Labelled Vulnerability Dataset on Android Source Code (LVDAndro) to Develop AI-Based Code Vulnerability Detection Models

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

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

    3 Citations (SciVal)
    Original languageEnglish
    Title of host publicationSECRYPT 2023 - Proceedings of the 20th International Conference on Security and Cryptography
    EditorsSabrina De Capitani di Vimercati, Pierangela Samarati
    PublisherScience and Technology Publications, Lda
    Pages659-666
    Number of pages8
    ISBN (Print)9789897586668
    DOIs
    Publication statusPublished (VoR) - 2023
    Event20th International Conference on Security and Cryptography, SECRYPT 2023 - Rome, Italy
    Duration: 10 Jul 202312 Jul 2023

    Publication series

    NameProceedings of the International Conference on Security and Cryptography
    Volume1
    ISSN (Print)2184-7711

    Conference

    Conference20th International Conference on Security and Cryptography, SECRYPT 2023
    Country/TerritoryItaly
    CityRome
    Period10/07/2312/07/23

    Keywords

    • Android Application Security
    • Artificial Intelligence
    • Auto Machine Learning
    • Code Vulnerability
    • Labelled Dataset

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