检索结果-内蒙古大学图书馆

Attribute-Based data Sharing Scheme with Flexible Search Functionality for Cloud-Assisted Autonomous Transportation system

引用

IEEE Transactions on Industrial Informatics 2023年第11期19卷 10977-10986页

作者： Xiong, Hu Wang, Hanxiao Meng, Weizhi Yeh, Kuo-Hui University of Electronic Science and Technology of China School of Information and Software Engineering Network and Data Security Key Laboratory of Sichuan Province Chengdu610054 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610025 China Technical University of Denmark Department of Applied Mathematics and Computer Science Kongens Lyngby2800 Denmark National Dong Hwa University Department of Information Management Hualien97401 Taiwan National Sun Yat-sen University Department of Computer Science and Engineering Kaohsiung804201 Taiwan

The existing group public key encryption with equality test schemes could only support one-to-one data sharing and are not suitable for cloud-assisted autonomous transportation systems, which demand one-to-many data sharing. To tackle this problem efficiently, in this article, we put forward the group-attribute-based encryption with equality test (G-ABEET) scheme. The presented G-ABEET allows sensors equipped in vehicles to encrypt traffic data with an expressive access policy before sharing it. Only users with attributes required by the access policy ought to access the shared ciphertexts, thus achieving selective one-to-many data sharing. Meanwhile, the authorized cloud server could provide group users with equality tests over the ciphertexts, realizing ciphertext search ability. Furthermore, with the group mechanism, the G-ABEET scheme could resist offline message recovery attacks. Besides, in the standard model, we give rigorous security proof of the G-ABEET construction. The feasibility and efficiency of G-ABEET are demonstrated by experimental simulations. © 2005-2012 IEEE.

关键词： Cloud computing

来源：评论

学校读者我要写书评

暂无评论

Quantum security analysis of SM4 algorithm 6

Quantum security analysis of SM4 algorithm

引用

6th International Conference on Wireless Communications and Smart Grid, ICWCSG 2024

作者： Yang, Hao Wang, Chunhong Tang, Xueming Cui, Yongquan Lu, Songfeng Cai, Dunbo Qian, Ling Zhang, Runqing Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Wuhan Maritime Communication Research Institute Wuhan430010 China Software Technology Co. Ltd. Suzhou215153 China

ISBN: (纸本)9781510682962

The security of commercial encryption algorithms has always been a focus of attention. The SM4 algorithm, a commercial cryptographic standard, has been recognized by ISO/IEC as an international standard and has shown excellent performance on classical computers. However, with the development of quantum computing, traditional encryption algorithms are facing new challenges. This paper investigates the quantum realization of SM4 algorithm. By applying the Grover algorithm to the SM4 algorithm, we conducted a quantum exhaustive attack and provided an estimation of the required quantum resources. This study offers a novel perspective on the application of quantum computing in breaking commercial encryption algorithms, which holds significant implications for the future development of quantum secure communication and cryptography. © 2024 SPIE.

关键词： Encryption algorithms

来源：评论

学校读者我要写书评

暂无评论

Improved MILP modeling for automatic security evaluation and application to fox

Improved MILP modeling for automatic security evaluation and...

引用

作者： Qiao, Kexin Hu, Lei Sun, Siwei Ma, Xiaoshuang Kan, Haibin State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Data Assurance and Communication Security Research Center Chinese Academy of Sciences Beijing100093 China University of Chinese Academy of Sciences Beijing100049 China Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University Shanghai200433 China

Counting the number of differentially active S-boxes is of great importance in evaluating the security of a block cipher against differential attack. Mouha et al. proposed a technique based on Mixed-Integer Linear Programming (MILP) to automatically calculate a lower bound of the number of differentially active S-boxes for word-oriented block ciphers, and applied it to symmetric ciphers AES and Enocoro-128v2. Later Sun et al. extended the method by introducing bit-level representations for Sboxes and new constraints in the MILP problem, and applied the extended method to PRESENT-80 and LBlock. This kind of methods greatly depends on the constraints in the MILP problem describing the differential propagation of the block cipher. A more accurate description of the differential propagation leads to a tighter bound on the number of differentially active S-boxes. In this paper, we refine the constraints in the MILP problem describing XOR operations, and apply the refined MILP modeling to determine a lower bound of the number of active S-boxes for the Lai-Massey type block cipher FOX in the model of single-key differential attack, and obtain a tighter bound in FOX64 than existing results. Experimental results show that 6, instead of currently known 8, rounds of FOX64 is strong enough to resist against basic single-key differential attack since the differential characteristic probability is upper bounded by 2-64, and thus the maximum differential characteristic probability of 12-round FOX64 is upper bounded by 2-128, where 128 is the key-length of FOX64. We also get the lower bound of the number of differentially active S-boxes for 5-round FOX128, and proved the security of the full-round FOX128 with respect to single-key differential attack. Copyright © 2015 The Institute of Electronics, Information and Communication Engineers.

