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

doi:10.5220/0012060400003555

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 proceeding › Conference contribution › peer-review

5 Citations (SciVal)

Original language	English
Title of host publication	SECRYPT 2023 - Proceedings of the 20th International Conference on Security and Cryptography
Editors	Sabrina De Capitani di Vimercati, Pierangela Samarati
Publisher	Science and Technology Publications, Lda
Pages	659-666
Number of pages	8
ISBN (Print)	9789897586668
DOIs	https://doi.org/10.5220/0012060400003555
Publication status	Published (VoR) - 2023
Event	20th International Conference on Security and Cryptography, SECRYPT 2023 - Rome, Italy Duration: 10 Jul 2023 → 12 Jul 2023

Publication series

Name	Proceedings of the International Conference on Security and Cryptography
Volume	1
ISSN (Print)	2184-7711

Conference

Conference	20th International Conference on Security and Cryptography, SECRYPT 2023
Country/Territory	Italy
City	Rome
Period	10/07/23 → 12/07/23

Keywords

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

Access to Document

10.5220/0012060400003555

Cite this

Senanayake, J., Kalutarage, H., Al-Kadri, M. O., Piras, L., & Petrovski, A. (2023). Labelled Vulnerability Dataset on Android Source Code (LVDAndro) to Develop AI-Based Code Vulnerability Detection Models. In S. De Capitani di Vimercati, & P. Samarati (Eds.), SECRYPT 2023 - Proceedings of the 20th International Conference on Security and Cryptography (pp. 659-666). (Proceedings of the International Conference on Security and Cryptography; Vol. 1). Science and Technology Publications, Lda. https://doi.org/10.5220/0012060400003555

Senanayake, Janaka ; Kalutarage, Harsha ; Al-Kadri, Mhd Omar et al. / Labelled Vulnerability Dataset on Android Source Code (LVDAndro) to Develop AI-Based Code Vulnerability Detection Models. SECRYPT 2023 - Proceedings of the 20th International Conference on Security and Cryptography. editor / Sabrina De Capitani di Vimercati ; Pierangela Samarati. Science and Technology Publications, Lda, 2023. pp. 659-666 (Proceedings of the International Conference on Security and Cryptography).

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

keywords = "Android Application Security, Artificial Intelligence, Auto Machine Learning, Code Vulnerability, Labelled Dataset",

author = "Janaka Senanayake and Harsha Kalutarage and Al-Kadri, {Mhd Omar} and Luca Piras and Andrei Petrovski",

note = "Publisher Copyright: {\textcopyright} 2023 by SCITEPRESS - Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0).; 20th International Conference on Security and Cryptography, SECRYPT 2023 ; Conference date: 10-07-2023 Through 12-07-2023",

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language = "English",

isbn = "9789897586668",

series = "Proceedings of the International Conference on Security and Cryptography",

publisher = "Science and Technology Publications, Lda",

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Senanayake, J, Kalutarage, H, Al-Kadri, MO, Piras, L & Petrovski, A 2023, Labelled Vulnerability Dataset on Android Source Code (LVDAndro) to Develop AI-Based Code Vulnerability Detection Models. in S De Capitani di Vimercati & P Samarati (eds), SECRYPT 2023 - Proceedings of the 20th International Conference on Security and Cryptography. Proceedings of the International Conference on Security and Cryptography, vol. 1, Science and Technology Publications, Lda, pp. 659-666, 20th International Conference on Security and Cryptography, SECRYPT 2023, Rome, Italy, 10/07/23. https://doi.org/10.5220/0012060400003555

Labelled Vulnerability Dataset on Android Source Code (LVDAndro) to Develop AI-Based Code Vulnerability Detection Models. / Senanayake, Janaka; Kalutarage, Harsha; Al-Kadri, Mhd Omar et al.
SECRYPT 2023 - Proceedings of the 20th International Conference on Security and Cryptography. ed. / Sabrina De Capitani di Vimercati; Pierangela Samarati. Science and Technology Publications, Lda, 2023. p. 659-666 (Proceedings of the International Conference on Security and Cryptography; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Piras, Luca

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Senanayake J, Kalutarage H, Al-Kadri MO, Piras L, Petrovski A. Labelled Vulnerability Dataset on Android Source Code (LVDAndro) to Develop AI-Based Code Vulnerability Detection Models. In De Capitani di Vimercati S, Samarati P, editors, SECRYPT 2023 - Proceedings of the 20th International Conference on Security and Cryptography. Science and Technology Publications, Lda. 2023. p. 659-666. (Proceedings of the International Conference on Security and Cryptography). doi: 10.5220/0012060400003555

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

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