DL Model for Security Detection in Stack Overflow to Predict Performance and Maintenance Needs of IOT Environment
Authors:
Patnam Koteshwara Vara Prasad, Bhushan, Gone Venkat, Mr. Naveen Chakravarthi
Page No: 1103-1110
Abstract:
The increasing proliferation of the Internet of Things (IoT) has revolutionized various industries by enabling real-time data exchange and automated processes. However, with this rapid growth comes the challenge of ensuring robust security and efficient performance management across IoT systems. As per recent statistics, the number of IoT devices is expected to exceed 75 billion by 2025, creating a vast network that is susceptible to security breaches and maintenance issues.
Description:
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Volume & Issue
Volume-14,Issue-4
Keywords
IoT Security Detection, Deep Learning, Predictive Maintenance, Natural Language Processing (NLP), Security Threat Detection, Anomaly Detection in IoT, Neural Networks for IoT Security, Text Classification for Cybersecurity, Machine Learning for IoT Security, Cyber Threat Intelligence, Predicting IoT Failures, Automated Security Analysis