necessary conditions for consensus and prove that a set of leader nodes satisfying these conditions can be selected in polynomial time. We characterize the requirements for leader selection in order to ensure consensus in line networks. The results are illustrated through numerical study.

关键词： Ganglia Negative solidification line network Network Polynomial time edges

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An Automatic Assessment System of Diabetic Foot Ulcers Based on Wound Area Determination, Color Segmentation, and Healing Score Evaluation

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Journal of Diabetes Science and Technology 2016年第2期10卷 421-428页

作者： Wang, Lei Pedersen, Peder C. Strong, Diane M. Tulu, Bengisu Agu, Emmanuel Ignotz, Ron He, Qian Electrical and Computer Engineering Department Worcester Polytechnic Institute 100 Institute Rd Worcester 01609 MA United States School of Business Worcester Polytechnic Institute Worcester MA United States Computer Science Department Worcester Polytechnic Institute Worcester MA United States Plastic Surgery Department UMASS Medical School Worcester MA United States

Background: For individuals with type 2 diabetes, foot ulcers represent a significant health issue. The aim of this study is to design and evaluate a wound assessment system to help wound clinics assess patients with foot ulcers in a way that complements their current visual examination and manual measurements of their foot ulcers. Methods: The physical components of the system consist of an image capture box, a smartphone for wound image capture and a laptop for analyzing the wound image. The wound image assessment algorithms calculate the overall wound area, color segmented wound areas, and a healing score, to provide a quantitative assessment of the wound healing status both for a single wound image and comparisons of subsequent images to an initial wound image. Results: The system was evaluated by assessing foot ulcers for 12 patients in the Wound Clinic at University of Massachusetts Medical School. As performance measures, the Matthews correlation coefficient (MCC) value for the wound area determination algorithm tested on 32 foot ulcer images was.68. The clinical validity of our healing score algorithm relative to the experienced clinicians was measured by Krippendorff's alpha coefficient (KAC) and ranged from.42 to.81. Conclusion: Our system provides a promising real-time method for wound assessment based on image analysis. Clinical comparisons indicate that the optimized mean-shift-based algorithm is well suited for wound area determination. Clinical evaluation of our healing score algorithm shows its potential to provide clinicians with a quantitative method for evaluating wound healing status. © 2015 Diabetes Technology Society.

关键词： clinical validation of wound assessment diabetic foot ulcer healing score tele-medicine wound image analysis

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Multi-objective reinforcement learning-based deep neural networks for cognitive space communications

Multi-objective reinforcement learning-based deep neural net...

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Cognitive Communications for Aerospace Applications Workshop (CCAA)

作者： Paulo Victor R. Ferreira Randy Paffenroth Alexander M. Wyglinski Timothy M. Hackett Sven G. Bilén Richard C. Reinhart Dale J. Mortensen Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA USA Department of Mathematical Sciences Worcester Polytechnic Institute Worcester MA USA School of Electrical Engineering and Computer Science The Pennsylvania State University University Park PA USA Space Communications and Navigation NASA John H. Glenn Research Center Cleveland OH USA

ISBN: (纸本)9781538639894

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through `virtual environment exploration'. Improvements in the multi-objective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located on-board the International Space Station.

关键词： Artificial neural networks Learning (artificial intelligence) Space communications NASA Resource management Prediction algorithms

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Network Topology Mapping from Partial Virtual Coordinates and Graph Geodesics

arXiv

引用

arXiv 2017年

作者： Jayasumana, Anura P. Paffenroth, Randy Ramasamy, Sridhar Department of Electrical & Computer Engineering Colorado State University Fort CollinsCO80525 Department of Mathematical Sciences Department of Computer Science Data Science Program Worcester Polytechnic Institute WorcesterMA01609

For many important network types (e.g., sensor networks in complex harsh environments and social networks) physical coordinate systems (e.g., Cartesian), and physical distances (e.g., Euclidean), are either difficult to discern or inappropriate. Accordingly, Topology Preserving Maps (TPMs) derived from a Virtual-Coordinate (VC) system representing the distance to a small set of anchors is an attractive alternative to physical coordinates for many network algorithms. Herein, we present an approach, based on the theory of low-rank matrix completion, to recover geometric properties of a network with only partial information about the VCs of nodes. In particular, our approach is a combination of geodesic recovery concepts and low-rank matrix completion, generalized to the case of hop-distances in graphs. Distortion evaluated using the change of distance among node pairs shows that even with up to 40% to 60% of random coordinates missing, accurate TPMs can be obtained. TPM generation can now also be based on different context appropriate VC systems or measurements as long as they characterize each node with distances to a small set of random nodes (instead of a global set of anchors). The proposed method is a significant generalization that allows the topology to be extracted from a random set of graph geodesics, making it applicable in contexts such as social networks where VC generation may not be *** Codes 15A83 Copyright © 2017, The Authors. All rights reserved.

