首页|Investigators at Department of Computer Sciences and Engineering Detail Findings in Artificial Intelligence (An Efficient Cyber Threat Prediction Using a Novel Artificial Intelligence Technique)
Investigators at Department of Computer Sciences and Engineering Detail Findings in Artificial Intelligence (An Efficient Cyber Threat Prediction Using a Novel Artificial Intelligence Technique)
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Springer Nature
Current study results on Artificial Intelligence have been published. According to news originating from Uttar Pradesh, India, by NewsRx correspondents, research stated, “Digital applications are ruling today’s world with their advancement. However, offering security for that digital application is an important and complex task.” Our news journalists obtained a quote from the research from the Department of Computer Sciences and Engineering, “Several detection-based security models have existed in the Artificial Intelligence (AI) vision. Still, the problem in threat detection has not ended because of the unique behavior of the different attacks. So, the present research has introduced a novel Cuttlefish-based Peephole Long Short Term Memory (CbPLSTM) model proposed for predicting the cyber threat from the data defends against attacks. Initially, data were preprocessed by removing noise from the data using the noise filtering function. Then, the refined data is imported to the classification layer of the CbP-LSTM for performing the feature extraction and attack prediction tasks. Moreover, the proposed CbP-LSTM model was implemented in the Python tool with several performance metrics, whereas the parameters were calculated, such as accuracy, precision, Recall, and F-score.”
Uttar PradeshIndiaAsiaArtificial IntelligenceCybersecurityEmerging TechnologiesMachine LearningDepartment of Computer Sciences and Engineering
NETL
NSTL
Springer Nature
