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Disentangled Representation Learning in Heterogeneous Information Network for Large-scale Android Malware Detection in the COVID-19 Era and Beyond

Autor: Shifu Hou, Yujie Fan, Mingxuan Ju, Yanfang Ye, Wenqiang Wan, Kui Wang, Yinming Mei, Qi Xiong, Fudong Shao

Publikováno v: Proceedings of the AAAI Conference on Artificial Intelligence. 35:7754-7761

In the fight against the COVID-19 pandemic, many social activities have moved online; society's overwhelming reliance on the complex cyberspace makes its security more important than ever. In this paper, we propose and develop an intelligent system n

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::fe0cd34803f716ea4b99fa81f3145235
https://doi.org/10.1609/aaai.v35i9.16947

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dStyle-GAN: Generative Adversarial Network based on Writing and Photography Styles for Drug Identification in Darknet Markets

Autor: Yujie Fan, Fudong Shao, Yanfang Ye, Yiyue Qian, Xin Li, Yiming Zhang, Qi Xiong

Publikováno v: ACSAC

Despite the persistent effort by law enforcement, illicit drug trafficking in darknet markets has shown great resilience with new markets rapidly appearing after old ones being shut down. In order to more effectively detect, disrupt and dismantle ill

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e78cd600ce94beaad3a427ffe650811b
https://doi.org/10.1145/3427228.3427603

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Metagraph Aggregated Heterogeneous Graph Neural Network for Illicit Traded Product Identification in Underground Market

Autor: Qian Peng, Liang Zhao, Yanfang Ye, Chuan Shi, Jianfei Zhang, Xusheng Xiao, Qi Xiong, Yujie Fan, Fudong Shao, Yiming Zhang

Publikováno v: ICDM

The emerging underground markets (e.g., Hack Forums) have been widely used by cybercriminals to trade in illicit products or services, which have played a vital role in the cybercriminal ecosystem. In order to combat the evolving cybercrimes, in this

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c1b837f41bc11f5d36270c81a925d9e8
https://doi.org/10.1109/icdm50108.2020.00022

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αCyber : Enhancing Robustness of Android Malware Detection System against Adversarial Attacks on Heterogeneous Graph based Model

Autor: Jingwei Lei, Fudong Shao, Wenqiang Wan, Yiming Zhang, Shifu Hou, Jiabin Wang, Yanfang Ye, Qi Xiong, Yujie Fan

Publikováno v: CIKM

The explosive growth and increasing sophistication of Android malware call for new defensive techniques that are capable of protecting mobile users against novel threats. To combat the evolving Android malware attacks, systems of HinDroid and AiDroid

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ce9c8f98f07928490bb72d64de3ecbbf
https://doi.org/10.1145/3357384.3357875

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Out-of-sample Node Representation Learning for Heterogeneous Graph in Real-time Android Malware Detection

Autor: Wenqiang Wan, Fudong Shao, Jiabin Wang, Jingwei Lei, Qi Xiong, Shifu Hou, Yanfang Ye, Lingwei Chen

Publikováno v: IJCAI

The increasingly sophisticated Android malware calls for new defensive techniques that are capable of protecting mobile users against novel threats. In this paper, we first extract the runtime Application Programming Interface (API) call sequences fr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0c896f1e2acb5d743ee001f6c7aeba09
https://doi.org/10.24963/ijcai.2019/576

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KADetector: Automatic Identification of Key Actors in Online Hack Forums Based on Structured Heterogeneous Information Network

Autor: Fudong Shao, Yiming Zhang, Qi Xiong, Yujie Fan, Liang Zhao, Yanfang Ye, Jiabin Wang

Publikováno v: ICBK

Underground forums have been widely used by cybercriminals to exchange knowledge and trade in illicit products or services, which have played a central role in the cybercriminal ecosystem. In order to facilitate the deployment of effective countermea

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4673b6bb655019142e88b722d6368f00
https://doi.org/10.1109/icbk.2018.00028

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