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Cluster-Aware Kronecker Supported Data Collection for Sensory Data

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Cluster-Aware Kronecker Supported Data Collection for Sensor...

International Conference on computer Communications and Networks (ICCCN)

作者： Siguang Chen Zhihao Wang Kewei Sha Jiangsu Engineering Research Center of Communication and Network Technology Nanjing University of Posts and Telecommunications Nanjing China Department of Computer Science & Cyber Security Institute University of Houston-Clear Lake Houston TX

Although current proposed compression schemes achieve a better performance compared with traditional data compression schemes, they have not fully exploited the spatial and temporal correlations among the data. Well-designed clustering algorithms are needed to explore strong spatial correlation. In this paper, we propose a k-means based Kronecker supported two-dimensional (spatio-temporal) compression scheme to achieve better compression results. Our scheme first leverages a k-means based clustering algorithm that explores the spatial correlation among sensory data. Then it develops a novel two-dimensional data compression mechanism, which can recover the original data from the compressed data with a high precision. Simulation results show that our proposed scheme is energy-efficient and can achieve better clustering results and recovery performance compared with other schemes for sensory data.

关键词： Correlation Clustering algorithms Data compression Wireless sensor networks Sparse matrices Sensors Spatial databases

Contract-Based Content Delivery in 5G Converged Networks

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China Communications 2017年第12期14卷 120-133页

作者： Xiaoyuan Lu Yiqing Li Xiaoying Gan Yanwei Xu Jun Yao School of Computer Science Fudan University Shanghai China Dept. of Electronics Engineering Shanghai Jiao Tong University Shanghai 200240 China Engineering Research Center of Cyber Security Auditing and Monitoring Ministry of Education China Shanghai Engineering Research Center for Broadband Technologies & Applications China Philips Lighting Research China

Mobile broadcasting services provided by converged networks do aid in satisfying users' demands for popular multimedia content while unicasting services offer personalized experiences for *** analyze hybrid broadcasting unicasting framework from the perspective of network economics,where content provider(CP) figures out the cooperation of broadcasting and unicasting services providers,as long as their pricing *** this end,a contract-based content delivery scheme is *** profit of CP depends on users' preference and satisfaction for unicasting and broadcasting *** provides different users with distinctive data *** intent is to maximize its own *** classifying users into different types,the optimal contract in close form is *** results show that the proposed optimal contract is able to generate incentive for users to employ broadcasting transmission,which further benefits both the CP and users.

关键词： content delivery 5g convergednetworks

Non-reciprocity compensation combined with turbo codes for secret key generation in vehicular ad hoc social IoT networks

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arXiv 2018年

作者： Epiphaniou, Gregory Karadimas, Petros Ismail, Dhouha Kbaier Ben Al-Khateeb, Haider Dehghantanha, Ali Choo, Kim-Kwang Raymond School of Computer Science and Technology University of Bedfordshire United Kingdom School of Engineering University of Glasgow Scotland United Kingdom School of Computer Science and Engineering University of Salford United Kingdom Department of Information Systems and Cyber Security University of Texas at San Antonio San AntonioTX United States

—The physical attributes of the dynamic vehicle-to-vehicle (V2V) propagation channel can be utilised for the generation of highly random and symmetric cryptographic keys. However, in physical-layer key agreement, non-reciprocity due to inherent channel noise and hardware impairments can propagate bit disagreements which have to be addressed prior to the symmetric key generation which is inherently important in social IoT networks. This work parametrically models temporal variability attributes such as 3D scattering and scatterers’ mobility and for the first time incorporates such features into the key generation process by combining non-reciprocity compensation with turbo codes. Preliminary results indicate a significant improvement in bit mismatch rate (BMR) and key generation rate (KGR) when compared with sample indexing techniques. Copyright © 2018, The Authors. All rights reserved.

