检索结果-内蒙古大学图书馆

IEEE International Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Yun Luo Yuling Chen Tao Li Yilei Wang Yixian Yang State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guiyang China School of Computer Science Qufu Normal University Rizhao China School of Cyberspace Security Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665421751

Secure multi-party computation(SMPC) is an important research field in cryptography, secure multi-party computation has a wide range of applications in practice. Accordingly, information security issues have arisen. Aiming at security issues in Secure multi-party computation, we consider that semi-honest participants have malicious operations such as collusion in the process of information interaction, gaining an information advantage over honest parties through collusion which leads to deviations in the security of the protocol. To solve this problem, we combine information entropy to propose an n-round information exchange protocol, in which each participant broadcasts a relevant information value in each round without revealing additional information. Through the change of the uncertainty of the correct result value in each round of interactive information, each participant cannot determine the correct result value before the end of the protocol. security analysis shows that our protocol guarantees the security of the output obtained by the participants after the completion of the protocol.

关键词： Analytical models Protocols Uncertainty Computational modeling Information security Big data Multi-party computation

来源：评论

学校读者我要写书评

暂无评论

PRAD: Unsupervised KPI Anomaly Detection by Joint Prediction and Reconstruction of Multivariate Time Series

PRAD: Unsupervised KPI Anomaly Detection by Joint Prediction...

引用

Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Zhiying Xiong Qilin Fan Kai Wang Xiuhua Li Xu Zhang Qingyu Xiong School of Big Data and Software Engineering Chongqing University Chongqing China Chongqing Key Laboratory of Digital Cinema Art Theory and Technology Chongqing University Chongqing China School of Computer Science and Technology Harbin Institute of Technology Weihai China Research Institute of Cyberspace Security Harbin Institute of Technology Weihai China Haihe Laboratory of Information Technology Application Innovation Tianjin China Department of Computer Science University of Exeter Exeter UK

Detecting anomalies for key performance indicator (KPI) data is of paramount importance to ensure the quality and reliability of network services. However, building the anomaly detection system for KPI is challenging due to the scarcity of abnormal labels and highly dynamic or even unseen patterns. In this paper, we propose an unsupervised KPI anomaly detection framework named PRAD by jointly optimizing prediction-based and reconstruction-based modules. Specifically, PRAD employs two parallel graph attention networks (GATs) to learn metric-oriented and time-oriented relationships. A temporal convolutional attention network (TCAN) is used to capture complex long-term dependencies. Furthermore, to tackle the overfitting issue in the variational auto-encoder (VAE), PRAD designs a reconstruction-based module that combines VAE with a generative adversarial network (GAN). The experimental results on the two public datasets demonstrate that the proposed PRAD outperforms existing anomaly detection methods.

关键词：

来源：评论

学校读者我要写书评

暂无评论

JPEGCNN: A Transform Domain Steganalysis Model Based on Convolutional Neural Network 5th

JPEGCNN: A Transform Domain Steganalysis Model Based on Conv...

引用

5th International Conference on Artificial Intelligence and security, ICAIS 2019

作者： Gan, Lin Chen, Jingjie Chen, Yuling Jin, Zhujun Han, Wenxi School of Cyberspace Security Beijing University of Posts and Telecommunications Beijing China State Key Laboratory of Public Big Data GuiZhou University Guizhou China

ISBN: (纸本)9783030242671

Convolutional Neural Network (CNN) has gained an overwhelming advantage in many fields of pattern recognition. Both excellent data learning ability and automatic feature extraction ability of CNN are urgently needed in image steganalysis. However, the application of CNN in image steganalysis is still in its infancy, especially in the field of JPEG steganalysis. In this paper, a steganalysis model based on CNN in gray image transform domain is proposed, which is called JPEGCNN. At the same time, on the basis of JPEGCNN, JPEGCNN is extended to the transform domain of color image by researching and designing different methods of feature extraction. RGBMERGE-JPEGCNN and RGBADD-JPEGCNN are proposed respectively, which make up for the lack of research on steganalysis model based on convolution neural network in the transform domain of color image. Experiments show that JPEGCNN, RGBMERGE-JPEGCNN and RGBADD-JPEGCNN proposed in this paper have good detection ability for steganography algorithm in transform domain. © 2019, Springer Nature Switzerland AG.

关键词： Steganography

来源：评论

学校读者我要写书评

暂无评论

A Method of Network Topology Discovery Based on Knowledge Reasoning : Based on more than heterogeneous data sources

A Method of Network Topology Discovery Based on Knowledge Re...

引用

Computer Science and Management Technology (ICCSMT), International Conference on

作者： Jun Xu Yang Xin Runcheng Liu Cyberspace Security Institute School of Beijing University of Posts and Telecommunications Beijing China Cyberspace Security Institute Beijing University of Posts and Telecommunications Beijing China Guizhou Provincial Key Laboratory of Public Big Data Guizhou University Guizhou China

ISBN: (纸本)9781728186689;9781728186696

At present, the network has gradually become the foundation of information construction. People have more demands for network topology management. The increasing scale of network topology and the heterogeneity between devices and protocols have brought great difficulties to network topology discovery. This paper proposes a knowledge-based reasoning Network topology discovery method. This method uses multiple heterogeneous data sources, uses computer network prior knowledge to construct a knowledge base from top to bottom, uses inference learning to establish reasoning rules, and then constructs a multi-level network topology structure.

