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Trusted Certified Auditor Using Cryptography for Secure Data Outsourcing and privacy preservation in Fog-Enabled VANETs

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Computers, Materials & Continua 2024年第5期79卷 3089-3110页

作者： Nagaraju Pacharla K.Srinivasa Reddy School of Computer Science and Engineering VIT-AP UniversityAmaravatiAndhra Pradesh522237India

With the recent technological developments,massive vehicular ad hoc networks(VANETs)have been established,enabling numerous vehicles and their respective Road Side Unit(RSU)components to communicate with oneanother.The best way to enhance traffic flow for vehicles and traffic management departments is to share thedata they receive.There needs to be more protection for the VANET systems.An effective and safe methodof outsourcing is suggested,which reduces computation costs by achieving data security using a homomorphicmapping based on the conjugate operation of matrices.This research proposes a VANET-based data outsourcingsystem to fix the issues.To keep data outsourcing secure,the suggested model takes cryptography models intoaccount.Fog will keep the generated keys for the purpose of vehicle authentication.For controlling and overseeingthe outsourced data while preserving privacy,the suggested approach considers the Trusted Certified Auditor(TCA).Using the secret key,TCA can identify the genuine identity of VANETs when harmful messages aredetected.The proposed model develops a TCA-based unique static vehicle labeling system using cryptography(TCA-USVLC)for secure data outsourcing and privacy preservation in VANETs.The proposed model calculatesthe trust of vehicles in 16 ms for an average of 180 vehicles and achieves 98.6%accuracy for data encryption toprovide security.The proposedmodel achieved 98.5%accuracy in data outsourcing and 98.6%accuracy in privacypreservation in fog-enabled VANETs.Elliptical curve cryptography models can be applied in the future for betterencryption and decryption rates with lightweight cryptography operations.

关键词： Vehicular ad-hoc networks data outsourcing privacy preservation cryptography keys trusted certified auditors data security

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Enhanced Clustering Based OSN privacy preservation to Ensure k-Anonymity, t-Closeness, l-Diversity, and Balanced privacy Utility

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Computers, Materials & Continua 2023年第4期75卷 2171-2190页

作者： Rupali Gangarde Amit Sharma Ambika Pawar Department of CSE Lovely Professional UniversityPhagwara144411India Department of CSE Symbiosis Institute of Technology(SIT)Affiliated to Symbiosis International(Deemed University)Pune412115India School of Computer Applications Lovely Professional UniversityPhagwara144411India Learning&Development Persistent UniversityPersistent SystemsPune411057India

Online Social Networks (OSN) sites allow end-users to share agreat deal of information, which may also contain sensitive information,that may be subject to commercial or non-commercial privacy attacks. Asa result, guaranteeing various levels of privacy is critical while publishingdata by OSNs. The clustering-based solutions proved an effective mechanismto achieve the privacy notions in OSNs. But fixed clustering limits theperformance and scalability. Data utility degrades with increased privacy,so balancing the privacy utility trade-off is an open research issue. Theresearch has proposed a novel privacy preservation model using the enhancedclustering mechanism to overcome this issue. The proposed model includesphases like pre-processing, enhanced clustering, and ensuring privacy preservation.The enhanced clustering algorithm is the second phase where authorsmodified the existing fixed k-means clustering using the threshold approach.The threshold value is determined based on the supplied OSN data of edges,nodes, and user attributes. Clusters are k-anonymized with multiple graphproperties by a novel one-pass algorithm. After achieving the k-anonymityof clusters, optimization was performed to achieve all privacy models, suchas k-anonymity, t-closeness, and l-diversity. The proposed privacy frameworkachieves privacy of all three network components, i.e., link, node, and userattributes, with improved utility. The authors compare the proposed techniqueto underlying methods using OSN Yelp and Facebook datasets. The proposedapproach outperformed the underlying state of art methods for Degree ofAnonymization, computational efficiency, and information loss.

关键词： Enhanced clustering online social network k-anonymity t-closeness l-diversity privacy preservation

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A Holistic Secure Communication Mechanism Using a Multilayered Cryptographic Protocol to Enhanced Security

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Computers, Materials & Continua 2024年第3期78卷 4417-4452页

作者： Fauziyah Zhaoshun Wang Mujahid Tabassum School of Computer and Communication Engineering University of Science and TechnologyBeijing100000China Noroff School of Technology and Digital Media(Noroff Accelerate) Noroff University CollegeKristiansand4612Norway

In an era characterized by digital pervasiveness and rapidly expanding datasets,ensuring the integrity and reliability of information is paramount.As cyber threats evolve in complexity,traditional cryptographic methods face increasingly sophisticated challenges.This article initiates an exploration into these challenges,focusing on key exchanges(encompassing their variety and subtleties),scalability,and the time metrics associated with various cryptographic processes.We propose a novel cryptographic approach underpinned by theoretical frameworks and practical engineering.Central to this approach is a thorough analysis of the interplay between Confidentiality and Integrity,foundational pillars of information security.Our method employs a phased strategy,beginning with a detailed examination of traditional cryptographic processes,including Elliptic Curve Diffie-Hellman(ECDH)key exchanges.We also delve into encrypt/decrypt paradigms,signature generation modes,and the hashes used for Message Authentication Codes(MACs).Each process is rigorously evaluated for performance and reliability.To gain a comprehensive understanding,a meticulously designed simulation was conducted,revealing the strengths and potential improvement areas of various techniques.Notably,our cryptographic protocol achieved a confidentiality metric of 9.13 in comprehensive simulation runs,marking a significant advancement over existing methods.Furthermore,with integrity metrics at 9.35,the protocol’s resilience is further affirmed.These metrics,derived from stringent testing,underscore the protocol’s efficacy in enhancing data security.