关键词： Internet of things

Gated fusion network for single image dehazing

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arXiv 2018年

作者： Ren, Wenqi Ma, Lin Zhang, Jiawei Pan, Jinshan Cao, Xiaochun Liu, Wei Yang, Ming-Hsuan IIE Cas Tencent Ai Lab City University of Hong Kong Nanjing University of Science and Technology School of Cyber Security University of Chinese Academy of Sciences University of California Electrical Engineering and Computer Science Merced United States

In this paper, we propose an efficient algorithm to directly restore a clear image from a hazy input. The proposed algorithm hinges on an end-to-end trainable neural network that consists of an encoder and a decoder. The encoder is exploited to capture the context of the derived input images, while the decoder is employed to estimate the contribution of each input to the final dehazed result using the learned representations attributed to the encoder. The constructed network adopts a novel fusion-based strategy which derives three inputs from an original hazy image by applying White Balance (WB), Contrast Enhancing (CE), and Gamma Correction (GC). We compute pixel-wise confidence maps based on the appearance differences between these different inputs to blend the information of the derived inputs and preserve the regions with pleasant visibility. The final dehazed image is yielded by gating the important features of the derived inputs. To train the network, we introduce a multi-scale approach such that the halo artifacts can be avoided. Extensive experimental results on both synthetic and real-world images demonstrate that the proposed algorithm performs favorably against the state-of-the-art algorithms. Copyright © 2018, The Authors. All rights reserved.

关键词： Image enhancement

MCP: A multi-component learning machine to predict protein secondary structure

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arXiv 2018年

作者： Khalatbari, Leila Kangavari, M.R. Hosseini, Saeid Yin, Hongzhi Cheung, Ngai-Man School of Computer Engineering Iran University of Science and Technology Tehran Iran ST Electronics SUTD Cyber Security Laboratory Singapore University of Technology and Design Singapore School of Information Technology and Electrical Engineering University of Queensland Brisbane Australia

The Gene or DNA sequence in every cell does not control genetic prop-erties on its own Rather, this is done through translation of DNA into protein and subsequent formation of a certain 3D structure. The biological function of a protein is tightly connected to its specific 3D structure. Prediction of the protein secondary struc-ture is a crucial intermediate step towards elucidating its 3D structure and function. Traditional experimental methods for prediction of protein structure are expensive and time-consuming. Therefore, various machine learning approaches have been proposed to predict the protein secondary structure. Nevertheless, the average accuracy of the suggested solutions has hardly reached beyond 80%. The possible underlying reasons are the ambiguous sequence-structure relation, noise in input protein data, class imbal- A nce, and the high dimensionality of the encoding schemes that represent the protein sequence. In this paper, we propose an accurate multi-component prediction machine to overcome the challenges of protein structure prediction. We devise a multi-component designation to address the high complexity challenge in sequence-structure relation. Furthermore, we utilize a compound string dissimilarity measure to directly interpret protein sequence content and avoid information loss. In order to improve the accuracy, we employ two different classifiers including support vector machine and fuzzy nearest neighbor and collectively aggregate the classification outcomes to infer the final protein secondary structures. We conduct comprehensive experiments to compare our model with the current state-of-the-art approaches. The experimental results demonstrate that given a set of input sequences, our multi-component framework can accurately predict the protein structure. Nevertheless, the effectiveness of our unified model can be further enhanced through framework configuration. Copyright © 2018, The Authors. All rights reserved.

关键词： Support vector machines

Towards a cyber defense framework for SCADA systems based on power consumption monitoring 50

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Towards a cyber defense framework for SCADA systems based on...

50th Annual Hawaii International Conference on System sciences, HICSS 2017

作者： Hernández, Jarilyn M. Chen, Qian Calhoun, Chelsea Sykes, Summer Nichols, Jerey A. Lane Dept. of Computer Science and Electrical Engineering West Virginia University United States Department of Engineering Computer Science Technology Savannah State University Cyber and Information Security Research Group Oak Ridge National Laboratory

ISBN: (纸本)9780998133102

Supervisory control and data acquisition (SCADA) systems are industrial automation systems that remotely monitor and control critical infrastructures. SCADA systems are major targets for espionage and sabotage attackers. Current commercial off-the-shelf security solutions are insufficient in protecting SCADA systems against sophisticated cyber-attacks. Furthermore, these breaches are not detected in real-time or fast enough to prevent further damages. To address this challenge we present a feasibility study that proves monitoring power consumption of SCADA devices is an effective approach to detect cyber-attacks. We built a testbed containing a Programmable Logic Controller (PLC) that was instrumented to record its power usage. Three SCADA-specific cyber-attacks were simulated and we report the power consumption of the PLC under these normal and anomalous scenarios. We show that it is possible to distinguish the PLC power utilization between these scenarios. In route to this result we found and describe vulnerabilities in the DF-1 protocol. © 2017 Proceedings of the Annual Hawaii International Conference on System sciences. All rights reserved.

