Conference
An AI-IoT hybrid algorithm for enhancing mentcare information system security.
| Τίτλος: | An AI-IoT hybrid algorithm for enhancing mentcare information system security. |
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| Συγγραφείς: | Gaata, Methaq Talib, Mohialden, Yasmin Makki, Hussien, Nadia Mahmood |
| Πηγή: | AIP Conference Proceedings; 2025, Vol. 3264 Issue 1, p1-11, 11p |
| Θεματικοί όροι: | Mental health services, Artificial intelligence, Distributed computing, Electronic data processing, Security systems |
| Περίληψη: | Take care of critical health information is important to medical privacy and confidentiality. This paper employs the Internet of Things (IoT) and artificial intelligence techniques to safeguard mental health care information systems. The system uses symmetric key encryption to secure private data during data processing. We develop various password strengths to enhance system security and entry control. To improve patient safety and trust, this system aims to create mental health care information tools that are safe and work well. The proposed system has three types of passwords: those that are easy to remember but offer strong security. Middle passwords are a good mix of security and ease of use. Strong passwords offer the highest level of security since they are longer and use a mix of letters, numbers, and symbols. The paper recommends using these passwords to access highly secure systems or accounts that contain crucial data when additional security is required. There is a list of methods for finding anomalies and explanations of fog computing-based distributed processing and symmetric key cryptography techniques. The paper presented the effects of finding anomalies in a 100x1 grid that had 10 anomalies in it. The paper provides the fog computing efficiency matrix technique for each numerical value. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: | Complementary Index |
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