关键词： Cryptographic security privacy preservation decryption integrity

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2P3FL:A Novel Approach for privacy Preserving in Financial Sectors Using Flower Federated Learning

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 2035-2051页

作者： Sandeep Dasari Rajesh Kaluri School of Computer Science Engineering and Information Systems Vellore Institute of TechnologyVellore632014India

The increasing data pool in finance sectors forces machine learning(ML)to step into new complications.Banking data has significant financial implications and is confidential.Combining users data from several organizations for various banking services may result in various intrusions and privacy leakages.As a result,this study employs federated learning(FL)using a flower paradigm to preserve each organization’s privacy while collaborating to build a robust shared global model.However,diverse data distributions in the collaborative training process might result in inadequate model learning and a lack of privacy.To address this issue,the present paper proposes the imple-mentation of Federated Averaging(FedAvg)and Federated Proximal(FedProx)methods in the flower framework,which take advantage of the data locality while training and guaranteeing global convergence.Resultantly improves the privacy of the local models.This analysis used the credit card and Canadian Institute for Cybersecurity Intrusion Detection Evaluation(CICIDS)datasets.Precision,recall,and accuracy as performance indicators to show the efficacy of the proposed strategy using FedAvg and FedProx.The experimental findings suggest that the proposed approach helps to safely use banking data from diverse sources to enhance customer banking services by obtaining accuracy of 99.55%and 83.72%for FedAvg and 99.57%,and 84.63%for FedProx.

关键词： Federated learning FedAvg FedProx flower framework privacy preservation financial sectors

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Semi-Homogenous Generalization： Improving Homogenous Generalization for privacy preservation in Cloud Computing

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Journal of Computer Science & Technology 2016年第6期31卷 1124-1135页

作者： Xian-Mang He Xiaoyang SeanWang Dong Li Yan-Ni Hao School of Information Science and Engineering Ningbo University Ningbo 315211 China School of Computer Science Fudan University Shanghai 200433 China Information Center National Natural Science Foundation of China Beijing 100085 China

Data security is one of the leading concerns and primary challenges for cloud computing. This issue is getting more and more serious with the development of cloud computing. However, the existing privacy-preserving data sharing techniques either fail to prevent the leakage of privacy or incur huge amounts of information loss. In this paper, we propose a novel technique, termed as linking-based anonymity model, which achieves K-anonymity with quasi-identifiers groups （QI-groups） having a size less than K. In the meanwhile, a semi-homogenous generalization is introduced to be against the attack incurred by homogenous generalization. To implement linking-based anonymization model, we propose a simple yet efficient heuristic local recoding method. Extensive experiments on real datasets are also conducted to show that the utility has been significantly improved by our approach compared with the state-of-the-art methods.

关键词： privacy preservation cloud computing linking-based anonymization semi-homogenous homogenous generalization

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EDA: an enhanced dual-active algorithm for location privacy preservation in mobile P2P networks

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Journal of Zhejiang University-Science C(Computers and Electronics) 2013年第5期14卷 356-373页

作者： Yan-zhe CHE Kevin CHIEW Xiao-yan HONG Qiang YANG Qin-ming HE College of Computer Science and Technology Zhejiang University School of Engineering Tan Tao University Department of Computer Science University of Alabama College of Electrical Engineering Zhejiang University

Various solutions have been proposed to enable mobile users to access location-based services while preserving their location privacy. Some of these solutions are based on a centralized architecture with the participation of a trustworthy third party, whereas some other approaches are based on a mobile peer-to-peer (P2P) architecture. The former approaches suffer from the scalability problem when networks grow large, while the latter have to endure either low anonymization success rates or high communication overheads. To address these issues, this paper deals with an enhanced dual-active spatial cloaking algorithm (EDA) for preserving location privacy in mobile P2P networks. The proposed EDA allows mobile users to collect and actively disseminate their location information to other users. Moreover, to deal with the challenging characteristics of mobile P2P networks, e.g., constrained network resources and user mobility, EDA enables users (1) to perform a negotiation process to minimize the number of duplicate locations to be shared so as to significantly reduce the communication overhead among users, (2) to predict user locations based on the latest available information so as to eliminate the inaccuracy problem introduced by using some out-of-date locations, and (3) to use a latest-record-highest-priority (LRHP) strategy to reduce the probability of broadcasting fewer useful locations. Extensive simulations are conducted for a range of P2P network scenarios to evaluate the performance of EDA in comparison with the existing solutions. Experimental results demonstrate that the proposed EDA can improve the performance in terms of anonymity and service time with minimized communication overhead.