关键词： Integer programming

来源：评论

学校读者我要写书评

暂无评论

Publication recommendations of manuscripts using improved C4.5 decision tree algorithm 2nd

Publication recommendations of manuscripts using improved C4...

引用

2nd International Conference on intelligent and Interactive systems and Applications, IISA 2017

作者： Jia, Didi Xie, Wu Chen, Zhiyong Qiang, Baohua School of Computer Science and Information Security Guilin University of Electronic Technology Guilin541004 China Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex System Guilin541004 China Guangxi Key Laboratory of Trusted Software Guilin541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin541004 China

ISBN: (纸本)9783319690957

In view of the problem that the result accuracy of the research publication recommendations of manuscripts is often low. It is very difficult for many contributors to find the suitable journals from many recommendation results. To solve this problem, a novel method of publication recommendations for authors’ manuscripts is proposed using our improved C4.5 decision tree algorithm. For the shortcomings of too many values of data samples during dealing with the traditional C4.5 methods, the five-value logic ideas are adopted to improve this C4.5 algorithm to apply in the research fields of publication recommendations. The experimental results show that the related publications are easier to obtain for authors via the decision trees with the improved C4.5 method than before, and this method has higher accuracy than ever. It is of great significance to help the researchers, especially for those who have no enough experience to choose the most suitable journals from a lot of publications. © 2018, Springer International Publishing AG.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

ANIMC: A Soft Approach for Autoweighted Noisy and Incomplete Multiview Clustering

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2022年第2期3卷 192-206页

作者： Fang, Xiang Hu, Yuchong Zhou, Pan Wu, Dapeng Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering The School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Information Storage System Ministry of Education of China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611 United States

Multiview clustering has wide real-world applications because it can process data from multiple sources. However, these data often contain missing instances and noises, which are ignored by most multiview clustering methods. Missing instances may make these methods difficult to use directly, and noises will lead to unreliable clustering results. In this article, we propose a novel autoweighted noisy and incomplete multiview clustering (ANIMC) approach via a soft autoweighted strategy and a doubly soft regular regression model. First, by designing adaptive semiregularized nonnegative matrix factorization, the soft autoweighted strategy assigns a proper weight to each view and adds a soft boundary to balance the influence of noises and incompleteness. Second, by proposing θ-norm, the doubly soft regularized regression model adjusts the sparsity of our model by choosing different θ. Compared with previous methods, ANIMC has three unique advantages: 1) it is a soft algorithm to adjust our approach in different scenarios, thereby improving its generalization ability;2) it automatically learns a proper weight for each view, thereby reducing the influence of noises;3) it performs doubly soft regularized regression that aligns the same instances in different views, thereby decreasing the impact of missing instances. Extensive experimental results show its superior advantages over other state-of-the-art works. © 2020 IEEE.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

A Botnet data Collection Method for Industrial Internet 20

A Botnet Data Collection Method for Industrial Internet

引用

20th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2023

作者： Jian, Shu Bo, Xian Chenli, Wang Jiazhong, Lu Yuanyuan, Huang Shuo, Han School of Cybersecurity Chengdu University of Information Technology Sichuan Chengdu610225 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Sichuan Chengdu610225 China Northwestern University Department of Statistics and Data Sciences EvanstonIL60202 United States

ISBN: (纸本)9798350318982

Industrial internet security is related to industrial production operations and national economic security. Network intrusion detection dataset in industrial control environment can effectively train detection models and mitigate network attacks, which is an indispensable component for industrial internet security. In this paper, we propose a data collection method for industrial Internet-oriented botnet by classifying traffic packets according to network traffic features and industrial control identification codes, containing the status of industrial control devices. This method can greatly improve the detection accuracy of the model in the industrial internet. To create a botnet incursion dataset in the industrial control environment, we simultaneously employed the existing industrial control devices to gather both industrial control and botnet network traffic. Finally, we used an AI-based model to detect the botnet. © 2023 IEEE.

