检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Song, Jialei Zuo, Xingquan Wang, Feiyang Huang, Hai Zhang, Tianle Shool of Computer Science Beijing University of Posts and Telecommunications Beijing China Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing China Shool of Cyberspace Security Beijing University of Posts and Telecommunications Beijing China

Deep neural networks (DNNs) are highly susceptible to adversarial samples, raising concerns about their reliability in safety-critical tasks. Currently, methods of evaluating adversarial robustness are primarily categorized into attack-based and certified robustness evaluation approaches. The former not only relies on specific attack algorithms but also is highly time-consuming, while the latter due to its analytical nature, is typically difficult to implement for large and complex models. A few studies evaluate model robustness based on the model’s decision boundary, but they suffer from low evaluation accuracy. To address the aforementioned issues, we propose a novel adversarial robustness evaluation metric, Robustness Difference Index (RDI), which is based on sample clustering features. RDI draws inspiration from clustering evaluation by analyzing the intra-class and inter-class distances of feature vectors separated by the decision boundary to quantify model robustness. It is attack-independent and has high computational efficiency. Experiments show that, RDI demonstrates a stronger correlation with the gold-standard adversarial robustness metric of attack success rate (ASR). The average computation time of RDI is only 1/30 of the evaluation method based on the PGD attack. Our open-source code is available at: https://***/r/RDI-B1DA. Copyright © 2025, The Authors. All rights reserved.

关键词： Open systems

来源：评论

学校读者我要写书评

暂无评论

XThe Application of Robot Localization and Navigation Based on WSN in the Disaster Relief

XThe Application of Robot Localization and Navigation Based ...

引用

作者： Cui, Xiaoyan Chen, Xiaoshuang Shi, Wei Zhang, Yi Key Laboratory of Trustworthy Distributed Computing and Service Automation School BUPT China

ISBN: (纸本)9783642357947

Disasters always disturb our normal life, and the loss is immeasurable. In this paper, we intend to find a new way to reduce the harm. We select the wireless sensor network to control the robot localization and navigation in the disaster relief. This paper means to design a pre-disaster monitoring and reconstruct network with new nodes added in the network, and robot position & navigation, and also build a post-disaster history disaster mode. This paper also takes consider of the actual result of the node energy consumption. It has practical significance. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Robots

来源：评论

学校读者我要写书评

暂无评论

An Effective Cloud Workflow Scheduling Approach Combining PSO and Idle Time Slot-Aware Rules

引用

IEEE/CAA Journal of Automatica Sinica 2021年第5期8卷 1079-1094页

作者： Yun Wang Xingquan Zuo the School of Computing Science Beijing University of Posts and TelecommunicationsBeijing 100876China the School of Information Engineering Nanchang Institute of TechnologyNanchang 330099China the Key Laboratory of Trustworthy Distributed Computing and Service(BUPT) Ministry of EducationBeijing 100876China

Workflow scheduling is a key issue and remains a challenging problem in cloud *** with the large number of virtual machine(VM)types offered by cloud providers,cloud users need to choose the most appropriate VM type for each *** task scheduling sequences exist in a workflow *** task scheduling sequences have a significant impact on the scheduling *** is not easy to determine the most appropriate set of VM types for tasks and the best task scheduling ***,the idle time slots on VM instances should be used fully to increase resources'utilization and save the execution cost of a *** paper considers these three aspects simultaneously and proposes a cloud workflow scheduling approach which combines particle swarm optimization(PSO)and idle time slot-aware rules,to minimize the execution cost of a workflow application under a deadline constraint.A new particle encoding is devised to represent the VM type required by each task and the scheduling sequence of *** idle time slot-aware decoding procedure is proposed to decode a particle into a scheduling *** handle tasks'invalid priorities caused by the randomness of PSO,a repair method is used to repair those priorities to produce valid task scheduling *** proposed approach is compared with state-of-the-art cloud workflow scheduling *** show that the proposed approach outperforms the comparative algorithms in terms of both of the execution cost and the success rate in meeting the deadline.

关键词： Cloud computing idle time slot particle swarm optimization task scheduling sequence workflow scheduling

来源：评论

学校读者我要写书评

暂无评论

A recommendation algorithm based on adaptive privacy protection 9

A recommendation algorithm based on adaptive privacy protect...

