High-Confidence Computing最新文献_第10页

Reaching consensus for membership dynamic in secret sharing and its application to cross-chain 秘密共享中成员动态达成共识及其在跨链中的应用

High-Confidence Computing Pub Date : 2023-09-01 DOI: 10.1016/j.hcc.2023.100131

Yan Zhu , Bingyu Li , Zhenyang Ding , Yang Yang , Qianhong Wu , Haibin Zheng

{"title":"Reaching consensus for membership dynamic in secret sharing and its application to cross-chain","authors":"Yan Zhu , Bingyu Li , Zhenyang Ding , Yang Yang , Qianhong Wu , Haibin Zheng","doi":"10.1016/j.hcc.2023.100131","DOIUrl":"https://doi.org/10.1016/j.hcc.2023.100131","url":null,"abstract":"<div><p>The communication efficiency optimization, censorship resilience, and generation of shared randomness are inseparable from the threshold cryptography in the existing Byzantine Fault Tolerant (BFT) consensus. The membership in consensus in a blockchain scenario supports dynamic changes, which effectively prevents the corruption of consensus participants. Especially in cross-chain protocols, the dynamic access to different blockchains will inevitably bring about the demand for member dynamic. Most existing threshold cryptography schemes rely on redefined key shares, leading to a static set of secret sharing participants. In this paper, we propose a general approach to coupling blockchain consensus and dynamic secret sharing. The committee performs consensus confirmation of both dynamic secret sharing and transaction proposals. Our scheme facilitates threshold cryptography membership dynamic, thus underlying support for membership dynamic of threshold cryptography-based BFT consensus schemes. We instantiate a dynamic HotStuff consensus to demonstrate the effectiveness of the scheme. After the correctness and security proof, our scheme achieves the secrecy and integrity of the threshold key shares while ensuring consensus liveness and safety. Experimental results prove that our scheme obtains dynamic membership with negligible overhead.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"3 3","pages":"Article 100131"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50191219","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

UltraJam: Ultrasonic adaptive jammer based on nonlinearity effect of microphone circuits UltraJam：基于麦克风电路非线性效应的超声自适应干扰器

High-Confidence Computing Pub Date : 2023-09-01 DOI: 10.1016/j.hcc.2023.100129

Zhicheng Han , Jun Ma , Chao Xu , Guoming Zhang

{"title":"UltraJam: Ultrasonic adaptive jammer based on nonlinearity effect of microphone circuits","authors":"Zhicheng Han , Jun Ma , Chao Xu , Guoming Zhang","doi":"10.1016/j.hcc.2023.100129","DOIUrl":"https://doi.org/10.1016/j.hcc.2023.100129","url":null,"abstract":"<div><p>The widely used devices (e.g. smartphones, recorders) equipped with microphones have posed a severe threat to confidential conversations. In this paper, we design an inaudible anti-eavesdropping method: UltraJam, to reduce the risk of unwanted and secret recordings. UltraJam uses the ultrasonic signal to mask conversation. By leveraging the nonlinear effect of microphone circuits, the adaptive ultrasonic signal can be recorded and demodulated into low-frequency which can effectively squash the sound. Based on the characteristics of the attenuation coefficient and frequency response, we construct a number of jamming signals with different bandwidths and designed a wideband signal injection array, meanwhile adaptively adjust the power at each bandwidth signal to cover more frequency bands and increase usage scenarios. To verify the security of the microphone jamming system, we also utilize several audio recovery methods to recover the raw signal from jamming noise. The experimental results show that less than 1% of the words are recognized in the jamming recording, and even with the audio recovery method, 99% of the words still cannot be recognized in the recovered jamming recording.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"3 3","pages":"Article 100129"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50191220","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

BC driven IoT-based food quality traceability system for dairy product using deep learning model 基于深度学习模型的BC驱动的基于物联网的乳制品食品质量追溯系统

