Computational Intelligence最新文献_第4页

Continuous identity authentication protocol against quantum attacks in satellite integrated smart grid 针对卫星集成智能电网中量子攻击的连续身份验证协议

IF 2.8 4区计算机科学

Computational Intelligence Pub Date : 2024-06-17 DOI: 10.1111/coin.12647

Chao Huang, Min Yang, Bo Li, Lin Yu

{"title":"Continuous identity authentication protocol against quantum attacks in satellite integrated smart grid","authors":"Chao Huang, Min Yang, Bo Li, Lin Yu","doi":"10.1111/coin.12647","DOIUrl":"https://doi.org/10.1111/coin.12647","url":null,"abstract":"To address the issue of low efficiency caused by the repeated use of quantum attack resistant static identity authentication methods in a satellite integrated smart grid, this paper proposes a quantum attack resistant continuous identity authentication protocol. First, in the initial authentication stage, in order to reduce computational complexity, the key encryption mechanism in the CRYSTALS-Kyber algorithm was improved and combined with the NTRU message recovery digital signature scheme to construct a lattice based explicit AKE (Kyber NTRU. AKE), which achieved mutual authentication and negotiated shared tokens. Second, in the continuous authentication stage, incorporating quantum attack resistant tokens into the current algorithm to improve authentication efficiency. The formal analysis results indicate that compared to the weakly forward secure Kyber.AKE in the CRYSTALS-Kyber algorithm, Kyber-NTRU.AKE achieves complete forward secrecy, while the non-formal analysis results demonstrate the security of the continuous authentication phase. Through theoretical analysis and efficiency comparison with Cyber.AKE, the analysis shows that the Cyber-NTRU.AKE has higher computational and communication efficiency than Cyber.AKE.","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141424999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Retraction: Muthuramalingam Sivakumar, Perumal Renuka, Pandian Chitra, Sundararajan Karthikeyan. IoT incorporated deep learning model combined with SmartBin technology for real-time solid waste management. Comput Intell 38: 323–344, 2022 (10.1111/coin.12495) 撤回： Muthuramalingam Sivakumar, Perumal Renuka, Pandian Chitra, Sundararajan Karthikeyan. 物联网深度学习模型与智能垃圾桶技术相结合，用于实时固体废物管理。 Comput Intell 38: 323-344, 2022 (10.1111/coin.12495)

IF 2.8 4区计算机科学

Computational Intelligence Pub Date : 2024-06-17 DOI: 10.1111/coin.12669

引用次数: 0

MRD-GAN: Multi-representation discrimination GAN for enhancing the diversity of the generated data MRD-GAN：用于提高生成数据多样性的多表征判别 GAN

IF 2.8 4区计算机科学

Computational Intelligence Pub Date : 2024-06-17 DOI: 10.1111/coin.12685

Mohammed Megahed, Ammar Mohammed

{"title":"MRD-GAN: Multi-representation discrimination GAN for enhancing the diversity of the generated data","authors":"Mohammed Megahed, Ammar Mohammed","doi":"10.1111/coin.12685","DOIUrl":"https://doi.org/10.1111/coin.12685","url":null,"abstract":"The generative adversarial network (GAN) is a highly effective member of the generative models category and is extensively employed for generating realistic samples across various domains. The fundamental concept behind GAN involves two networks, a generator and a discriminator, competing against each other. During the training process, generator and discriminator networks encounter several issues that can potentially affect the quality and diversity of the generated samples. One such critical issue is mode collapse, where the generator fails to create varied samples. To tackle this issue, this article introduces a GAN approach called the multi-representation discrimination GAN (MRD-GAN). In this approach, the discriminator supports concurrent network discrimination flows to manage different representations of the data through various transformation functions, such as dimension rescaling, brightness adjustment, and gamma correction applied to the input data of the discriminator. We use a fusion function to aggregate the output of all flows and return a consolidated loss value to update the generator's weights. Hence, the discriminator conveys diverse feedback to the generator. The proposed approach has been evaluated on four distinct benchmarks, namely CelebA, Cifar-10, Fashion-Mnist, and Mnist. The experimental results demonstrate that the proposed approach surpasses the existing state-of-the-art GAN models in terms of FID metric that measures the diversity of the generated samples. Significantly, the proposed approach demonstrates remarkable FID scores of 14.02, 30.19, 9.42, and 3.14 on the CelebA, Cifar-10, Fashion-Mnist, and Mnist datasets, respectively.","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141425025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust colored point cloud alignment based on L*a*b* guided and Cauchy kernel 基于 L*a*b* 导向和 Cauchy 核的鲁棒彩色点云配准

