Conference
An AI-IoT hybrid algorithm for enhancing mentcare information system security.
| Τίτλος: | An AI-IoT hybrid algorithm for enhancing mentcare information system security. |
|---|---|
| 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] |
| Copyright of AIP Conference Proceedings is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: edb DbLabel: Complementary Index An: 183498960 RelevancyScore: 1009 AccessLevel: 6 PubType: Conference PubTypeId: conference PreciseRelevancyScore: 1008.54302978516 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: An AI-IoT hybrid algorithm for enhancing mentcare information system security. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Gaata%2C+Methaq+Talib%22">Gaata, Methaq Talib</searchLink><br /><searchLink fieldCode="AR" term="%22Mohialden%2C+Yasmin+Makki%22">Mohialden, Yasmin Makki</searchLink><br /><searchLink fieldCode="AR" term="%22Hussien%2C+Nadia+Mahmood%22">Hussien, Nadia Mahmood</searchLink> – Name: TitleSource Label: Source Group: Src Data: AIP Conference Proceedings; 2025, Vol. 3264 Issue 1, p1-11, 11p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Mental+health+services%22">Mental health services</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Distributed+computing%22">Distributed computing</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Security+systems%22">Security systems</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: 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] – Name: Abstract Label: Group: Ab Data: <i>Copyright of AIP Conference Proceedings is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edb&AN=183498960 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1063/5.0258428 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 1 Subjects: – SubjectFull: Mental health services Type: general – SubjectFull: Artificial intelligence Type: general – SubjectFull: Distributed computing Type: general – SubjectFull: Electronic data processing Type: general – SubjectFull: Security systems Type: general Titles: – TitleFull: An AI-IoT hybrid algorithm for enhancing mentcare information system security. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Gaata, Methaq Talib – PersonEntity: Name: NameFull: Mohialden, Yasmin Makki – PersonEntity: Name: NameFull: Hussien, Nadia Mahmood IsPartOfRelationships: – BibEntity: Dates: – D: 05 M: 03 Text: 2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 0094243X Numbering: – Type: volume Value: 3264 – Type: issue Value: 1 Titles: – TitleFull: AIP Conference Proceedings Type: main |
| ResultId | 1 |