关键词： Knowledge engineering Couplings Protocols Network topology databases Fuses Knowledge based systems

来源：评论

学校读者我要写书评

暂无评论

MSpace: Multi security namespace management for containers

Journal of Engineering Research (Kuwait)

引用

Journal of Engineering Research (Kuwait) 2025年

作者： Liang, Hao He, Gongshan Jiang, Jinhu National Digital Switching System Engineering & Technological Research Center Zhengzhou 450002 China Key Laboratory of Cyberspace Security Ministry of Education Zhengzhou 450002 China School of Computer Science Fudan University Shanghai 200438 China Institute of Big Data Fudan University Shanghai 200433 China

Existing system security frameworks like LSM are primarily designed for the operating system kernel and are not applicable to user-level container methods. This is primarily because the system security framework is designed and implemented within the operating system kernel, which is shared across the entire system and cannot fulfill the isolation requirements of containers. The security policies of multiple containers are intermixed in the underlying system kernel, which impacts each other and increases the overhead of monitoring, leading to inefficiencies in cloud servers running numerous containers. Improvements to the security of containers are ad hoc and partial, often lacking support for the universal SELinux mode. In this paper, we introduce MSpace, an enhanced kernel SELinux framework that supports containerized secure spaces with individual security policies and mechanisms. To enhance security, we first introduce an instantiation mechanism for virtual hook tables, which, in conjunction with the container's namespace, ensures each has its own instantiated hook tables instead of a system-wide one, thereby isolating secure spaces. Subsequently, a security namespace method was devised to support container-specific private security policies. Lastly, to maintain compatibility, only the instantiation and deallocation interfaces were added while preserving the original interfaces unchanged. The results demonstrate that MSpace effectively alleviates the issue of using SELinux for internal containers, with an average reduction of 2.83 % in system call latency compared to using host SELinux directly. © 2025 The Authors

关键词： Container security MSpace SELinux System call latency Virtual jump tables

来源：评论

学校读者我要写书评

暂无评论

Dual Consistent Constraint via Disentangled Consistency and Complementarity for Multi-view Clustering

arXiv

引用

arXiv 2025年

作者： Li, Bo Yun, Jing College of Data Science and Application Inner Mongolia University of Technology Inner Mongolia Huhhot010080 China Inner Mongolia Autonomous Region Engineering and Technology Research Center of Big Data-Based Software Service Inner Mongolia Huhhot010080 China Inner Mongolia Key Laboratory of Beijiang Cyberspace Security Inner Mongolia Huhhot010080 China

Multi-view clustering can explore common semantics from multiple views and has received increasing attention in recent years. However, current methods focus on learning consistency in representation, neglecting the contribution of each view’s complementarity aspect in representation learning. This limit poses a significant challenge in multi-view representation learning. This paper proposes a novel multi-view clustering framework that introduces a disentangled variational autoencoder that separates multi-view into shared and private information, i.e., consistency and complementarity information. We first learn informative and consistent representations by maximizing mutual information across different views through contrastive learning. This process will ignore complementary information. Then, we employ consistency inference constraints to explicitly utilize complementary information when attempting to seek the consistency of shared information across all views. Specifically, we perform a within-reconstruction using the private and shared information of each view and a cross-reconstruction using the shared information of all views. The dual consistency constraints are not only effective in improving the representation quality of data but also easy to extend to other scenarios, especially in complex multi-view scenes. This could be the first attempt to employ dual consistent constraint in a unified MVC theoretical framework. During the training procedure, the consistency and complementarity features are jointly optimized. Extensive experiments show that our method outperforms baseline methods. © 2025, CC BY.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

VSRQ: Quantitative Assessment Method for Safety Risk of Vehicle Intelligent Connected System

arXiv

引用

arXiv 2023年

作者： Zhang, Tian Guan, Wenshan Miao, Hao Huang, Xiujie Liu, Zhiquan Wang, Chaonan Guan, Quanlong Fang, Liangda Duan, Zhifei Department of Cyberspace Security College of Information Science and Technology Jinan University Guangzhou511486 China Department of Computer Science College of Information Science and Technology Jinan University Guangzhou510632 China College of Information Science and Technology Jinan University Guangdong Institution of Smart Education Jinan University Guangzhou510632 China College of Cyber Security Jinan University Guangzhou510632 China Guangdong Gene Data Processing and Analysis Engineering Research Center China Pazhou Laboratory Guangzhou510330 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin541004 China Guangzhou XPeng Motors Technology Co. Ltd No.8 Songgang Road Changxing Street Cencun Tianhe District Guangzhou China