IF 2.8 4区计算机科学

Computational Intelligence Pub Date : 2024-06-17 DOI: 10.1111/coin.12657

Teng Wan, Shaoyi Du, Qiang Zhang, Ying Qi, Chunyao Huang, Wei Zeng

{"title":"Robust colored point cloud alignment based on L*a*b* guided and Cauchy kernel","authors":"Teng Wan, Shaoyi Du, Qiang Zhang, Ying Qi, Chunyao Huang, Wei Zeng","doi":"10.1111/coin.12657","DOIUrl":"https://doi.org/10.1111/coin.12657","url":null,"abstract":"Precision agriculture benefits from point set registration, which can monitor plant health and growth in real time, promote the precise application of fertilizers and pesticides, and provide technical support for achieving sustainable development of agriculture. In this work, we propose a robust point set registration method for precision agriculture based on L*a*b* color guidance, bidirectional search and Cauchy distribution. First, the L*a*b* color guidance is applied to establish accurate correspondences between agricultural RGB-D data. Second, the bidirectional nearest neighbor search strategy between point sets improves the reliability of establishing correspondences and broadens the convergence domain of the algorithm. Third, Cauchy distribution is utilized as an energy function for noise suppression, which further improves the robustness of the algorithm in dealing with complex vegetation scenes. Finally, results of ablation and simulation experiments indicate that the proposed registration algorithm can achieve more accurate and robust alignment results than other classic and state-of-the-art point cloud registration algorithms to achieve monitoring and comparison of plant growth.","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141424981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Retraction: Neeraj Kumar, Upendra Kumar. Artificial intelligence for classification and regression tree based feature selection method for network intrusion detection system in various telecommunication technologies. Comput Intell 40: e12500, 2024 (10.1111/coin.12500) 撤回： Neeraj Kumar, Upendra Kumar. 基于人工智能的分类和回归树特征选择方法，用于各种电信技术中的网络入侵检测系统。 Comput Intell 40: e12500, 2024 (10.1111/coin.12500)

IF 2.8 4区计算机科学

Computational Intelligence Pub Date : 2024-06-12 DOI: 10.1111/coin.12672

引用次数: 0

Retraction: Gerard Deepak, Arumugam Santhanavijayan. QGMS: A query growth model for personalization and diversification of semantic search based on differential ontology semantics using artificial intelligence. Comput Intell 40: e12514, 2024 (10.1111/coin.12514) 撤回：杰拉德-迪帕克、阿鲁穆加姆-桑塔纳维贾扬。 QGMS：基于人工智能差异本体语义的个性化和多样化语义搜索查询增长模型。 Comput Intell 40: e12514, 2024 (10.1111/coin.12514)

IF 2.8 4区计算机科学

Computational Intelligence Pub Date : 2024-06-12 DOI: 10.1111/coin.12679

引用次数: 0

Retraction: S. P. Santhoshkumar, H. Lilly Beaulah, Abdulrahman Saad Alqahtani, P. Parthasarathy, Azath Mubarakali. A remote diagnosis of Parkinson's ailment using artificial intelligence based BPNN framework and cloud based storage architecture for securing data in cloud environment for the application of telecommunication technologies. Comput Intell 40: e12508, 2024 (10.1111/coin.12508) 撤回： S. P. Santhoshkumar, H. Lilly Beaulah, Abdulrahman Saad Alqahtani, P. Parthasarathy, Azath Mubarakali. 使用基于人工智能的 BPNN 框架和基于云的存储架构对帕金森病进行远程诊断，以确保云环境中电信技术应用的数据安全。 Comput Intell 40: e12508, 2024 (10.1111/coin.12508)

