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Decentralized Multi-Authority Attribute-based Searchable Encryption Scheme

International Journal of Network security 2021年第2期23卷 332-342页

作者： Ren, Juan Zhang, Leyou Wang, Baocang Science and Technology on Communication Security Laboratory Chengdu610041 China School of Mathematics and Statistics Xidian University Xi'an710126 China School of Information Engineering Xuchang University Xuchang461000 China State Key Laboratory of Integrated Service Networks Xidian University Xi'an710071 China

Attribute-based searchable encryption (ABSE) scheme is an efficient mechanism to implement access control and secure keywords search based on attributes over encrypted data. However, most existing ABSE schemes rely on single trusted authority to manage the attribute private keys. In real life, it is impractical that one authority completes all verifications and certifications to all attributes. In addition, the existence of the vulnerable item makes them be vulnerable to secret-key-recovery attack in some existing multi-authority attribute-based encryption (ABE) schemes based on access tree. To solve above problems, we design a decentralized multi-authority ABSE scheme based on access tree, which can resist the keyword guessing (KG) attack and the secret-keys-recovery attack. We also give performance analysis of the proposed scheme and prove it to be selectively secure under the decisional bilinear Diffie-Hellman (DBDH) assumption, the hash Diffie-Hellman (HDH) assumption and the bilinear Diffie-Hellman (BDH) assumption. © 2021, International Journal of Network security. All Rights Reserved.

关键词： Access control

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Decentralizing Multi-Authority Attribute-Based Access control Scheme with Fully Hidden Policy

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International Journal of Network security 2021年第4期23卷 588-603页

作者： Zhang, Leyou Ren, Juan Kang, Li Wang, Baocang School of Mathematics and Statistics Xidian University Xi’an710126 China Science and Technology on Communication Security Laboratory Chengdu610041 China School of Information Engineering Xuchang University Xuchang461000 China State Key Laboratory of Integrated Service Networks Xidian University Xi’an710071 China

Decentralized multi-authority attribute-based encryption (MA-ABE) is considered a potential method to protect users’ privacy in the cloud. However, most of the existing works cannot provide a complete solution since some vulnerabilities can be found in users’ collusion, global identity (GID) leakage-resilience, and access policy hiding. In this paper, we focus on overcoming these short- comings. At first, we investigate the recent works and give a summary of them. Then an efficient decentralized MA-ABE scheme with a fully hidden access policy is pre- sented. To implement the hidden access policy, we use the technique of Inner-Product Encryption (IPE). Under this technique, the Vi‘ete’s Formulas is used to convert the access policy into a vector, which results in an effi- cient decentralized MA-ABE scheme with the shortened ciphertext and secret keys, which are only concerned with the number of wildcards. To further improve efficiency, the decryption is partially outsourced. The security of the proposed scheme is reduced to the standard decisional bi- linear Diffie-Hellman (DBDH) assumption and the Deci- sional Linear (DLIN) assumption instead of other strong assumptions. Finally, performance analysis and numeri- cal experiments confirm the scalability and flexibility of our approach. © 2021

关键词： Cryptography

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Modulation Recognition of Underwater Acoustic communication Signals Based on Joint Feature Extraction

Modulation Recognition of Underwater Acoustic Communication ...

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2019 IEEE International Conference on Signal, information and Data Processing, ICSIDP 2019

作者： Ge, Yizhou Zhang, Xin Zhou, Qing Science and Technology on Communication Information Security Control Laboratory Jiaxing314000 China No.36 Research Institute of CETC Jiaxing314000 China School of Marine Science and Technology Northwestern Polytechnical University Xi'an710072 China

ISBN: (纸本)9781728123455

Recently, the research on modulation identification of underwater acoustic (UWA) communication signals has attracted much attention. It is a challenge to identify the modulation of underwater acoustic communication signals in the environment of low signal-to-noise ratio (SNR), multipath interference, frequency and phase drift. In this paper, a joint feature extraction algorithm is proposed which combines the method of cyclic spectrum with high-order cumulant to perform the modulation recognition of UWA communication. In the algorithm, the higher-order cumulant features of the communication signals and their counterparts after the square transformation are used firstly for the intra-class modulation recognition of phase shift keying (PSK) and frequency shift keying (FSK), and the inter-class modulation recognition of PSK. Then the cross-section parameter of spectral correlation function of signals are used for inter-class recognition of FSK modulation. Simulation results show that BPSK, QPSK, 2FSK and 4FSK underwater acoustic communication signals can be identified at rate better than 90% by using the joint modulation recognition algorithm with a signal-to-noise ratio of -2dB. © 2019 IEEE.

