检索结果-内蒙古大学图书馆

IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Zhichao Cao Yuan He Yunhao Liu Department of Computer Science and Engineering HKUST Hong Kong China MOE Key Laboratory for Information System Security School of Software TNLIST Tsinghua University China

ISBN: (纸本)9781467307734;9781467307758

Energy-constrained wireless sensor networks are duty-cycled, relaying on multi-hop forwarding to collect data packets. A forwarding scheme generally involves three design elements: media access, link estimation, and routing strategy. Most existing studies, however, focus only on a subset of those three. Disregarding the low duty cycle nature of media access often leads to overestimate of link quality. Neglecting the characteristic of bursty loss over wireless links inevitably consumes much more energy than necessary and underutilizes wireless channels. The routing strategy, if not well tailored to the above factors, results in poor packet delivery performance. In this paper, we propose L 2 , a practical design of data forwarding in low duty cycle wireless sensor networks. L 2 addresses link burstiness using multivariate Bernoulli link model. Further incorporated with synchronized rendezvous, L 2 enables sensor nodes to work in a lazy mode, keep their radios off as long as they can, and allocates the precious energy for only a limited number of promising transmissions. We implement L 2 on real sensor network testbeds. The results show that L 2 outperforms state-of-the-art approaches in terms of energy efficiency and network yield.

关键词： Receivers Synchronization Wireless sensor networks Estimation Routing Schedules Delay

来源：评论

学校读者我要写书评

暂无评论

Efficient partially policy-hidden with multi-authority for access control scheme in Internet of Things

Efficient partially policy-hidden with multi-authority for a...

引用

International Conference on networking and network Applications (NaNA)

作者： Yan Liu Ruizhong Du School of Cyber Security and Computer Hebei University Baoding China Key Laboratory on High Trusted Information System in Hebei Province Hebei University Baoding China

ISBN: (数字)9781728189543

ISBN: (纸本)9781728189550

The widespread application from all walks of life in the Internet of Things (IoT) has improved our daily lives, however, the rapidly increased number of devices and data has brought security attacks frequently. To maximize the protection of data privacy and security, an attribute-based encryption(ABE) scheme based on hidden policy with multi-authority is proposed to achieve the fine-grained access control of the shared data. First, the computation complexity is reduced through outsourcing decryption and authentication to edge nodes to avoid the burden of terminals with limited computing and communication capabilities. Second, the system exploits Multi-Authority, in which users are identified with a hash function to effectively resist collusion attacks caused by joint communication between different authorities. At the same time, partially policy is hidden using the linear secret sharing scheme (LSSS) to preserve the attribute privacy. Theoretical analysis and comparison prove that the proposed scheme is secure to resist the attacks and efficient in computation.

关键词： Access control Privacy Resists Computational efficiency Outsourcing Internet of Things Cryptography

来源：评论

学校读者我要写书评

暂无评论

BTC: Bilateral-Branch Vision Transformer via Hilbert Patch Embedding for Image Clustering

BTC: Bilateral-Branch Vision Transformer via Hilbert Patch E...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Taizhang Hu Fan Yang Xing Wei Chong Zhao Li Meng Bin Wen Yang Lu School of Computer and Information Hefei University of Technology Anhui Mine IOT and Security Monitoring Technology Key Laboratory School of Biomedical Engineering Anhui Medical University

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Recently, image clustering methods based on contrastive learning have attracted attention for their advantage of enhancing image representation. However, existing clustering methods struggle to accurately capture global information and maintain the continuity of image semantic information. To address these problems, we propose a contrastive clustering framework called Bilateral-Branch Vision Transformer via Hilbert Patch Embedding for Image Clustering, namely BTC. The core idea is to introduce Vision Transformer (ViT) to provide a global vision, and improve it with the Hilbert Patch Embedding module, which prevents patches from being semantically fragmented during feature extraction. This way, we can fuse the features extracted from two ViT branches based on Patch Embedding and HPE modules, improving global information and contextual semantic continuity. Our extensive experiments on five datasets show that BTC has good performance and effectiveness.

