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http://localhost:8080/xmlui/handle/123456789/3802| Title: | EMERGING AI-ENABLED SECURITY FOR INDUSTRY 4.0 |
| Authors: | Dabbe, Chetan Rakibe, Priya Agarwal, Nimish Barhate, Bhavesh Choudhari, Rucha Pawar, Sakshi |
| Keywords: | Industry 4.0 Artificial Intelligence Cybersecurity Machine Learning |
| Issue Date: | 5-Dec-2023 |
| Abstract: | In the world of industry, where everything is going to be connected and automated. The expanding network of interconnected devices and systems heightens their exposure to cyber-attacks and security breaches. For solving such problems or to overcome such problems, combining AI with cybersecurity is essential, because AI is mostly used for analyzing the huge amount of data from sensors and devices to detect and prevent cyber threats. The use of Machine Learning algorithms is crucial for recognizing regular behavioral patterns and detecting any deviations that may indicate potential security threats. Anomaly detection, predictive analysis and Intrusion detection are the various techniques that are used in combination with cybersecurity measures i.e. intrusion detection system and firewalls for providing the best approach to cybersecurity for Industry applications. Additionally, the ideal AI-driven cybersecurity solution integrates advanced technologies for real-time anomaly detection and comprehensive security response, ensuring proactive protection against evolving cyber threats. Moreover, it seamlessly integrates with existing security infrastructure, enhancing overall security posture and facilitating a unified approach to threat detection and response. The main aim to use AI with cybersecurity for industry application is to reduce the increasing cyber-attacks. |
| URI: | http://localhost:8080/xmlui/handle/123456789/3802 |
| Appears in Collections: | EMERGING AI-ENABLED SECURITY FOR INDUSTRY 4.0 |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| ijaet20v5-4-2023-276 (1).pdf | 562.67 kB | Unknown | View/Open |
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