High-Confidence Computing Pub Date : 2023-09-01 DOI: 10.1016/j.hcc.2023.100121

Noothi Manisha, Madiraju Jagadeeshwar

引用次数: 0

DEFEAT: A decentralized federated learning against gradient attacks DEFEAT：一种针对梯度攻击的去中心化联合学习

High-Confidence Computing Pub Date : 2023-09-01 DOI: 10.1016/j.hcc.2023.100128

Guangxi Lu , Zuobin Xiong , Ruinian Li , Nael Mohammad , Yingshu Li , Wei Li

{"title":"DEFEAT: A decentralized federated learning against gradient attacks","authors":"Guangxi Lu , Zuobin Xiong , Ruinian Li , Nael Mohammad , Yingshu Li , Wei Li","doi":"10.1016/j.hcc.2023.100128","DOIUrl":"https://doi.org/10.1016/j.hcc.2023.100128","url":null,"abstract":"<div><p>As one of the most promising machine learning frameworks emerging in recent years, Federated learning (FL) has received lots of attention. The main idea of centralized FL is to train a global model by aggregating local model parameters and maintain the private data of users locally. However, recent studies have shown that traditional centralized federated learning is vulnerable to various attacks, such as gradient attacks, where a malicious server collects local model gradients and uses them to recover the private data stored on the client. In this paper, we propose a decentralized federated learning against aTtacks (DEFEAT) framework and use it to defend the gradient attack. The decentralized structure adopted by this paper uses a peer-to-peer network to transmit, aggregate, and update local models. In DEFEAT, the participating clients only need to communicate with their single-hop neighbors to learn the global model, in which the model accuracy and communication cost during the training process of DEFEAT are well balanced. Through a series of experiments and detailed case studies on real datasets, we evaluate the excellent model performance of DEFEAT and the privacy preservation capability against gradient attacks.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"3 3","pages":"Article 100128"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50191222","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: 3

An efficient identity-based signature protocol over lattices for the smart grid 智能电网中一种有效的基于身份的格签名协议

High-Confidence Computing Pub Date : 2023-08-19 DOI: 10.1016/j.hcc.2023.100147

Longzhu Zhu , Fan Jiang , Min Luo , Quanrun Li

引用次数: 0

Research on active defense decision-making method for cloud boundary networks based on reinforcement learning of intelligent agent 基于智能代理强化学习的云边界网络主动防御决策方法研究

High-Confidence Computing Pub Date : 2023-08-11 DOI: 10.1016/j.hcc.2023.100145

Huan Wang , Yunlong Tang , Yan Wang , Ning Wei , Junyi Deng , Zhiyan Bin , Weilong Li

{"title":"Research on active defense decision-making method for cloud boundary networks based on reinforcement learning of intelligent agent","authors":"Huan Wang , Yunlong Tang , Yan Wang , Ning Wei , Junyi Deng , Zhiyan Bin , Weilong Li","doi":"10.1016/j.hcc.2023.100145","DOIUrl":"10.1016/j.hcc.2023.100145","url":null,"abstract":"<div><p>The cloud boundary network environment is characterized by a passive defense strategy, discrete defense actions, and delayed defense feedback in the face of network attacks, ignoring the influence of the external environment on defense decisions, thus resulting in poor defense effectiveness. Therefore, this paper proposes a cloud boundary network active defense model and decision method based on the reinforcement learning of intelligent agent, designs the network structure of the intelligent agent attack and defense game, and depicts the attack and defense game process of cloud boundary network; constructs the observation space and action space of reinforcement learning of intelligent agent in the non-complete information environment, and portrays the interaction process between intelligent agent and environment; establishes the reward mechanism based on the attack and defense gain, and encourage intelligent agents to learn more effective defense strategies. the designed active defense decision intelligent agent based on deep reinforcement learning can solve the problems of border dynamics, interaction lag, and control dispersion in the defense decision process of cloud boundary networks, and improve the autonomy and continuity of defense decisions.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 2","pages":"Article 100145"},"PeriodicalIF":0.0,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000430/pdfft?md5=3999db4a0c52cf4973ef09d3cfb36ff6&pid=1-s2.0-S2667295223000430-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75345400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

