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A Novel Eccentric Intrusion Detection Model Based on Recurrent Neural Networks with Leveraging LSTM

Computers, Materials & Continua 2024年第3期78卷 3089-3127页

作者： Navaneetha Krishnan Muthunambu Senthil Prabakaran balasubramanian prabhu kavin Kishore Senthil Siruvangur Kavitha Chinnadurai Jehad Ali Department of Computer Applications Karpagam College of EngineeringCoimbatore641032India Department of Computer Science and Engineering Karpagam College of EngineeringCoimbatore641032India Department of Data Science and Business Systems College of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathur603203India Department of Computer Science and Engineering Sathyabama Institute of Science and TechnologyJeppiaar NagarRajiv Gandhi SalaiChennai600119India Department of AI Convergence Network Ajou UniversitySuwon16499Korea

The extensive utilization of the Internet in everyday life can be attributed to the substantial accessibility of online services and the growing significance of the data transmitted via the ***,this development has expanded the potential targets that hackers might *** adequate safeguards,data transmitted on the internet is significantly more susceptible to unauthorized access,theft,or *** identification of unauthorised access attempts is a critical component of cybersecurity as it aids in the detection and prevention of malicious *** research paper introduces a novel intrusion detection framework that utilizes Recurrent Neural Networks(RNN)integrated with Long Short-Term Memory(LSTM)*** proposed model can identify various types of cyberattacks,including conventional and distinctive *** networks,a specific kind of feedforward neural networks,possess an intrinsic memory *** Neural Networks(RNNs)incorporating Long Short-Term Memory(LSTM)mechanisms have demonstrated greater capabilities in retaining and utilizing data dependencies over extended *** such as data types,training duration,accuracy,number of false positives,and number of false negatives are among the parameters employed to assess the effectiveness of these models in identifying both common and unusual *** are utilised in conjunction with LSTM to support human analysts in identifying possible intrusion events,hence enhancing their decision-making capabilities.A potential solution to address the limitations of Shallow learning is the introduction of the Eccentric Intrusion Detection *** model utilises Recurrent Neural Networks,specifically exploiting LSTM *** proposed model achieves detection accuracy(99.5%),generalisation(99%),and false-positive rate(0.72%),the parameters findings reveal that it is superior to state-of-the-art techniques.

关键词： Cybersecurity intrusion detection machine learning leveraging long short-term memory(LLSTM) CICIDS2019 dataset innovative cyberattacks

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Comparison of two incisions for open reduction and internal fixation of mandibular body fractures: A randomised controlled clinical trial evaluating the surgical outcome

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Chinese Journal of Traumatology 2019年第1期22卷 34-40页

作者： Sasikala balasubramanian Elavenil Panneerselvam Gayathri Gopi Komagan prabhu Nakkeeran Aditi Rajendra Sharma Krishnakumar Raja VB Department of Oral & Maxillofacial Surgery SRM Dental College & Hospital Ramapuram Campus Ramapuram Chennai 600089 India

Purpose: The purpose of the study is to compare the surgical access and post-operative outcome of two intra-oral incisions used for approaching a mandibular body fracture. Methods: This clinical trial involved 60 patients with mandibular body fractures who were randomly allocated to control and study groups. The fractures were approached using the routine vestibular incision in the control group and crevicular incision with vertical release in the study group. The effects of incision design on the post-surgical outcome variables like swelling, trismus, paresthesia, wound healing and gingival recession were statistically analysed with non-parametric tests by using SPSS 22.0 software. Comparison of continuous variables between the groups and time points was done using Mann Whitney test and Friedman test respectively. Chi-square test was used to compare proportions between groups. Dunn's test with Bonferroni correction was used for pair wise comparisons. Results: The study group demonstrated favourable surgical outcome in the immediate postoperative phase as compared to the control group. The difference in mouth opening, swelling and neurosensory impairment between the two groups was found to be statistically significant (p < 0.05). Conclusion: Crevicular incision was found to be an ideal alternative to vestibular incision in achieving surgical access and fixation of mandibular body fractures with reduction in postoperative patient discomfort and better surgical outcome.

关键词： Mandibular fractures Incision Nerve injury

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