关键词： Location-based service privacy preservation Spatial cloaking Mobile peer-to-peer networks

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Implicit privacy preservation:a framework based on data generation

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Security and Safety 2022年第1期1卷 166-183页

作者： Qing Yang Cheng Wang Teng Hu Xue Chen Changjun Jiang Key Laboratory of Embedded System and Service Computing(Tongji University) Ministry of EducationShanghai 201804China National(Province-Ministry Joint)Collaborative Innovation Center for Financial Network Security Tongji UniversityShanghai 201804China

This paper addresses a special and imperceptible class of privacy,called implicit privacy.In contrast to traditional(explicit)privacy,implicit privacy has two essential properties:(1)It is not initially de ned as a privacy attribute;(2)it is strongly associated with privacy attributes.In other words,attackers could utilize it to infer privacy attributes with a certain probability,indirectly resulting in the disclosure of private information.To deal with the implicit privacy disclosure problem,we give a measurable de nition of implicit privacy,and propose an ex-ante implicit privacy-preserving framework based on data generation,called IMPOSTER.The framework consists of an implicit privacy detection module and an implicit privacy protection module.The former uses normalized mutual information to detect implicit privacy attributes that are strongly related to traditional privacy attributes.Based on the idea of data generation,the latter equips the Generative Adversarial Network(GAN)framework with an additional discriminator,which is used to eliminate the association between traditional privacy attributes and implicit ones.We elaborate a theoretical analysis for the convergence of the framework.Experiments demonstrate that with the learned generator,IMPOSTER can alleviate the disclosure of implicit privacy while maintaining good data utility.

关键词： privacy preservation Implicit privacy Generative adversarial network Data utility Data generation

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Research of privacy preservation Method Based on Data Coloring

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China Communications 2016年第10期13卷 181-197页

作者： Bilin Shao Genqing Bian Xirui Quan Zhixian Wang School of Management Xi'an University of Architecture and Technology School of Information and Control Engineering Xi'an University of Architecture and Technology School of Information Engineering Yulin University

In the cloud computing environment, outsourcing service mode of data storage causes the security problem, the reliability of data cannot be guaranteed, and the privacy preservation problem has aroused wide concern. In order to solve the problem of inefficiency and high-complexity caused by traditional privacy preservation methods such as data encryption and access control technology, a privacy preservation method based on data coloring is proposed. The data coloring model is established and the coloring mechanism is adopted to deal with the sensitive data of numerical attributes, and the cloud model similarity measurement based on arithmetic average least-approximability is adopted to authenticate the ownership of privacy data. On the premise of high availability of data, the method strengthens the security of the privacy information. Then, the performance, validity and the parameter errors of the algorithm are quantitatively analyzed by the experiments using the UCI dataset. Under the same conditions of privacy preservation requirements, the proposed method can track privacy leakage efficiently and reduce privacy leakage risks. Compared with the k-anonymity approach, the proposed method enhances the computational time efficiency by 18.5%.

关键词： data coloring privacy preservation cloud model cloud similarity

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ENHANCING privacy preservation FRAMEWORK IN DISTRIBUTED TRUST MODEL

ENHANCING PRIVACY PRESERVATION FRAMEWORK IN DISTRIBUTED TRUS...

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第八届分布式计算及其应用国际学术研讨会

作者： Yusheng Zhong1 Bo Yang 2 Mingwu Zhang 3 Wenzheng Zhang 4 123College of Informatics South China Agriculture UniversityGuangzhou Guangdong 510642 China 4 National Laboratory for Modern CommunicationsChengdu Sichuan 610041 China

Distributed trust management implements authorization, delegation,and access control with a decentralized and flexible manner.Credentials submitting and policies interacting will disclose owner’s sensitive attributes and privacy.In this paper, several solutions about establishing trust with privacy preserving are introduced,including secure and anonymous credentials,sensitive policies,balance of trust and privacy,risk analyzing and evaluating.The privacy enhancing frameworks for trust establishing are described to enforce the trust and privacy balance.Several potential solutions are also proposed and discussed.

关键词： Trust Management Credential Sensitive Policy privacy preservation

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privacy preservation of Smart Meters Based on Identity Authentication

Privacy Preservation of Smart Meters Based on Identity Authe...

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作者： Hongbo Hu Xin Zhao Yalian Wu Mengbiao Huang Ziqi Zhu Qingyu Yang College of Information Engineering Xiangtan University

Smart meters provide a lot of convenience for both power supply and consumption. Due to the frequent transmission of information, it brings great challenges to the privacy preservation of the user’s household power consumption data in the smart grid. In order to achieve the anonymity of smart meters. A smart meter privacy preservation scheme based on identity authentication is proposed. The third-party certification authority is introduced in this scheme;it issues pseudonym certificates to realize the identity privacy preservation of smart meters. The masking technology with the Advanced Encryption Standard algorithm is used for data aggregation. The results show that our scheme reduces the computational cost and the communication overhead.

关键词： Smart Meter Identity Authentication privacy preservation Masking Technology

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