Detecting Malicious Accounts in Online Developer Communities Using Deep Learning

Qingyuan Gong, Jiayun Zhang, Yang Chen, Qi Li, Yu Xiao, Xin Wang, Pan Hui

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

55 Lataukset (Pure)

Abstrakti

Online developer communities like GitHub provide services such as distributed version control and task management, which allow a massive number of developers to collaborate online. However, the openness of the communities makes themselves vulnerable to different types of malicious attacks, since the attackers can easily join and interact with legitimate users. In this work, we formulate the malicious account detection problem in online developer communities, and propose GitSec, a deep learning-based solution to detect malicious accounts. GitSec distinguishes malicious accounts from legitimate ones based on the account profiles as well as dynamic activity characteristics. On one hand, GitSec makes use of users' descriptive features from the profiles. On the other hand, GitSec processes users' dynamic behavioral data by constructing two user activity sequences and applying a parallel neural network design to deal with each of them, respectively. An attention mechanism is used to integrate the information generated by the parallel neural networks. The final judgement is made by a decision maker implemented by a supervised machine learning-based classifier. Based on the real-world data of GitHub users, our extensive evaluations show that GitSec is an accurate detection system, with an F1-score of 0.922 and an AUC value of 0.940.
AlkuperäiskieliEnglanti
OtsikkoCIKM '19:Proceedings of the 28th ACM International Conference on Information and Knowledge Management
KustantajaACM
Sivut1251-1260
ISBN (elektroninen)978-1-4503-6976-3
DOI - pysyväislinkit
TilaJulkaistu - marraskuuta 2019
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaACM International Conference on Information & Knowledge Management - Beijing, Beijing, Kiina
Kesto: 3 marraskuuta 20197 marraskuuta 2019
Konferenssinumero: 28
http://www.cikm2019.net/

Julkaisusarja

NimiACM International Conference on Information & Knowledge Management
ISSN (painettu)2155-0751

Conference

ConferenceACM International Conference on Information & Knowledge Management
LyhennettäCIKM
MaaKiina
KaupunkiBeijing
Ajanjakso03/11/201907/11/2019
www-osoite

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    Siteeraa tätä

    Gong, Q., Zhang, J., Chen, Y., Li, Q., Xiao, Y., Wang, X., & Hui, P. (2019). Detecting Malicious Accounts in Online Developer Communities Using Deep Learning. teoksessa CIKM '19:Proceedings of the 28th ACM International Conference on Information and Knowledge Management (Sivut 1251-1260). (ACM International Conference on Information & Knowledge Management). ACM. https://doi.org/10.1145/3357384.3357971