关键词： Sensor networks

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Implementation of a space communications cognitive engine

Implementation of a space communications cognitive engine

引用

Cognitive Communications for Aerospace Applications Workshop (CCAA)

作者： Timothy M. Hackett Sven G. Bilén Paulo Victor R. Ferreira Alexander M. Wyglinski Richard C. Reinhart School of Electrical Engineering and Computer Science University Park Pennsylvania Department of Electrical Engineering & Computer Engineering Worcester Polytechnic Institute Worcester MA USA NASA John H. Glenn Research Center Cleveland Ohio

ISBN: (纸本)9781538639894

Although communications-based cognitive engines have been proposed, very few have been implemented in a full system, especially in a space communications system. In this paper, we detail the implementation of a multi-objective reinforcement-learning algorithm and deep artificial neural networks for the use as a radio-resource-allocation controller. The modular software architecture presented encourages re-use and easy modification for trying different algorithms. Various trade studies involved with the system implementation and integration are discussed. These include the choice of software libraries that provide platform flexibility and promote reusability, choices regarding the deployment of this cognitive engine within a system architecture using the DVB-S2 standard and commercial hardware, and constraints placed on the cognitive engine caused by real-world radio constraints. The implemented radio-resource-allocation-management controller was then integrated with the larger space-ground system developed by NASA Glenn Research Center (GRC).

关键词： Engines Licenses Artificial neural networks NASA Software libraries Space vehicles

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Development of a tele-nursing mobile manipulator for remote care-giving in quarantine areas

Development of a tele-nursing mobile manipulator for remote ...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Zhi Li Peter Moran Qingyuan Dong Ryan J. Shaw Kris Hauser Department of Mechanical Engineering Worcester Polytechnic Institute Worcester MA USA Department of Electrical and Computer Engineering Duke University Durham NC USA School of Nursing Duke University Durham NC USA

During outbreaks of contagious diseases, healthcare workers are at high risk for infection due to routine interaction with patients, handling of contaminated materials, and challenges associated with safely removing protective gear. This poses an opportunity for the use of remote-controlled robots that could perform common nursing duties inside hazardous clinical areas, thereby minimizing the exposure of healthcare workers to contagions and other biohazards. This paper describes the development of the prototype system Tele-Robotic Intelligent Nursing Assistant (TRINA), which consists of a mobile manipulator robot, a human operator's console, and operator assistance algorithms which automate or partially-automate tedious and error-prone tasks. Using off-the-shelf robotic and sensing components, total hardware costs are kept under $75,000. The system's capabilities for performing standard nursing tasks are evaluated in the simulation laboratory of a nursing school.

关键词： Medical services Robot sensing systems Robot kinematics Collision avoidance Mobile communication Manipulators

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Revealing and Detecting Malicious Retweeter Groups

Revealing and Detecting Malicious Retweeter Groups

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International Conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Nguyen Vo Kyumin Lee Cheng Cao Thanh Tran Hongkyu Choi Department of Computer Science Utah State University Logan UT USA Department of Computer Science Worcester Polytechnic Institute Worcester MA USA Department of Computer Science and Engineering Texas A&M University College Station TX USA

ISBN: (数字)9781450349932

ISBN: (纸本)9781450349932

Retweeting/sharing action has enabled information to be cascaded to distant nodes on social network. Unfortunately, malicious users as a group have taken advantage of the retweeting function with coordinated behavior to falsely distort the volume of specific keywords, topics or URLs for promotional purposes (e.g., spreading fake news, and increasing public visibility of products or services). Unfortunately, little is known about their retweeting behavior as a group and how to detect them based on group-based signals. To fill the gap, in this paper, we (i) propose Attractor+ algorithm to extract retweeter groups, members of each of which have similar retweeting behavior; (ii) analyze underlying characteristics of malicious and legitimate retweeter groups; (iii) propose group-based features to catch synchronized and coordinated behavior; and build a predictor to classify if a group is malicious. Experimental results show that our proposed method outperformed existing approaches.

关键词： Feature extraction Synchronization Heuristic algorithms Standards computer science Twitter

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