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Security and Privacy Protection in visual sensor networks: A Survey

ACM COMPUTING SURVEYS 2014年第1期47卷 2-2页

作者： Winkler, Thomas Rinner, Bernhard Alpen Adria Univ Klagenfurt Inst Networked & Embedded Syst A-9020 Klagenfurt Austria Lakeside Labs A-9020 Klagenfurt Austria

visual sensor networks (VSNs) are receiving a lot of attention in research, and at the same time, commercial applications are starting to emerge. VSN devices come with image sensors, adequate processing power, and memory. They use wireless communication interfaces to collaborate and jointly solve tasks such as tracking persons within the network. VSNs are expected to replace not only many traditional, closed-circuit surveillance systems but also to enable emerging applications in scenarios such as elderly care, home monitoring, or entertainment. In all of these applications, VSNs monitor a potentially large group of people and record sensitive image data that might contain identities of persons, their behavior, interaction patterns, or personal preferences. These intimate details can be easily abused, for example, to derive personal profiles. The highly sensitive nature of images makes security and privacy in VSNs even more important than in most other sensor and data networks. However, the direct use of security techniques developed for related domains might be misleading due to the different requirements and design challenges. This is especially true for aspects such as data confidentiality and privacy protection against insiders, generating awareness among monitored people, and giving trustworthy feedback about recorded personal data-all of these aspects go beyond what is typically required in other applications. In this survey, we present an overview of the characteristics of VSN applications, the involved security threats and attack scenarios, and the major security challenges. A central contribution of this survey is our classification of VSN security aspects into data-centric, node-centric, network-centric, and user-centric security. We identify and discuss the individual security requirements and present a profound overview of related work for each class. We then discuss privacy protection techniques and identify recent trends in VSN security and privacy. A

关键词： Security Design Human Factors visual sensor networks privacy protection image sensor security

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Fast and accurate near-duplicate image elimination for visual sensor networks

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INTERNATIONAL JOURNAL OF DISTRIBUTED sensor networks 2017年第2期13卷 1-1页

作者： Zhou, Zhili Wu, Q. M. Jonathan Huang, Fang Sun, Xingming Nanjing Univ Informat Sci & Technol Jiangsu Engn Ctr Network Monitoring Nanjing Jiangsu Peoples R China Nanjing Univ Informat Sci & Technol Sch Comp & Software Nanjing Jiangsu Peoples R China Univ Windsor Dept Elect & Comp Engn 401 Sunset Ave Windsor ON N9B 3P4 Canada

Currently, a huge amount of visual data such as digital images and videos have been collected by visual sensor nodes, that is, camera nodes, and distributed on visual sensor networks. Among the visual data, there are a lot of near-duplicate images, which cause a serious waste of limited storage, computing, and transmission resources of visual sensor networks and a negative impact on users' experience. Thus, near-duplicate image elimination is urgently demanded. This article proposes a fast and accurate near-duplicate elimination approach for visual sensor networks. First, a coarse-to-fine clustering method based on a combination of global feature and local feature is proposed to cluster near-duplicate images. Then in each near-duplicate group, we adopt PageRank algorithm to analyze the contextual relevance among images to select and reserve seed image and remove the others. The experimental results prove that the proposed approach achieves better performances in the aspects of both efficiency and accuracy compared with the state-of-the-art approaches.

关键词： visual sensor networks Internet of Things near-duplicate image elimination image copy detection near-duplicate detection

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Collaborative Localization in visual sensor networks

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ACM TRANSACTIONS ON sensor networks 2014年第2期10卷 18-18页

作者： Karakaya, Mahmut Qi, Hairong Meliksah Univ Dept Elect & Elect Engn Talas Kayseri Turkey Univ Tennessee Dept Elect Engn & Comp Sci Knoxville TN USA

Collaboration in visual sensor networks is essential not only to compensate for the limitations of each sensor node but also to tolerate inaccurate information generated by faulty sensors. This article focuses on the design of a collaborative target localization algorithm that is resilient to sensor faults. We first develop a distributed solution to fault-tolerant target localization based on a so-called certainty map. To tolerate potential sensor faults, a voting mechanism is adopted and a threshold value needs to be specified which is the key to the realization of the distributed solution. Analytical study is conducted to derive the lower and upper bounds for the threshold such that the probability of faulty sensors negatively impacts the localization performance is less than a small value. Second, we focus on the detection and correction of one type of sensor faults, error in camera orientation. We construct a generative image model in each camera based on the detected target location to estimate camera's orientation, detect inaccuracies in camera orientations and correct them before they cascade. Based on results obtained from both simulation and real experiments, we show that the proposed method is effective in localization accuracy as well as fault detection and correction performance.

