2023 7th International Conference on Cryptography, Security and Privacy (CSP)最新文献_第2页

A Multi-Strategy Adversarial Attack Method for Deep Learning Based Malware Detectors 基于深度学习的恶意软件检测器多策略对抗攻击方法

2023 7th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2023-04-01 DOI: 10.1109/CSP58884.2023.00018

Wang Yang, Fan Yin

引用次数: 0

Efficient Privacy-Preserving Data Aggregation for Lightweight Secure Model Training in Federated Learning 联邦学习中轻量级安全模型训练的高效隐私保护数据聚合

2023 7th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2023-04-01 DOI: 10.1109/CSP58884.2023.00026

Cong Hu, Shuang Wang, Cuiling Liu, T. Zhang

{"title":"Efficient Privacy-Preserving Data Aggregation for Lightweight Secure Model Training in Federated Learning","authors":"Cong Hu, Shuang Wang, Cuiling Liu, T. Zhang","doi":"10.1109/CSP58884.2023.00026","DOIUrl":"https://doi.org/10.1109/CSP58884.2023.00026","url":null,"abstract":"Federated learning has been widely adopted in every aspect of our daily life to well protect the dataset privacy, since the model parameters are trained locally and aggregated to global one, but the data themselves are not required to be sent to servers as traditional machine learning. In State Grid, different power companies tend to cooperate to train a global model to predict the risk of the grid or the trustworthiness of the customers in the future. The datasets belonging to each power company should be protected against another corporation, sector or other unauthorized entities, since they are closely related to users' privacy. On the other hand, it is widely reported even the local mode parameters can also be exploited to launch several attacks such as membership inference. Most existing work to realize privacy-preserving model aggregation relies on computationally intensive public key homomorphic encryption(HE) such as Paillier's cryptosystem, which loads intolerably high complexity on resource-constrained local users. To address this challenging issue, in this paper, a lightweight privacy-preserving data aggregation scheme is proposed without utilizing public-key homomorphic encryption. First, an efficient privacy-preserving data aggregation protocol PPDA is proposed based on any one-way trapdoor permutation in the multiple user setting. Then, based on PPDA, a lightweight secure model training scheme LSMT in federated learning is designed. Finally, security analysis and extensive simulations show that our proposed PPDA and LSMT well protect the sensitive data of power enterprises from collusion attacks, guarantees the security of aggregated results, and outperforms existing ones in terms of computational and communication overhead.","PeriodicalId":255083,"journal":{"name":"2023 7th International Conference on Cryptography, Security and Privacy (CSP)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126556633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Computation on Jacobians of Hyperelliptic Curves of Genus 3 3属超椭圆曲线雅可比矩阵的计算

2023 7th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2023-04-01 DOI: 10.1109/CSP58884.2023.00032

Zhili Dong, Minzhong Luo, Chang Lv

引用次数: 0

Secure Multiparty Computation with Identifiable Abort and Fairness 具有可识别中止和公平性的安全多方计算

2023 7th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2023-04-01 DOI: 10.1109/CSP58884.2023.00023

Long Nie, ShaoWen Yao, J. Liu

{"title":"Secure Multiparty Computation with Identifiable Abort and Fairness","authors":"Long Nie, ShaoWen Yao, J. Liu","doi":"10.1109/CSP58884.2023.00023","DOIUrl":"https://doi.org/10.1109/CSP58884.2023.00023","url":null,"abstract":"Dishonest majority considered in the SPDZ(the nickname of the protocol of Damgard et al. from Crypto 2012) protocols implies the impossibility of fairness(which means that corrupted parties can prevent the honest parties from learning output). The corrupted parties can learn the outputs of the honest parties and abort the protocol. Settling for the second best, there are many works focusing on the detection of the cheaters. We construct a SPDZ-like protocol which achieves fairness when at most $n/2$ parties behave maliciously and supports identifiable abort for dishonest majority. We suggest a sharing stage after the parties finish their computation. The parties share the returns of the computation in this stage. The correctness of the sharing is guaranteed by verifiable secret sharing and homomorphic signature. The honest parties can reconstruct the outputs of the cheaters in the setting of an honest majority. We can't prevent the corrupted parties from learning the outputs and aborting the protocol for dishonest majority. Therefore, the sharing stage does not harm to the honest parties. Instead, we provide the honest parties with the identities of all cheaters in this case.","PeriodicalId":255083,"journal":{"name":"2023 7th International Conference on Cryptography, Security and Privacy (CSP)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128087859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Classification and Application of Long-duration Flows Based on Flow Behavior 基于流动特性的长时流分类及应用

2023 7th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2023-04-01 DOI: 10.1109/CSP58884.2023.00009

Zihao Chen, Wei Ding, Weijian Sun, Liang Xu

引用次数: 0

A Survey on Cross-Chain Data Transfer 跨链数据传输研究综述

2023 7th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2023-04-01 DOI: 10.1109/CSP58884.2023.00017

Wei Zheng, Ning Tian, Kejie Zhao, Hong Lei, Zhiwei Liu

引用次数: 0

A New Research on Verifiable and Searchable Encryption Scheme Based on Blockchain 一种基于区块链的可验证可搜索加密方案研究

2023 7th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2023-04-01 DOI: 10.1109/CSP58884.2023.00037

Zhong Kang, Maoning Wang

{"title":"A New Research on Verifiable and Searchable Encryption Scheme Based on Blockchain","authors":"Zhong Kang, Maoning Wang","doi":"10.1109/CSP58884.2023.00037","DOIUrl":"https://doi.org/10.1109/CSP58884.2023.00037","url":null,"abstract":"Cloud storage attracts more and more individuals and enterprises to outsource and store data on cloud servers due to its advantages of high efficiency, speed, low economic cost and on-demand access. Due to privacy requirements, data files need to be uploaded after being encrypted. Current searchable encryption technology enables retrieval of encrypted data, but lacks verification of searched results. In response to the above problem, this paper proposes a new searchable encryption scheme based on blockchain, which supports multi-keyword ranked search together with verification of searched results. Concretely, the scheme first encrypts the data and uploads it to the cloud server, then builds the index via blockchain. By calling the smart contracts to execute the search algorithm, the search result is returned to the user and the hash value is verified, which ensures the integrity and accuracy of the searched result. Secondly, by combining the vector space model and BM25 model to construct the index and query of encrypted data, the ranked search for multiple keywords is realized, in which the keyword balanced binary tree index is established to improve the retrieval efficiency. Experimental results show that the improved scheme has higher search accuracy while ensuring retrieval efficiency.","PeriodicalId":255083,"journal":{"name":"2023 7th International Conference on Cryptography, Security and Privacy (CSP)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131071902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Improved Key Mismatch Attack on Kyber 改进的Kyber密钥不匹配攻击

2023 7th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2023-04-01 DOI: 10.1109/CSP58884.2023.00030

Yaru Wang, Haodong Jiang, Zhi Ma

引用次数: 0

Generating t-Closed Partitions of Datasets with Multiple Sensitive Attributes 生成具有多个敏感属性的数据集的t-Closed分区

2023 7th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2023-04-01 DOI: 10.1109/CSP58884.2023.00024

Vikas Thammanna Gowda, R. Bagai

引用次数: 0

An Improved DEFAULT-like Cipher via Dynamic Secret S-Boxes Against Differential Fault Attack 一种改进的基于动态秘密s盒的类默认密码对抗差分故障攻击

2023 7th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2023-04-01 DOI: 10.1109/CSP58884.2023.00035

Linyang Yan, Huijiao Wang, Yongzhuang Wei

引用次数: 0