关键词： Underwater acoustic communication

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Tigc-Net: Transformer-Improved Graph Convolution Network for Spatio-Temporal Prediction

SSRN

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SSRN 2022年

作者： Chen, Kai Yang, Chunfeng Zhou, Zhengyuan Liu, Yao Ji, Tianjiao Sun, Weiya Chen, Yang School of Cyber Science and Engineering Southeast University Nanjing210096 China Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education Nanjing210096 China The College of Software Engineering Southeast University Nanjing210096 China Laboratory of Image Science and Technology The School of Computer Science and Engineering Southeast University Nanjing210096 China Jiangsu Key Laboratory of Molecular and Functional Imaging Department of Radiology Zhongda Hospital Southeast University Nanjing210009 China Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing School of Computer Science and Engineering Southeast University Nanjing210096 China NHC Key Laboratory of Medical Virology and Viral Diseases National Institute for Viral Disease Control and Prevention Chinese Center for Disease Control and Prevention Beijing China Beijing Institute of Tracking and Communication Technology Beijing100094 China

Modeling spatio-temporal sequences is an important topic yet challenging for existing neural networks. Most of the current spatio-temporal sequence prediction methods usually capture features separately in temporal and spatial dimensions or employ multiple mutually independent local spatio-temporal graphs to represent a spatio-temporal sequence. The first kind of method mentioned above is difficult to mine the complex spatio-temporal correlations, while the other is limited for the accuracy of long-term predictions. To handle these issues, this paper proposes a Transformer-Improved Graph Convolution Network for spatio-temporal prediction. Specifically, the temporal location encoding method is exploited to derive the spatio-temporal characteristics of the sequence utilizing a spatio-temporal feature fusion network. In addition, a spatio-temporal attention network is developed to enhance the spatio-temporal correlation of the sequence, and the dynamic spatial features of sequence are further extracted through the adaptive graph convolution network. A private dataset and a public dataset are employed to demonstrate the performance of the proposed TIGC-Net. The qualitative and quantitative results show that the proposed TIGC-Net can extract dynamic spatiotemporal properties more effectively, enhance the spatio-temporal correlation of sequences and improve the prediction accuracy compared with four stateof-the-art. © 2022, The Authors. All rights reserved.

关键词： Convolution

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Distributed Fine-Grained Traffic Speed Prediction for Large-Scale Transportation Networks based on Automatic LSTM Customization and Sharing

arXiv

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arXiv 2020年

作者： Lee, Ming-Chang Lin, Jia-Chun Gran, Ernst Gunnar Department of Information Security and Communication Technology Norwegian University of Science and Technology Gjøvik2815 Norway Simula Research Laboratory Fornebu1364 Norway

Short-term traffic speed prediction has been an important research topic in the past decade, and many approaches have been introduced. However, providing fine-grained, accurate, and efficient traffic-speed prediction for large-scale transportation networks where numerous traffic detectors are deployed has not been well studied. In this paper, we propose DistPre, which is a distributed fine-grained traffic speed prediction scheme for large-scale transportation networks. To achieve fine-grained and accurate traffic-speed prediction, DistPre customizes a Long Short-Term Memory (LSTM) model with an appropriate hyperparameter configuration for a detector. To make such customization process efficient and applicable for large-scale transportation networks, DistPre conducts LSTM customization on a cluster of computation nodes and allows any trained LSTM model to be shared between different detectors. If a detector observes a similar traffic pattern to another one, DistPre directly shares the existing LSTM model between the two detectors rather than customizing an LSTM model per detector. Experiments based on traffic data collected from freeway I5-N in California are conducted to evaluate the performance of DistPre. The results demonstrate that DistPre provides time-efficient LSTM customization and accurate fine-grained traffic-speed prediction for large-scale transportation networks. Copyright © 2020, The Authors. All rights reserved.

关键词： Speed

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Extending Registration and Authentication Processes of FIDO2 External Authenticator with QR Codes

Extending Registration and Authentication Processes of FIDO2...

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IEEE International Conference on Trust, security and Privacy in Computing and communications (TrustCom)

作者： Chengqian Guo Quanwei Cai Qiongxiao Wang Jingqiang Lin State Key Laboratory of Information Security Institute of Information Engineering CAS Data Assurance and Communication Security Research Center CAS School of Cyber Security University of Chinese Academy of Sciences School of Cyber Security University of Science and Technology of China

ISBN: (数字)9781665403924

ISBN: (纸本)9781665403931

FIDO2, the newest set of FIDO specifications, enables the user to leverage an external authenticator for the authentication in both mobile and desktop environments (referred to as user agent). For the secure registration and authentication, FIDO2 requires the external authenticator and user agent to establish a confidential and mutually authenticated data transport channel through either USB interfaces, Near Field communication (NFC) or Bluetooth. However, the external authenticator and host may not be equipped with one of the above physical media simultaneously, for example, a desktop may only have USB interfaces while an external authenticator (e.g., a smartphone) may have no USB inferfaces. This affects the wide adoption of FIDO2. In this paper, we extend the registration and authentication processes of FIDO2 external authenticator with QR code, which enables the external authenticator being equipped with a camera to be used for the authentication at any user agent. During the registration process, our scheme requires the user to provide the original credential and a one-time password displayed on the authenticator, and therefore ensures the correct user will only be bound with the expected authenticator. The security of our scheme has been formally analyzed based on the Dolev-Yao style model, a widely adopted model for the analysis of web systems. We have implemented the prototype, and the performance evaluation demonstrated the efficiency of our scheme, which needs 373 ms for registration and 141 ms for authentication in our environment.