JFinder: A novel architecture for java vulnerability identification based quad self-attention and pre-training mechanism JFinder:一种基于quad自注意和预训练机制的java漏洞识别新架构

High-Confidence Computing Pub Date : 2023-08-09 DOI: 10.1016/j.hcc.2023.100148

Jin Wang , Zishan Huang , Hui Xiao, Yinhao Xiao

引用次数: 0

Lightweight key distribution for secured and energy efficient communication in wireless sensor network: An optimization assisted model 无线传感器网络中用于安全和节能通信的轻量级密钥分配：一个优化辅助模型

High-Confidence Computing Pub Date : 2023-06-01 DOI: 10.1016/j.hcc.2023.100126

Ezhil Roja P. , Misbha D.S.

{"title":"Lightweight key distribution for secured and energy efficient communication in wireless sensor network: An optimization assisted model","authors":"Ezhil Roja P. , Misbha D.S.","doi":"10.1016/j.hcc.2023.100126","DOIUrl":"https://doi.org/10.1016/j.hcc.2023.100126","url":null,"abstract":"<div><p>Due to their open, expansive, and resource-constrained character, Wireless Sensor Networks (WSNs) face significant energy, efficiency, and security issues. With a fair level of energy and resource consumption, several lightweight cryptographic techniques are introduced to increase the security as well as effectiveness of WSNs. Still, they have problems with scalability, key distribution, security, and power management. This work proposes a novel light weighted key distribution mechanism for safe and energy efficient communication in WSN. The proposed model includes stages like optimal Cluster Head Selection (CHS), improved Elliptic Curve Cryptography (ECC)-based encryption, and lightweight key management, respectively. In the first phase, a hybrid optimization strategy is proposed, termed as Coot updated Butterfly algorithm with Logistic Solution Space algorithm (CUBA-LSS) for optimal clustering via selecting the optimal CH. This selection process relies on the consideration of the Received Signal Strength Indicator (RSSI), energy, delay, and distance. Data transmission is the subsequent process, where the proposed algorithm ensures secured transmission through Improved ECC. At last, a lightweight key management system is determined via session key generation to protect the encryption key.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"3 2","pages":"Article 100126"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50200505","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: 1

Erratum regarding missing statements in previously published articles 关于先前发表文章中遗漏陈述的勘误表

High-Confidence Computing Pub Date : 2023-06-01 DOI: 10.1016/j.hcc.2023.100105

引用次数: 0

Attribute-based keyword search encryption for power data protection 基于属性的关键字搜索加密用于电力数据保护

High-Confidence Computing Pub Date : 2023-06-01 DOI: 10.1016/j.hcc.2023.100115

Xun Zhang , Dejun Mu , Jinxiong Zhao

{"title":"Attribute-based keyword search encryption for power data protection","authors":"Xun Zhang , Dejun Mu , Jinxiong Zhao","doi":"10.1016/j.hcc.2023.100115","DOIUrl":"https://doi.org/10.1016/j.hcc.2023.100115","url":null,"abstract":"<div><p>To protect the privacy of power data, we usually encrypt data before outsourcing it to the cloud servers. However, it is challenging to search over the encrypted data. In addition, we need to ensure that only authorized users can retrieve the power data. The attribute-based searchable encryption is an advanced technology to solve these problems. However, many existing schemes do not support large universe, expressive access policies, and hidden access policies. In this paper, we propose an attribute-based keyword search encryption scheme for power data protection. Firstly, our proposed scheme can support encrypted data retrieval and achieve fine-grained access control. Only authorized users whose attributes satisfy the access policies can search and decrypt the encrypted data. Secondly, to satisfy the requirement in the power grid environment, the proposed scheme can support large attribute universe and hidden access policies. The access policy in this scheme does not leak private information about users. Thirdly, the security analysis and performance analysis indicate that our scheme is efficient and practical. Furthermore, the comparisons with other schemes demonstrate the advantages of our proposed scheme.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"3 2","pages":"Article 100115"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50200502","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: 1