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您的检索式：作者名="K.Pradeep Mohan Kumar"
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| 1 | Feature Selection with Deep Reinforcement Learning for Intrusion Detection System显示文摘An intrusion detection system(IDS)becomes an important tool for ensuring security in the network.In recent times,machine learning(ML)and deep learning(DL)models can be applied for the identification of intrusions over the network effectively.To resolve the security issues,this paper presents a new Binary Butterfly Optimization algorithm based on Feature Selection with DRL technique,called BBOFS-DRL for intrusion detection.The proposed BBOFSDRL model mainly accomplishes the recognition of intrusions in the network.To attain this,the BBOFS-DRL model initially designs the BBOFS algorithm based on the traditional butterfly optimization algorithm(BOA)to elect feature subsets.Besides,DRL model is employed for the proper identification and classification of intrusions that exist in the network.Furthermore,beetle antenna search(BAS)technique is applied to tune the DRL parameters for enhanced intrusion detection efficiency.For ensuring the superior intrusion detection outcomes of the BBOFS-DRL model,a wide-ranging experimental analysis is performed against benchmark dataset.The simulation results reported the supremacy of the BBOFS-DRL model over its recent state of art approaches. | S.Priya K.Pradeep Mohan Kumar | 2023 | Computer Systems Science & Engineering2023，46，9： | 1 |
| 2 | Bird Swarm Algorithm with Fuzzy Min-Max Neural Network for Financial Crisis Prediction显示文摘Financial crisis prediction(FCP)models are used for predicting or forecasting the financial status of a company or financial firm.It is considered a challenging issue in the financial sector.Statistical and machine learning(ML)models can be employed for the design of accurate FCP models.Though numerous works have existed in the literature,it is needed to design effective FCP models adaptable to different datasets.This study designs a new bird swarm algorithm(BSA)with fuzzy min-max neural network(FMM-NN)model,named BSA-FMMNN for FCP.The major intention of the BSA-FMMNN model is to determine the financial status of a firm or company.The presented BSA-FMMNN model primarily undergoes minmax normalization to transform the data into uniformity range.Besides,k-medoid clustering approach is employed for the outlier removal process.Finally,the classification process is carried out using the FMMNN model,and the parameters involved in it are tuned by the use of BSA.The utilization of proficient parameter selection process using BSA demonstrate the novelty of the study.The experimental result analysis of the BSA-FMMNN model is validated using benchmark dataset and the comparative outcomes highlighted the supremacy of the BSA-FMMNN model over the recent approaches. | K.Pradeep Mohan Kumar S.Dhanasekaran I.S.Hephzi Punithavathi P.Duraipandy Ashit Kumar Dutta Irina V.Pustokhina Denis A.Pustokhin | 2022 | Computers, Materials & Continua2022，，10： | 0 |
| 3 | Privacy Preserving Blockchain with Optimal Deep Learning Model for Smart Cities显示文摘Recently,smart cities have emerged as an effective approach to deliver high-quality services to the people through adaptive optimization of the available resources.Despite the advantages of smart cities,security remains a huge challenge to be overcome.Simultaneously,Intrusion Detection System(IDS)is the most proficient tool to accomplish security in this scenario.Besides,blockchain exhibits significance in promoting smart city designing,due to its effective characteristics like immutability,transparency,and decentralization.In order to address the security problems in smart cities,the current study designs a Privacy Preserving Secure Framework using Blockchain with Optimal Deep Learning(PPSF-BODL)model.The proposed PPSFBODL model includes the collection of primary data using sensing tools.Besides,z-score normalization is also utilized to transform the actual data into useful format.Besides,Chameleon Swarm Optimization(CSO)with Attention Based Bidirectional Long Short TermMemory(ABiLSTM)model is employed for detection and classification of intrusions.CSO is employed for optimal hyperparameter tuning of ABiLSTM model.At the same time,Blockchain(BC)is utilized for secure transmission of the data to cloud server.This cloud server is a decentralized,distributed,and open digital ledger that is employed to store the transactions in different methods.A detailed experimentation of the proposed PPSF-BODL model was conducted on benchmark dataset and the outcomes established the supremacy of the proposed PPSFBODL model over recent approaches with a maximum accuracy of 97.46%. | K.Pradeep Mohan Kumar Jenifer Mahilraj D.Swathi R.Rajavarman Subhi R.M.Zeebaree Rizgar RZebari Zryan Najat Rashid Ahmed Alkhayyat | 2022 | Computers, Materials & Continua2022，，12： | 0 |
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