引用

9th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, ISAEECE 2024

作者： Song, Yiyang Li, Xiaoyong Yuan, Kaiguo Kong, Weiyu Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9781510683303

Differential privacy, as a provable privacy protection framework, has been widely applied in recommendation systems. However, the integration of existing collaborative filtering algorithms with differential privacy typically encounters two issues. Firstly, algorithms often use the same privacy budget for data from different time periods, introducing unnecessary noise and reducing performance. Secondly, when using gradient descent to solve collaborative filtering models, the allocation of privacy budgets is relatively simple, usually evenly distributed across each iteration. This allocation requires a predefined number of iterations. If the number is too small, the algorithm may terminate before reaching the optimal solution;if too large, each budget per iteration may be too small, leading to excessive noise. To address these issues, an adaptive privacy budget recommendation algorithm is proposed. Firstly, a dynamic time window-based privacy budget calculation algorithm is utilized to provide varying levels of privacy protection for rating data from different time periods, thus avoiding unnecessary noise. Then, an adaptive privacy budget gradient descent strategy is employed to solve the collaborative filtering model, which dynamically allocates privacy budgets based on the noise gradient of each round. This algorithm is compared with existing differential privacy-based recommendation algorithms on the Movielens-1M dataset, demonstrating superior predictive accuracy and lower sensitivity to privacy protection. © 2024 SPIE.

关键词： Differential privacy

来源：评论

学校读者我要写书评

暂无评论

Multi-Agent Trust Evaluation Model based on Reinforcement Learning 8

Multi-Agent Trust Evaluation Model based on Reinforcement Le...

引用

8th International Conference on Dependable Systems and Their Applications, DSA 2021

作者： Haoran, Jia Yuyu, Yuan Qiang, Han Pengqian, Zhao Ting, Guo Ministry of Education Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications China

ISBN: (纸本)9781665443913

The establishment of trust between agents is an important part of Multi-agent Reinforcement Learning (MARL). Recent studies on multi-agents have paid more attention to the game relationship between agents, ignoring trust is the basis of cooperation among agents. In this article, we propose a trust evaluation model in MARL to evaluate the trustworthiness of the target agent. The trust evaluation of the target agent is composed of direct trust and reputation. Direct trust is obtained from the historical interaction of agents. Reputation is to evaluate the impact of an agent's behavior by counterfactual action of a high-ranking agent. In addition, this paper also proposes a trust-based reward mechanism in MARL, which divides agent rewards into environmental rewards and trust rewards. Trust rewards are obtained through trust evaluation values, which drive the agents to reach a cooperative state and obtain higher long-term rewards. In this paper, we set up experiments in harvest game to verify that the trust evaluation model can effectively promote the cooperation of agents and avoid the problem of agents facing social dilemmas. © 2021 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Browser Fingerprint Linking Based on Transformer-encoder Model

Browser Fingerprint Linking Based on Transformer-encoder Mod...

引用

2023 International Conference on Computer Network Security and Software Engineering, CNSSE 2023

作者： Tan, Yun Li, Xiaoyong Si, Xiaotian Li, Linghui Gao, Yali Yuan, Jie Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (数字)9781510666528

ISBN: (纸本)9781510666511

Browser fingerprinting has been used as a user-tracking technique in recent years. As a long-term tracking technique, it requires not only obtaining unique browser fingerprints but also linking fingerprints from the same browser instance in that browsers change rapidly and frequently. To improve the efficiency of linking the evolving browser fingerprints, in this paper, we propose a browser fingerprint linking method based on Transformer-encoder. Transformer-encoder utilizes an attention mechanism to focus on certain parts of the input sequence, enabling it to capture complex connections and interactions within the data more efficiently. To make the most of the parallel processing mechanism of the Transformer-encoder, we combine multiple fingerprint comparison vectors into an input vector to train the model. We conduct extensive experiments on a public dataset to evaluate our proposed model. The experimental results show that our model outperforms some existing models, which proves the effectiveness of the Transformer-encoder in linking browser fingerprints. © 2023 SPIE.

关键词： Tracking (position)

来源：评论

学校读者我要写书评

暂无评论

NFT Security Matrix:Towards Modeling NFT Ecosystem Threat

引用

Computer Modeling in Engineering & Sciences 2024年第6期139卷 3255-3285页

作者： Peng Liao Chaoge Liu Jie Yin Zhi Wang Xiang Cui Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and TelecommunicationsBeijing100876China Zhongguancun Laboratory Beijing100094China Institute of Information Engineering Chinese Academy of SciencesBeijing100085China

Digital assets have boomed over the past few years with the emergence of Non-fungible Tokens(NFTs).To be specific,the total trading volume of digital assets reached an astounding$55.5 billion in ***,numerous security concerns have been raised by the rapid expansion of the NFT *** holders are exposed to a plethora of scams and traps,putting their digital assets at risk of being ***,academic research on NFT security is scarce,and the security issues have aroused rare *** this study,the NFT ecological process is comprehensively *** process falls into five different stages encompassing the entire lifecycle of ***,the security issues regarding the respective stage are elaborated and analyzed in depth.A matrix model is proposed as a novel contribution to the categorization of NFT security *** data are collected from social networks,the Ethereum blockchain,and NFT markets to substantiate our claims regarding the severity of security concerns in the NFT *** this comprehensive dataset,nine key NFT security issues are identified from the matrix model and then subjected to qualitative and quantitative *** study aims to shed light on the severity of NFT ecosystem security *** findings stress the need for increased attention and proactive measures to safeguard the NFT ecosystem.