关键词： Electric power utilization

IoTChain: A three-tier blockchain-based IoT security architecture

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arXiv 2018年

作者： Bao, Zijian Shi, Wenbo He, Debiao Choo, Kim-Kwang Raymond Department of Computer Science and Engineering Northeastern University Shenyang China School of Computer and Communication Engineering Northeastern University Qinhuangdao China State Key Lab of Software Engineering Computer School Wuhan University Wuhan China Department of Information Systems and Cyber Security Department of Electrical and Computer Engineering University of Texas at San Antonio San AntonioTX78249 United States

There has been increasing interest in the potential of blockchain in enhancing the security of devices and systems, such as Internet of Things (IoT). In this paper, we present a blockchain-based IoT security architecture, IoTchain. The three-tier architecture comprises an authentication layer, a blockchain layer and an application layer, and is designed to achieve identity authentication, access control, privacy protection, lightweight feature, regional node fault tolerance, denial-of-service resilience, and storage integrity. We also evaluate the performance of IoTchain to demonstrate its utility in an IoT deployment. Copyright © 2018, The Authors. All rights reserved.

关键词： Internet of things

CBEAT: Chrome Browser Extension Analysis Tool 5th

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CBEAT: Chrome Browser Extension Analysis Tool

5th International Symposium on security in Computing and Communications, SSCC 2017

作者： Roy, Sudakshina Singha Jevitha, K.P. TIFAC CORE in Cyber Security Amrita School of Engineering Coimbatore India Amrita Vishwa Vidyapeetham Amrita University Coimbatore India Department of Computer Science and Engineering Amrita School of Engineering Coimbatore India

ISBN: (纸本)9789811068973

With exponential increased usage of browser extensions for smooth and effortless browsing experience, preventing exposure of user’s private and sensitive data for malicious intent becomes a perpetual challenging task for security researchers. To address this potential threat, extensive work has been carried out to develop a Chrome Browser Extension Analysis Tool, CBEAT. Exclusivity of CBEAT lies in performing holistic analysis combining manifest analysis and JavaScript static taint analysis of manifest and JavaScript files of Chrome Extensions. CBEAT calculates an extension score based on both analysis mentioned above. This score is subsequently used to arrive at classification of the extension and classified as high, medium and low in exposing user’s private and sensitive data. Out of tested Chrome extensions, this paper finds 40% of them as low, 32% as medium and 28% as high. © 2017, Springer Nature Singapore Pte Ltd.

关键词： Sensitive data

A Blockchain-based Architecture Framework for Secure Sharing of Personal Health Data

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A Blockchain-based Architecture Framework for Secure Sharing...

International Conference on e-health Networking, Applications and Services (HealthCom)

作者： Sandro Amofa Emmanuel Boateng Sifah Kwame O.-B Obour Agyekum Smahi Abla Qi Xia James C. Gee Jianbin Gao School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Center for Cyber Security University of Electronic Science and Technology of China Chengdu China Department of Radiology University of Pennsylvania Philadelphia USA School of Resource and Enviroment University of Electronic Science and Technology of China

ISBN: (纸本)9781538642955

Health information exchanges have been popular for some time with their advantages known and widely researched. In spite of their utility in increasing provider efficiency and decreasing administrative costs, one challenge that has persisted is the data owners inability to control data after transmission. The lack of technical mechanisms to effectively control patients' health data in the network significantly affects participation of health and medical institutions while perpetrating the silo-based data management that locks value and potential inherent in the data. This not only affects researchers due to the lack of data for research and analysis but the quality of life of *** present a blockchain-supported architectural framework for secure control of personal data in a health information exchange by pairing user-generated acceptable use policies with smart contracts. We highlight the merits of our system, its user-centric focus and also show experimental results along with directions for extending our work. The framework introduces minimal risk to data by architecting a mechanism for controlling data after sharing. In adopting our framework, health service providers can deliver a stronger assurance for data management than is possible with current systems.

关键词： Information exchange Electronic mail Medical services Monitoring computer science