关键词： computer vision Fuses Clustering methods Semantics Contrastive learning Transformer cores Image representation Feature extraction Transformers Data mining

来源：评论

学校读者我要写书评

暂无评论

Real perfect contrast visual cryptography scheme with reversing

引用

Journal of Computational information Systems 2009年第1期5卷 401-405页

作者： Han, Yanyan Hu, Yupu He, Wencai Ministry of Education Key Laboratory of Computer Networks and Information Security Xidian University Xi'an 710071 China Department of Scientific Research Beijing Electronics and Scientist Technology Institute Beijing 100070 China

Visual cryptography schemes are characterized by two parameters: the pixel expansion and the contrast. Generally, to achieve high contrast, schemes should have large pixel expansion. This paper proposed a real perfect contrast visual cryptography scheme (RPCVCS) having the best contrast without loss of resolution. Moreover, the proposed scheme can be implemented based on both the perfect black visual cryptography scheme (PBVCS) and the non-perfect black visual cryptography scheme (NPBVCS). In this paper, basic Boolean operations such as 'AND', 'OR' and 'NOT' were applied to perform the scheme. Compared with the previous schemes, the proposed scheme achieves the best contrast, has the compatibility and performs fewer Boolean operations within fewer finite runs. The experimental results were also given in this paper. Copyright © 2009 Binary information Press.

关键词： Pixels

来源：评论

学校读者我要写书评

暂无评论

FLEER: A Federated Learning Framework for EEG Emotion Recognition

FLEER: A Federated Learning Framework for EEG Emotion Recogn...

引用

Artificial Intelligence, networking and information Technology (AINIT), International Seminar on

作者： Mingming Li Xianglei Tang School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China Zhejiang Electronic Information Products Inspection and Research Institute (Key Laboratory of Information Security of Zhejiang Province) Hangzhou China

ISBN: (数字)9798350385557

ISBN: (纸本)9798350385564

The success of deep learning (DL) methods in the Brain-computer Interface (BCI) field for emotion recognition of electroencephalographic (EEG) recordings has been limited due to the scarcity of large datasets. Individual difference and privacy concern restrict the feasibility of creating a large EEG-BCI dataset through merging multiple small datasets for the collaborative training of machine learning models. To solve this problem, we propose a personalized federated learning framework based on the common feature for EEG emotion recognition classification network (FLEER). FLEER learns user's common feature representation through deep learning methods and generates the personalized model for each user. We assess the effectiveness of the proposed architecture on the DEAP dataset for 4-class emotion recognition classification. The experimental results show FLEER provides an effective method for EEG emotion recognition classification while avoiding the actual data sharing and its results are comparable to the baseline in intra-subject. Additionally, our model provides 2 % better accuracy compared to other DL architectures in inter-subject.

关键词： Deep learning Training Seminars Emotion recognition Data privacy Federated learning Brain modeling

来源：评论

学校读者我要写书评

暂无评论

Minfer: A method of inferring motif statistics from sampled edges

Minfer: A method of inferring motif statistics from sampled ...

引用

International Conference on Data Engineering

作者： Pinghui Wang John C.S. Lui Don Towsley Junzhou Zhao MOE Key Laboratory for Intelligent Networks and Network Security Xi'an Jiaotong University Xi'an China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9781509020218

Characterizing motif (i.e., locally connected sub-graph patterns) statistics is important for understanding complex networks such as online social networks and communication networks. Previous work made the strong assumption that the graph topology of interest is known in advance. In practice, sometimes researchers have to deal with the situation where the graph topology is unknown because it is expensive to collect and store all topological and meta information. Hence, typically what is available to researchers is only a snapshot of the graph, i.e., a subgraph of the graph. Crawling methods such as breadth first sampling can be used to generate the snapshot. However, these methods fail to sample a streaming graph represented as a high speed stream of edges. Therefore, graph mining applications such as network traffic monitoring use random edge sampling (i.e., sample each edge with a fixed probability) to collect edges and generate a sampled graph, which we called a “RESampled graph”. Clearly, a RESampled graph's motif statistics may be quite different from those of the underlying original graph. To resolve this, we propose a framework and implement a system called Minfer, which takes the given RESampled graph and accurately infers the underlying graph's motif statistics. We also apply Fisher information to bound the errors of our estimates. Experiments using large scale datasets show the accuracy and efficiency of our method.

关键词： Topology Electronic mail Communication networks Social network services network topology Intelligent networks security

来源：评论

学校读者我要写书评

暂无评论

Full Service Hopping for Proactive Cyber-Defense

Full Service Hopping for Proactive Cyber-Defense

引用

IEEE International Conference on networking, Sensing and Control

作者： Leyi Shi Chunfu Jia Shuwang Lu College of Computer and CommunicationEngineering China University of Petroleum Dongying China State Key Laboratory of Information Security Graduate School of Chinese Academy of Sciences Beijing China

Inspired by deceptive and evasive countermeasures for military environment, a proactive cyber defense tactic of full service hopping is proposed which changes all the service information pseudo-randomly, including service port, network address, service slot, cryptographic algorithm and even the service protocol. A novel concept of dynamic honey pot is presented which mimics the ancient battle diagrams to bewilder the adversary by changing the role of every hopping station pseudo-randomly. Thereafter a full service hopping framework and synchronization scheme of Spokesman are introduced. Then a distributed prototype is carried out through mobile Java agent. Our experimental works demonstrate that full hopping tactic has better performance for active cyber-defense. Moreover, the overheads of handover and synchronization during service hopping are also discussed in this paper.