关键词： Non-fungible token blockchain cyber security

来源：评论

学校读者我要写书评

暂无评论

A Secure Interaction and Control Method for InterClouds services

引用

China Communications 2015年第S2期12卷 132-137页

作者： GAN Jiefu PENG Li LU Yueming China Information Security Certification Center School of Information and Communication Engineering Beijing University of Posts and Telecommunications Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education

Inter-clouds services build information bridges over computing clouds so as to provide the convenience for electronic commerce and other information services. However, the interactions between clouds have challenges in information disclosure, services spoofing and information inconsistent. This paper proposes a secure interaction and control method for inter-clouds services, which uses information encryption, digital signature,time logic control means, to protect users' privacy and keep the integrity and consistency of cloud customers' request information, and prevent the spoofing of information requests. The results show that the method could prevent the spoofing well in a stable network environment and improve the security of clouds sessions.

关键词： inter-clouds services encryption signature spoofing

来源：评论

学校读者我要写书评

暂无评论

Game-theoretic private blockchain design in edge computing networks

引用

Digital Communications and Networks 2024年第6期10卷 1622-1634页

作者： Daoqi Han Yang Liu Fangwei Zhang Yueming Lu Key Laboratory of Trustworthy Distributed Computing and Service Ministry of EducationBeijing University of Posts and Telecommunications(BUPT)Beijing 100876China Beijing Institute of Astronautical Systems Engineering BeijingChina Beijing Institute of Technology BeijingChina

Considering the privacy challenges of secure storage and controlled flow,there is an urgent need to realize a decentralized ecosystem of private blockchain for cyberspace.A collaboration dilemma arises when the participants are self-interested and lack feedback of complete *** blockchains have similar faults,such as trustlessness,single-factor consensus,and heavily distributed ledger,preventing them from adapting to the heterogeneous and resource-constrained Internet of *** this paper,we develop the game-theoretic design of a two-sided rating with complete information feedback to stimulate collaborations for private *** design consists of an evolution strategy of the decision-making network and a computing power network for continuously verifiable *** formulate the optimum rating and resource scheduling problems as two-stage iterative games between participants and *** theoretically prove that the Stackelberg equilibrium exists and the group evolution is ***,we propose a multi-stage evolution consensus with feedback on a block-accounting workload for metadata *** continuously validate a block,the metadata of the optimum rating,privacy,and proofs are extracted to store on a lightweight ***,to increase resource utilization,surplus computing power is scheduled flexibly to enhance security by ***,the evaluation results show the validity and efficiency of our model,thereby solving the collaboration dilemma in the private blockchain.

关键词： Ecosystem Edge computing Feedback Stackelberg game Private blockchain Scalable computing power

来源：评论

学校读者我要写书评

暂无评论

Robust text clustering with graph and textual adversarial learning 5

Robust text clustering with graph and textual adversarial le...

引用

5th IEEE International Conference on Data Science in Cyberspace, DSC 2020

作者： Liang, Yongming Tian, Tian Jin, Kaifu Yang, Xiaoyu Lv, Yuefei Zhang, Xi Beijing University of Posts and Telecommunications Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing China

ISBN: (纸本)9781728195582

Text clustering is a fundamental task that finds groups of similar texts in the corpus. Deep learning based models can capture the semantic and syntactic information in local word sequences to represent the texts but may ignore global text structures in the corpus. Recently, Graph Convolutional Networks (GCNs) have achieved the state-of-the-art performance in many applications, which may facilitate the text clustering task by exploiting the graph structures between texts via words and phrases. However, GCNs are vulnerable to adversarial attacks, e.g., small perturbations in graph structures and node attributes lead to poor performance. To address this issue, we propose a Robust Text Clustering (RTC) approach which consists of both autoencoder and GCN modules to exploit the local text features and global text structures respectively in one unified framework. We generate two types of adversarial perturbations targeting text structure and graph structure, and develop an adversarial training method to improve the robustness and generalization of the RTC framework. Extensive experiments on two real-world datasets demonstrate the effectiveness of our proposal in text clustering. © 2020 IEEE.

关键词： Semantics

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：