关键词： Algorithms Performance Theory Scene analysis sensor fusion target localization fault tolerance visual sensor networks

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Passivity-Based Cooperative Estimation for visual sensor networks: Averaging of Multiple Target Objects Poses

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SICE Journal of Control, Measurement, and System Integration 2011年第3期4卷 181-190页

作者： Takeshi Hatanaka Masayuki Fujita Department of Mechanical and Control Engineering Tokyo Institute of Technology

This paper presents a novel cooperative estimation algorithm for visual sensor networks. We consider the situation where multiple smart vision cameras with computation and communication capability see different target objects. The objective of the present algorithm is to meet two requirements: (i) gaining estimates close to an average pose for static objects and (ii) tracking of estimates to moving objects' poses. In order to meet the requirements simultaneously, we present a cooperative estimation algorithm based on passivity of the kinematic model of rigid body motion. Though the present algorithm embodies both properties from its structure, we restrict our theoretical interests to averaging and provide an upper bound of the ultimate error between the actual average and the estimates given by the present algorithm.

关键词： visual sensor networks cooperative estimation vision-based estimation averaging passivity

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Priority-based Routing Framework for Image Transmission in visual sensor networks: Experimental Analysis

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2020年第1期11卷 668-677页

作者： Felemban, Emad Naseer, Atif Amjad, Adil Umm Al Qura Univ Coll Comp & Informat Syst Mecca Saudi Arabia Umm Al Qura Univ Sci & Technol Unit Mecca Saudi Arabia

A visual sensor Network (VSN) is a specialized Wireless sensor Network (WSN) equipped with cameras. Its primary function is to capture images, videos and send them to power rich sink nodes for processing. As image data is much larger than scalar data sensed by a typical WSN, applications of VSN require much bigger amount of data to be transferred to the sink. Due to constraints of WSN such as low energy, limited CPU power and scarce memory, transmission of large amount of data becomes challenging. On the other hand, some VSN applications require critical image features sooner than the entire image to take action. In this paper, we provide the details of experiments done using our proposed Priority-based Routing Framework for Image Transmission (PRoFIT). PRoFIT is designed to deliver critical image features at high priority to the sink node for early processing. Peak signal-to-noise ratio (PSNR) analyses show that PRoFIT improves VSN application response time as compared to priority-less routing. This paper also contains the design of our VSN testbed. Multiple indoor and outdoor experiments were performed to validate the framework. This framework also improves the energy efficiency of the network. The results show that the PRoFIT is 40% efficient in terms of energy consumption.

关键词： Priority-based routing visual sensor networks test-bed framework

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Fast Sample Adaptive Offset Jointly Based on HOG Features and Depth Information for VVC in visual sensor networks

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sensorS 2020年第23期20卷 6754-6754页

作者： Wang, Ruyan Tang, Liuwei Tang, Tong Chongqing Univ Posts & Telecommun Sch Commun & Informat Engn Chongqing 400065 Peoples R China Key Lab Opt Commun & Networks Chongqing 400065 Peoples R China Key Lab Ubiquitous Sensing & Networking Chongqing 400065 Peoples R China

visual sensor networks (VSNs) can be widely used in multimedia, security monitoring, network camera, industrial detection, and other fields. However, with the development of new communication technology and the increase of the number of camera nodes in VSN, transmitting and compressing the huge amounts of video and image data generated by video and image sensors has become a major challenge. The next-generation video coding standard-versatile video coding (VVC), can effectively compress the visual data, but the higher compression rate is at the cost of heavy computational complexity. Therefore, it is vital to reduce the coding complexity for the VVC encoder to be used in VSNs. In this paper, we propose a sample adaptive offset (SAO) acceleration method by jointly considering the histogram of oriented gradient (HOG) features and the depth information for VVC, which reduces the computational complexity in VSNs. Specifically, first, the offset mode selection (select band offset (BO) mode or edge offset (EO) mode) is simplified by utilizing the partition depth of coding tree unit (CTU). Then, for EO mode, the directional pattern selection is simplified by using HOG features and support vector machine (SVM). Finally, experimental results show that the proposed method averagely saves 67.79% of SAO encoding time only with 0.52% BD-rate degradation compared to the state-of-the-art method in VVC reference software (VTM 5.0) for VSNs.