关键词： Intrusion detection information security Cryptography Cryptographic protocols Prototypes Java National security Internet computer security Radio communication countermeasures

来源：评论

学校读者我要写书评

暂无评论

Using evolutionary process for cross-version software defect prediction

引用

International Journal of Performability Engineering 2019年第9期15卷 2484-2493页

作者： Li, Yong Liu, Zhandong Zhang, Haijun College of Computer Science and Technology Xinjiang Normal University Urumqi830054 China Data Security Key Laboratory Xinjiang Normal University Urumqi830054 China Key Laboratory of Safety-Critical Software Ministry of Industry and Information Technology Nanjing211106 China

Cross-version defect prediction can effectively reduce the construction cost of a model, which is of great significance for understanding the causes of defects in subsequent software versions and improving the quality of software products. The objective of this work is to validate the feasibility of the cross-version defect predictor using the evolutionary process in different scenarios and to investigate practical guidelines for the choice of evolutionary process and historical data of a given project. Firstly, we verified the effectiveness of the evolutionary process attributes in the cross-version prediction model. Then, we analyzed the cross-version model prediction performance based on multi-version historical data. Finally, multiple benchmark models were selected for experimental comparison to further verify the effectiveness of the proposed method. The experimental conclusions can not only effectively reduce the construction cost of the defect prediction model in the version evolution scenarios, but also help developers understand the defect generation mechanism in the subsequent versions and improve the software development process in a targeted way. © 2019 Totem Publisher, Inc. All rights reserved.

关键词： Defects

来源：评论

学校读者我要写书评

暂无评论

Seeing is not Believing: An Identity Hider for Human Vision Privacy Protection

arXiv

引用

arXiv 2023年

作者： Wang, Tao Zhang, Yushu Yang, Zixuan Xiao, Xiangli Zhang, Hua Hua, Zhongyun The College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China The Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies Shenzhen518055 China The State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Shenzhen518055 China

Massive captured face images are stored in the database for the identification of individuals. However, these images can be observed unintentionally by data examiners, which is not at the will of individuals and may cause privacy violations. Existing protection schemes can maintain identifiability but slightly change the facial appearance, rendering it still susceptible to the visual perception of the original identity by data examiners. In this paper, we propose an effective identity hider for human vision protection, which can significantly change appearance to visually hide identity while allowing identification for face recognizers. Concretely, the identity hider benefits from two specially designed modules: 1) The virtual face generation module generates a virtual face with a new appearance by manipulating the latent space of StyleGAN2. In particular, the virtual face has a similar parsing map to the original face, supporting other vision tasks such as head pose detection. 2) The appearance transfer module transfers the appearance of the virtual face into the original face via attribute replacement. Meanwhile, identity information can be preserved well with the help of the disentanglement networks. In addition, diversity and background preservation are supported to meet various requirements. Extensive experiments demonstrate that the proposed identity hider achieves excellent performance on privacy protection and identifiability preservation. Copyright © 2023, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhanced Competitive Swarm Optimizer for Multi-task Optimization 2020

Enhanced Competitive Swarm Optimizer for Multi-task Optimiza...

引用

Proceedings of the 2020 9th International Conference on Computing and Pattern Recognition

作者： Wei Li Junqing Yuan Haonan Luo Zhou Lei Qingzheng Xu School of Computer Science and Engineering Xi'an University of Technology and Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China School of Computer Science and Engineering Xi'an University of Technology Xi'an China College of Information and Communication National University of Defense Technology Xi'an China

ISBN: (纸本)9781450387835

In the real world, many problems possess the high degree of similarity. Inspired by multifactorial inheritance model, evolutionary multi-task optimization paradigm is proposed to simultaneously solve multiple optimization problems. However, experimental results have revealed that the performance of multifactorial evolutionary algorithm deteriorates with negative knowledge transfer between uncorrelated tasks. To alleviate this issue, we proposed an enhanced competitive swarm optimizer to explore the generality of the multitasking paradigm. A new velocity update mechanism for losers is proposed to improve the search ability. Further, a mating approach is proposed to transfer implicit knowledge among tasks for generating offspring. Experimental and statistical analyses are performed on CEC2017 evolutionary multitask optimization competition. Results show that the proposed algorithm is competitive in comparison with other state-of-the-art multifactorial optimization algorithms.

关键词： Evolutionary multitasking competitive swarm optimizer evolutionary algorithms

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：