关键词： Botnet

来源：评论

学校读者我要写书评

暂无评论

MC-GAN: An Adversarial Sample Defense Algorithm 20

MC-GAN: An Adversarial Sample Defense Algorithm

引用

20th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2023

作者： Chenli, Wang Juyang, W.U. Xing, Yang Junfei, Wang Jian, S.H.U. Jiazhong, L.U. Yuanyuan, Huang Shuo, H.A.N. School of Cybersecurity Chengdu University of Information Technology Sichuan Chengdu610225 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Sichuan Chengdu610225 China Northwestern University Department of Statistics and Data Sciences EvanstonIL60202 United States

ISBN: (纸本)9798350318982

The current adversarial sample defense algorithms are plagued by issues such as poor defense effectiveness and high training costs. In order to enhance sample classification accuracy while reducing training costs, we have introduced a novel defense algorithm based on model compression within the framework of Generative Adversarial Networks (GANs). This algorithm integrates GANs with model compression techniques, and the results of testing on public datasets have demonstrated an improved accuracy in defending against adversarial samples along with reduced training costs. © 2023 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Dlr: Adversarial Examples Detection and Label Recovery for Deep Neural Networks

SSRN

引用

SSRN 2023年

作者： Han, Keji Ge, Yao Wang, Ruchuan Li, Yun Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing University of Posts and Telecommunications Jiangsu Nanjing210023 China

Deep neural networks (DNNs) are demonstrated to be vulnerable to the adversarial example crafted by the adversary to fool the target model. Adversarial training and adversarial example detection are two popular methods to mitigate the adversarial issue. The adversarial training makes the target model recognize the adversarial example correctly for the image classification task, while it does not generalize well. The adversarial detection generalizes well but cannot help the target model recognize the adversarial example. We first define the label recovery task to address the adversarial issue for DNNs. Then we propose a new generative classifier and apply it to the adversarial example label recovery task. The proposed method is named as Detection and Label Recovery (DLR) defense method, which consists of Detector and Recover. Detector feeds the legitimate and adversarial examples to the target model and Recover, respectively. The Recover explores the ground-truth label of the detected adversarial example. DLR combines the merits of adversarial training and adversarial example detection. Experimental results demonstrate that our method outperforms some state-of-the-art adversarial training methods. © 2023, The Authors. All rights reserved.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Towards improving detection performance for malware with a correntropy-based deep learning method

引用

Digital Communications and Networks 2021年第4期7卷 570-579页

作者： Xiong Luo Jianyuan Li Weiping Wang Yang Gao Wenbing Zhao School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China Beijing Intelligent Logistics System Collaborative Innovation Center Beijing101149China China Information Technology Security Evaluation Center Beijing100085China Department of Electrical Engineering and Computer Science Cleveland State UniversityClevelandOH44115USA

With the rapid development of Internet of Things(IoT)technologies,the detection and analysis of malware have become a matter of concern in the industrial application of Cyber-Physical system(CPS)that provides various services using the IoT ***,many advanced machine learning methods such as deep learning are popular in the research of malware detection and analysis,and some achievements have been made so ***,there are also some *** example,considering the noise and outliers in the existing datasets of malware,some methods are not robust ***,the accuracy of malware classification still needs to be *** at this issue,we propose a novel method that combines the correntropy and the deep learning *** our proposed method for malware detection and analysis,given the success of the mixture correntropy as an effective similarity measure in addressing complex datasets with noise,it is therefore incorporated into a popular deep learning model,i.e.,Convolutional Neural Network(CNN),to reconstruct its loss function,with the purpose of further detecting the features of *** present the detailed design process of our ***,the proposed method is tested both on a real-world malware dataset and a popular benchmark dataset to verify its learning performance.

关键词： Malware detection Mixture correntropy Deep learning Convolutional neural network(CNN)

来源：评论

学校读者我要写书评

暂无评论

An optimal profit route planning scheme based on ACO-OPP 21

An optimal profit route planning scheme based on ACO-OPP

引用

21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on data Science and systems, HPCC/SmartCity/DSS 2019

作者： Qiu, Yuhua Xu, Xiaolong Xia, Fei Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China Information and communication Branch State Grid Jiangsu Electric Power Company Nanjing China

ISBN: (纸本)9781728120584

Taxi plays an important role of urban public transportation system. However, without appropriate route planning scheme, taxi drivers can only choose to wait or seek passengers in the absence of orders, leading to wasting a lot of time and fuel. In this paper, an optimal profit route planning scheme for taxi drivers with Ant Colony Optimization Algorithm based on Optimal Profit Points (ACO-OPP) is proposed. First, the taxi trajectory data are preprocessed and the pick-up and drop-off points are extracted to obtain high-quality data;second, the data spatiotemporal distribution is analyzed to plan a more appropriate and rational route;the clustering algorithm is used to obtain the optimal profit points to increase the occupancy rate of taxis;then, ACO-OPP is utilized to plan the profit routes for each taxi. A series of experiments are implemented based on the real taxi trajectory dataset to test and compare the performance of the simulated annealing algorithm, the genetic algorithm, the ant colony algorithm and ACO-OPP on the optimal route length and the profitability with the unit time profit function. The experimental results show that ACO-OPP has the shortest optimal route length and the best profit per unit time. © 2019 IEEE.

关键词： Profitability

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：