关键词： visual sensor networks versatile video coding sample adaptive offset edge offset depth

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A Generalized Threat Model for visual sensor networks

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sensorS 2020年第13期20卷 3629.-3629.页

作者： Simonjan, Jennifer Taurer, Sebastian Dieber, Bernhard Georgia Inst Technol Atlanta GA 30318 USA Joanneum Res A-9020 Klagenfurt Austria

Today, visual sensor networks (VSNs) are pervasively used in smart environments such as intelligent homes, industrial automation or surveillance. A major concern in the use of sensor networks in general is their reliability in the presence of security threats and cyberattacks. Compared to traditional networks, sensor networks typically face numerous additional vulnerabilities due to the dynamic and distributed network topology, the resource constrained nodes, the potentially large network scale and the lack of global network knowledge. These vulnerabilities allow attackers to launch more severe and complicated attacks. Since the state-of-the-art is lacking studies on vulnerabilities in VSNs, a thorough investigation of attacks that can be launched against VSNs is required. This paper presents a general threat model for the attack surfaces of visual sensor network applications and their components. The outlined threats are classified by the STRIDE taxonomy and their weaknesses are classified using CWE, a common taxonomy for security weaknesses.

关键词： visual sensor networks security threat model distributed systems

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Hierarchical Feature Scheme for Object Recognition in visual sensor networks

ELEKTROTEHNISKI VESTNIK-ELECTROCHEMICAL REVIEW

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ELEKTROTEHNISKI VESTNIK-ELECTROCHEMICAL REVIEW 2009年第1-2期76卷 38-44页

作者： Sulic, Vildana Pers, Janez Kristan, Matej Kovacic, Stanislav Univ Ljubljani Fak Elektrotehn Trzaska 25 Ljubljana 1000 Slovenia

visual sensor networks are the meeting point of two significantly different technologies: one is image processing with high computation and storage demands, and the other is distributed sensor approach with low power, low computational and storage capabilities. We propose a framework for hierarchical feature encoding scheme for a frequent computer vision task - object recognition. The key of our approach is the principle that individual nodes in the network hold only a small amount of information about objects seen by the network. However, this information is sufficient to efficiently route network query, when a new, unknown object is encountered. A set of criteria has to be fulfilled by the object recognition method to qualify for use in our framework. The paper provides examples of three widely known object recognition approaches that can be easily adapted for use in such hierarchical feature encoding scheme.

关键词： visual sensor networks computer vision object recognition

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Distributed Object Recognition in visual sensor networks

Distributed Object Recognition in Visual Sensor Networks

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IEEE International Conference on Communications

作者： Stefano Paris Alessandro Redondi Matteo Cesana Marco Tagliasacchi Mathematical and Algorithmic Sciences Lab France Research Center - Huawei Technologies Co. Ltd. LIPADE - Universite Paris Descartes Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano

ISBN: (纸本)9781467364300

This work focuses on visual sensor networks (VSNs) which perform visual analysis tasks such as object recognition. There, the goal is to find the image in a reference database which is the closest match to the image captured by camera sensor nodes. Recognition is performed by relying on visual features extracted from the acquired image, which are matched against a database of labeled features in order to find the closest image match. The matching functionalities are often implemented at a central controller outside the VSN. In contrast, we study the performance trade-offs involved in distributing the matching functionalities inside the VSN by letting sensor nodes performing parts of the matching process. We propose an optimization framework to optimally distribute the matching task to in-network sensor nodes with the goal of minimizing the overall completion time of the recognition task. The proposed optimization framework is then used to assess the performance of distributed matching, comparing it to a traditional, centralized approach in realistic VSN scenarios.

关键词： Cache Placement Object Recognition visual sensor networks

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Comparison of two paradigms for image analysis in visual sensor networks 13

Comparison of two paradigms for image analysis in visual sen...

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Proceedings of the 11th ACM Conference on Embedded Networked sensor Systems

作者： A. Canclini L. Baroffio M. Cesana A. Redondi M. Tagliasacchi Politecnico di Milano

This interactive demo presents and compares two different paradigms for image analysis in visual sensor networks (VSN), using a testbed based on battery-operated Beagle-Bone platforms with sight and wireless communica... 详细信息

ISBN: (纸本)9781450320276

关键词： visual features image analysis visual sensor networks

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