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Devineni et al., 2023 - Google Patents

Machine learning-powered anomaly detection: Enhancing data security and integrity

Devineni et al., 2023

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Document ID
10505556353449501358
Author
Devineni S
Kathiriya S
Shende A
Publication year
Publication venue
Journal of Artificial Intelligence & Cloud Computing. SRC/JAICC-198. DOI: doi. org/10.47363/JAICC/2023 (2)

External Links

Snippet

Anomaly detection is crucial for the integrity and security of data across various industries. The advent and evolution of machine learning (ML) has significantly enhanced the capabilities of anomaly detection systems, offering more effective, precise, and flexible …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
    • G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
    • G06F21/6245—Protecting personal data, e.g. for financial or medical purposes
    • G06F21/6263—Protecting personal data, e.g. for financial or medical purposes during internet communication, e.g. revealing personal data from cookies
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run

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