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Pregled bibliografske jedinice broj: 816712

Evaluation of Android Malware Detection Based on System Calls


Dimjašević, Marko; Atzeni, Simone; Ugrina, Ivo; Rakamarić, Zvonimir
Evaluation of Android Malware Detection Based on System Calls // Proceedings of the 2016 ACM on International Workshop on Security And Privacy Analytics
New York (NY): The Association for Computing Machinery (ACM), 2016. str. 1-8 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


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Naslov
Evaluation of Android Malware Detection Based on System Calls

Autori
Dimjašević, Marko ; Atzeni, Simone ; Ugrina, Ivo ; Rakamarić, Zvonimir

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 2016 ACM on International Workshop on Security And Privacy Analytics / - New York (NY) : The Association for Computing Machinery (ACM), 2016, 1-8

ISBN
978-1-4503-4077-9

Skup
IWSPA ’16 (2016 ACM on International Workshop on Security And Privacy Analytics)

Mjesto i datum
New Orleans (LA), Sjedinjene Američke Države, 09.04.2016. - 11.04.2016

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Android; Malware; System Call

Sažetak
With Android being the most widespread mobile platform, protecting it against malicious applications is essential. Android users typically install applications from large remote repositories, which provides ample opportunities for malicious newcomers. In this paper, we evaluate a few techniques for detecting malicious Android applications on a repository level. The techniques perform automatic classification based on tracking system calls while applications are executed in a sandbox environment. We implemented the techniques in the MALINE tool, and performed extensive empirical evaluation on a suite of around 12, 000 applications. The evaluation considers the size and type of inputs used in analyses. We show that simple and relatively small inputs result in an overall detection accuracy of 93% with a 5% benign application classification error, while results are improved to a 96% detection accuracy with upsampling. Finally, we show that even simplistic feature choices are effective, suggesting that more heavyweight approaches should be thoroughly (re)evaluated.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Računarstvo



POVEZANOST RADA


Ustanove:
Sveučilište u Zagrebu

Profili:

Avatar Url Ivo Ugrina (autor)

Citiraj ovu publikaciju:

Dimjašević, Marko; Atzeni, Simone; Ugrina, Ivo; Rakamarić, Zvonimir
Evaluation of Android Malware Detection Based on System Calls // Proceedings of the 2016 ACM on International Workshop on Security And Privacy Analytics
New York (NY): The Association for Computing Machinery (ACM), 2016. str. 1-8 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Dimjašević, M., Atzeni, S., Ugrina, I. & Rakamarić, Z. (2016) Evaluation of Android Malware Detection Based on System Calls. U: Proceedings of the 2016 ACM on International Workshop on Security And Privacy Analytics.
@article{article, author = {Dimja\v{s}evi\'{c}, Marko and Atzeni, Simone and Ugrina, Ivo and Rakamari\'{c}, Zvonimir}, year = {2016}, pages = {1-8}, keywords = {Android, Malware, System Call}, isbn = {978-1-4503-4077-9}, title = {Evaluation of Android Malware Detection Based on System Calls}, keyword = {Android, Malware, System Call}, publisher = {The Association for Computing Machinery (ACM)}, publisherplace = {New Orleans (LA), Sjedinjene Ameri\v{c}ke Dr\v{z}ave} }
@article{article, author = {Dimja\v{s}evi\'{c}, Marko and Atzeni, Simone and Ugrina, Ivo and Rakamari\'{c}, Zvonimir}, year = {2016}, pages = {1-8}, keywords = {Android, Malware, System Call}, isbn = {978-1-4503-4077-9}, title = {Evaluation of Android Malware Detection Based on System Calls}, keyword = {Android, Malware, System Call}, publisher = {The Association for Computing Machinery (ACM)}, publisherplace = {New Orleans (LA), Sjedinjene Ameri\v{c}ke Dr\v{z}ave} }




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