Android Code Vulnerabilities Early Detection Using AI-Powered ACVED Plugin

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

    3 Citations (SciVal)
    Original languageEnglish
    Title of host publicationData and Applications Security and Privacy XXXVII - 37th Annual IFIP WG 11.3 Conference, DBSec 2023, Proceedings
    EditorsVijayalakshmi Atluri, Anna Lisa Ferrara
    PublisherSpringer Science and Business Media Deutschland GmbH
    Pages339-357
    Number of pages19
    ISBN (Print)9783031375859
    DOIs
    Publication statusPublished (VoR) - 2023
    Event37th Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy, DBSec 2023 - Sophia Antipolis, France
    Duration: 19 Jul 202321 Jul 2023

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume13942 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference37th Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy, DBSec 2023
    Country/TerritoryFrance
    CitySophia Antipolis
    Period19/07/2321/07/23

    Keywords

    • Android application security
    • artificial intelligence
    • code vulnerability
    • labelled dataset
    • plugin

    Fingerprint

    Dive into the research topics of 'Android Code Vulnerabilities Early Detection Using AI-Powered ACVED Plugin'. Together they form a unique fingerprint.

    Cite this