Developing Secured Android Applications by Mitigating Code Vulnerabilities with Machine Learning

Janaka Senanayake*, Harsha Kalutarage, Mhd Omar Al-Kadri, Andrei Petrovski, Luca Piras

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    6 Citations (SciVal)
    Original languageEnglish
    Title of host publicationASIA CCS 2022 - Proceedings of the 2022 ACM Asia Conference on Computer and Communications Security
    PublisherAssociation for Computing Machinery
    Pages1255-1257
    Number of pages3
    ISBN (Electronic)9781450391405
    DOIs
    Publication statusPublished (VoR) - 30 May 2022
    Event17th ACM ASIA Conference on Computer and Communications Security 2022, ASIA CCS 2022 - Virtual, Online, Japan
    Duration: 30 May 20223 Jun 2022

    Publication series

    NameASIA CCS 2022 - Proceedings of the 2022 ACM Asia Conference on Computer and Communications Security

    Conference

    Conference17th ACM ASIA Conference on Computer and Communications Security 2022, ASIA CCS 2022
    Country/TerritoryJapan
    CityVirtual, Online
    Period30/05/223/06/22

    Keywords

    • android
    • code vulnerability detection
    • machine learning
    • secure mobile apps
    • static analysis
    • vulnerability dataset

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