The field of intelligent connected in modern vehicles continues to expand, and the functions of vehicles become more and more complex with the development of the times. This has also led to an increasing number of vehicle vulnerabilities and many safety issues. Therefore, it is particularly important to identify high-risk vehicle intelligent connected systems, because it can inform security personnel which systems are most vulnerable to attacks, allowing them to conduct more thorough inspections and tests. In this paper, we develop a new model for vehicle risk assessment by combining I-FAHP with FCA clustering: VSRQ model. We extract important indicators related to vehicle safety, use fuzzy cluster analys (FCA) combined with fuzzy analytic hierarchy process (FAHP) to mine the vulnerable components of the vehicle intelligent connected system, and conduct priority testing on vulnerable components to reduce risks and ensure vehicle safety. We evaluate the model on OpenPilot and experimentally demonstrate the effectiveness of the VSRQ model in identifying the safety of vehicle intelligent connected systems. The experiment fully complies with ISO 26262 and ISO/SAE 21434 standards, and our model has a higher accuracy rate than other models. These results provide a promising new research direction for predicting the security risks of vehicle intelligent connected systems and provide typical application tasks for VSRQ. The experimental results show that the accuracy rate is 94.36%, and the recall rate is 73.43%, which is at least 14.63% higher than all other known indicators. Copyright © 2023, The Authors. All rights reserved.

关键词： Vehicle safety

来源：评论

学校读者我要写书评

暂无评论

Blockchain Private key Storage Algorithm Based on Image Information Hiding 5th

Blockchain Private Key Storage Algorithm Based on Image Info...

引用

5th International Conference on Artificial Intelligence and security, ICAIS 2019

作者： Wang, Ning Chen, Yuling Yang, Yu Fang, Zigang Sun, Yizhe School of Cyberspace Security Beijing University of Posts and Telecommunications Beijing China State Key Laboratory of Public Big Data GuiZhou University GuiyangGuizhou China

ISBN: (纸本)9783030242671

The private key is the unique credential of the blockchain asset and can be used to sign and authenticate transactions. Losing the private key also loses the control of the account, so the leakage of the private key is one of the major factors affecting the security of the blockchain. In order to improve the security of blockchain private key storage technology in transactions, this paper proposes a blockchain private key storage algorithm based on image information hiding. In order to improve the camouflage ability and reduce the bit error rate, the algorithm adds random numbers and error correction code to the original private key to provide double protection. After generating the watermark information, the watermark information is embedded into the digital image by means of discrete wavelet transform and quantized index modulation to realize the process of information hiding. Finally, it is proved that this algorithm has good transparency and robustness, can hide the private key information visually, and extract it accurately. © 2019, Springer Nature Switzerland AG.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

PPCSB: A Privacy-Preserving Electricity Consumption Statistics and Billing Scheme in Smart Grid 5th

PPCSB: A Privacy-Preserving Electricity Consumption Statisti...

引用

5th International Conference on Artificial Intelligence and security, ICAIS 2019

作者： Li, Chenyang Chen, Yuling Yang, Yu Li, Chaochao Zeng, Yang School of Cyberspace Security Beijing University of Posts and Telecommunications Beijing China State Key Laboratory of Public Big Data GuiZhou University GuiyangGuizhou China

ISBN: (纸本)9783030242671

Research on the privacy protection of smart grids mostly stays in fixed electricity prices or electricity aggregation. Aiming at the problem of real-time pricing and privacy data protection of smart grid, this paper proposes a privacy-preserving electricity consumption statistics and billing scheme in smart grid (PPCSB). In this scheme, the techniques of additive homomorphic encryption and mixed multiplicative homomorphic encryption are used to ensure the security of the data communication;Batch verification is used to improve the efficiency of signature verification. In addition, the proposed scheme does not require a trusted third party in order to improve the usability of the scheme. Through performance analysis of the scheme, it shows that the scheme has better security and better functions. © 2019, Springer Nature Switzerland AG.

关键词： Smart power grids

来源：评论

学校读者我要写书评

暂无评论

Heuristic-Q: A Privacy data Pricing Method Based on Heuristic Reinforcement Learning 5th

Heuristic-Q: A Privacy Data Pricing Method Based on Heuristi...

引用

5th International Conference on Artificial Intelligence and security, ICAIS 2019

作者： Chen, Xi Chen, Jingjie Chen, Yuling Yang, Jinglan Li, Deyin School of Cyberspace Security Beijing University of Posts and Telecommunications Beijing China State Key Laboratory of Public Big Data Guizhou University GuiyangGuizhou China

ISBN: (纸本)9783030242671

With the development of big data applications in recent years, the value of personal data has received more and more attention. How to balance the conflict between data value development and personal privacy protection is an urgent problem to be solved. In response to the above contradictions, the market proposed a private data transaction mechanism to realize the commercial use of private data. However, existing private data transaction mechanisms still have deficiencies in some respects. In order to seek pricing strategies that maximize total revenue, this paper designs and constructs a privacy data dynamic pricing model from the perspective of data collectors, introduces heuristic reinforcement learning ideas, and proposes a pricing strategy algorithm based on heuristic functions. Finally, the simulation experiment of the proposed pricing model and strategy learning algorithm is carried out, and its performance is analyzed. The simulation results confirm that the algorithm can help data collectors get higher returns in the process of limited private data transactions. © 2019, Springer Nature Switzerland AG.

关键词： Reinforcement learning

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：