{"type":"ScholarlyArticle","title":"iDev: Enhancing Social Coding Security by Cross-platform User Identification Between GitHub and Stack Overflow","authors":[{"name":"Yujie Fan","slug":"yujie-fan","given":"Yujie","family":"Fan","affiliation":"Department of CDS , Case Western Reserve University , OH , USA; Department of CSEE , West Virginia University , WV , USA"},{"name":"Yiming Zhang","slug":"yiming-zhang","given":"Yiming","family":"Zhang","affiliation":"Department of CDS , Case Western Reserve University , OH , USA; Department of CSEE , West Virginia University , WV , USA"},{"name":"Shifu Hou","slug":"shifu-hou","given":"Shifu","family":"Hou","affiliation":"Department of CDS , Case Western Reserve University , OH , USA; Department of CSEE , West Virginia University , WV , USA"},{"name":"Lingwei Chen","slug":"lingwei-chen","given":"Lingwei","family":"Chen","affiliation":"Department of CSEE , West Virginia University , WV , USA"},{"name":"Yanfang Ye","slug":"yanfang-ye","given":"Yanfang","family":"Ye","affiliation":"Department of CDS , Case Western Reserve University , OH , USA; Department of CSEE , West Virginia University , WV , USA"},{"name":"Chuan Shi","slug":"chuan-shi","given":"Chuan","family":"Shi","affiliation":"School of CS , Beijing University of Posts and Telecommunications , Beijing , China"},{"name":"Liang Zhao","slug":"liang-zhao","given":"Liang","family":"Zhao","affiliation":"Department of IST , George Mason University , VA , USA"},{"name":"Shouhuai Xu","slug":"shouhuai-xu","given":"Shouhuai","family":"Xu","affiliation":"Department of CS , University of Texas at San Antonio , TX , USA"}],"abstract":"As modern social coding platforms such as GitHub and Stack Overflow become increasingly popular, their potential security risks increase as well (e.g., risky or malicious codes could be easily embedded and distributed). To enhance the social coding security, in this paper, we propose to automate cross-platform user identification between GitHub and Stack Overflow to combat the attackers who attempt to poison the modern software programming ecosystem. To solve this problem, an important insight brought by this work is to leverage social coding properties in addition to user attributes for cross-platform user identification. To depict users in GitHub and Stack Overflow (attached with attributed information), projects, questions and answers as well as the rich semantic relations among them, we first introduce an attributed heterogeneous information network (AHIN) for modeling. Then, we propose a novel AHIN representation learning model AHIN2Vec to efficiently learn node (i.e., user) representations in AHIN for cross-platform user identification. Comprehensive experiments on the data collections from GitHub and Stack Overflow are conducted to validate the effectiveness of our developed system iDev integrating our proposed method in cross-platform user identification by comparisons with other baselines.","doi":"10.24963/ijcai.2019/315","url":"https://ijcai.org/proceedings/2019/315","pdf":"https://ijcai.org/proceedings/2019/0315.pdf","markdown":"https://ijcai.org/proceedings/2019/315.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/315","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Machine Learning A-L","track":"Main track","number":315,"pages":{"first":2272,"last":2278},"keywords":["Multidisciplinary Topics and Applications: Security and Privacy","Machine Learning: Data Mining"],"videos":[],"references":[{"position":1,"raw":"[Baltes et al., 2017] Sebastian Baltes, Richard Kiefer, and Stephan Diehl. 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