IF 2.8 4区计算机科学

Computational Intelligence Pub Date : 2024-06-12 DOI: 10.1111/coin.12674

引用次数: 0

Retraction: Chinnathangam Karthikraja, Jayaprakasam Senthilkumar, Rajadurai Hariharan, Gandhi Usha Devi, Yuvaraj Suresh, Vijayakumar Mohanraj. An empirical intrusion detection system based on XGBoost and bidirectional long-short term model for 5G and other telecommunication technologies. Comput Intell 38: 1216–1231, 2022 (10.1111/coin.12497) 撤回： Chinnathangam Karthikraja, Jayaprakasam Senthilkumar, Rajadurai Hariharan, Gandhi Usha Devi, Yuvaraj Suresh, Vijayakumar Mohanraj. 基于 XGBoost 和双向长短期模型的经验入侵检测系统，适用于 5G 和其他电信技术。 Comput Intell 38: 1216-1231, 2022 (10.1111/coin.12497)

IF 2.8 4区计算机科学

Computational Intelligence Pub Date : 2024-06-12 DOI: 10.1111/coin.12671

{"title":"Retraction: Chinnathangam Karthikraja, Jayaprakasam Senthilkumar, Rajadurai Hariharan, Gandhi Usha Devi, Yuvaraj Suresh, Vijayakumar Mohanraj. An empirical intrusion detection system based on XGBoost and bidirectional long-short term model for 5G and other telecommunication technologies. Comput Intell 38: 1216–1231, 2022 (10.1111/coin.12497)","authors":"","doi":"10.1111/coin.12671","DOIUrl":"https://doi.org/10.1111/coin.12671","url":null,"abstract":"The above article, published online on 23 January 2022 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor-in-Chief, Diana Inkpen, and Wiley Periodicals LLC. The article was published as part of a guest-edited special issue. Following publication, it came to our attention that two of those named as Guest Editors of this issue were being impersonated and/or misrepresented by a fraudulent entity. An investigation by the publisher found that all of the articles, including this one, experienced compromised editorial handling and peer review which was not in line with the journal's ethical standards. Therefore, a decision has been made to retract this article. We did not find any evidence of misconduct by the authors. The authors have been informed of the decision to retract but do not agree with this decision.","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/coin.12671","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141315318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Retraction: Om Kumar, C.U, Ponsy, R. K. Sathia Bhama. Efficient ensemble to combat flash attacks. Comput Intell 40: e12488, 2024 (10.1111/coin.12488) 撤回： Om Kumar, C.U, Ponsy, R. K. Sathia Bhama. 高效合集对抗闪存攻击。 Comput Intell 40: e12488, 2024 (10.1111/coin.12488)

IF 2.8 4区计算机科学

Computational Intelligence Pub Date : 2024-06-12 DOI: 10.1111/coin.12676

引用次数: 0

Retraction: Vijaya Rangan Vivekanandhan, Subramaniam Sakthivel, Muthaiyan Manikandan. Adaptive neuro fuzzy inference system to enhance the classification performance in smart irrigation system. Comput Intell 38: 308–322, 2022 (10.1111/coin.12492) 撤回： Vijaya Rangan Vivekanandhan, Subramaniam Sakthivel, Muthaiyan Manikandan. 提高智能灌溉系统分类性能的自适应神经模糊推理系统。 Comput Intell 38: 308-322, 2022 (10.1111/coin.12492)

IF 2.8 4区计算机科学

Computational Intelligence Pub Date : 2024-06-12 DOI: 10.1111/coin.12681

引用次数: 0