关键词： Analytical models Privacy Authentication Prototypes Near field communication Universal Serial Bus security

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Robust Beamforming Based on Covariance Matrix Reconstruction and ADMM

Robust Beamforming Based on Covariance Matrix Reconstruction...

引用

IEEE International Conference on Radar

作者： Pengcheng Gong Zhaobin Wang Kaiyan Xu School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Computer Science and Engineering Wuhan Institute of Technology Wuhan China Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of Technology Wuhan China

ISBN: (纸本)9781665468893

Considering at the issue that the performance of the traditional beamforming algorithm will decrease sharply when the disturbance occurs at the disturbed position and the steering vector mismatch occurs, a new robust beamforming method based on covariance matrix reconstruction and Alternating Direction Method of Multipliers (ADMM) is proposed. Firstly, based on the maximum output power criterion of beamformers, an optimization model is designed to solve the optimal steering vector. Then, the covariance matrix is reconstructed by using the defined interference range to widen the nullity and enhance the anti-motion interference ability of the system. Then, for the quadratic inequality constraint problem of the steering vector, this paper uses ADMM to solve the model iteratively, and obtains the specific solution of the steering vector in each iteration. In addition, the complexity of the algorithm is also analyzed. The experimental results show that, compared with the existing beamforming algorithms, the proposed method Widen the width of zero notch in the interference area, improves the anti-interference performance of the beam, and can well correct the mismatched steering vector.

关键词： Systematics Array signal processing Interference Radar Resists Convex functions Robustness

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Research on evaluation index system for software vulnerability analysis methods 4

Research on evaluation index system for software vulnerabili...

引用

4th IEEE International Conference on Data science in Cyberspace, DSC 2019

作者： Li, Jin Huang, Min-Huan Lu, Shuai-Bing Li, Hu Chen, Jin-Fu National Key Laboratory of Science and Technology on Information System Security Beijing China School of Computer Science and Communication Engineering Jiangsu University Jiangsu China

ISBN: (纸本)9781728145280

Due to the diversity of existing software vulnerability analysis methods, a unified index system is required if we are to accurately and comprehensively evaluate the analytic effects in order to further improve the level of analysis. Accordingly, this paper first proposes the principles and process necessary to construct an evaluation index system for software vulnerability analysis. Moreover, by focusing on the problems identified in previous relevant research, an evaluation index system for software vulnerability analysis methods that contains four aspects-accuracy, coverage, value and performance-is proposed;this system is more comprehensive and complete than existing achievements. Finally, using the vulnerability analysis testing framework, the indexes of the three different versions of cppcheck are measured. The results show that the proposed evaluation index system can be used for the comparative evaluation of different vulnerability analysis methods. © 2019 IEEE.

关键词： Analysis method Evaluation index system Software vulnerability

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Research of Association Rules Mining based on Fuzzy Alarm Extraction

Research of Association Rules Mining based on Fuzzy Alarm Ex...

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作者： Li tongyan Lei dong Qin Zhiguang Chengdu University of Information Technology Dept.of Communication Engineering Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Chengdu University of Information Technology Dept.of Communication Engineering

In communication alarm correlation analysis, original alarm data often have problems about information redundancy, data incompleteness, time synchronization and "sharp boundary". This paper proposed a novel alarm extraction algorithm in order to resolve above problems. We first fuzzy the original alarms to avoid "sharp boundary" during the alarm preprocessing process, and then we proposed a novel double constraint based sliding time window method to improve the efficiency on extracting data. Performance tests of the algorithm indicate that this method has higher extracting efficiency than traditional methods, which is suitable for alarm data in telecommunication networks.

关键词： Alarm correlation analysis fuzzy alarm sharp boundary

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GPDP: Game-Enhanced Personalized Differentially Private Smart Community

GPDP: Game-Enhanced Personalized Differentially Private Smar...

引用

IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom) Green Computing and communications (GreenCom)

作者： Yuping Zhang Youyang Qu Longxiang Gao Bruce Gu Lei Cui Xuemeng Zhai School of Network & Communication Chendu Technological University Chendu Sichuan China School of Information Technology Deakin University Geelong VIC Australia College of Engineering and Science Victoria University Footscary VIC Australia Key Laboratory of Advanced Control and Intelligent Information System Taiyuan University of Science and Technology Taiyuan Shanxi China College of Engineering and Science University of Electronic Science and Technology of China Chengdu Sichuan China

ISBN: (纸本)9781665417631

Smart community, as a key component of Internet of Things (IoT), is experiencing fast booming, which significantly enhances residents' quality of life. Using fog computing to establish a smart community is an effective way to further develop smart and sustainable cities due to the reduction of bandwidth consumption and latency. However, privacy issues are emerging because the continuous attacks are putting sensitive information under great threats. Motivated by this, we propose a differentially private smart community model with personalized privacy protection. Differential privacy is deployed in a personalized way while a logarithmic function is leveraged to map data sensitivity to privacy protection level. Extensive evaluation results show the advantages of the proposed model from the perspective of the optimized trade-off between personalized privacy protection and data utility.

关键词： Differential privacy Privacy Sensitivity Smart cities Computational modeling Bandwidth Data models

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