{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,5]],"date-time":"2026-04-05T20:37:38Z","timestamp":1775421458716,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":34,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,9,19]],"date-time":"2022-09-19T00:00:00Z","timestamp":1663545600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1936121"],"award-info":[{"award-number":["U1936121"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,9,19]]},"DOI":"10.1145\/3544902.3546240","type":"proceedings-article","created":{"date-parts":[[2022,9,7]],"date-time":"2022-09-07T04:07:45Z","timestamp":1662523665000},"page":"205-215","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["PG-VulNet: Detect Supply Chain Vulnerabilities in IoT Devices using Pseudo-code and Graphs"],"prefix":"10.1145","author":[{"given":"Xin","family":"Liu","sequence":"first","affiliation":[{"name":"Lanzhou University, China"}]},{"given":"Yixiong","family":"Wu","sequence":"additional","affiliation":[{"name":"Tsinghua University, China"}]},{"given":"Qingchen","family":"Yu","sequence":"additional","affiliation":[{"name":"Zhejiang University, China"}]},{"given":"Shangru","family":"Song","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology, China"}]},{"given":"Yue","family":"Liu","sequence":"additional","affiliation":[{"name":"Southeast University, China and Qi An Xin Group Corp, China"}]},{"given":"Qingguo","family":"Zhou","sequence":"additional","affiliation":[{"name":"Lanzhou University, China"}]},{"given":"Jianwei","family":"Zhuge","sequence":"additional","affiliation":[{"name":"Tsinghua University, China"}]}],"member":"320","published-online":{"date-parts":[[2022,9,19]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"30th USENIX Security Symposium (USENIX Security 21)","author":"Ahmadi Mansour","year":"2021","unstructured":"Mansour Ahmadi , Reza\u00a0Mirzazade farkhani, Ryan Williams , and Long Lu . 2021 . Finding Bugs Using Your Own Code: Detecting Functionally-similar yet Inconsistent Code . In 30th USENIX Security Symposium (USENIX Security 21) . USENIX Association. https:\/\/www.usenix.org\/conference\/usenixsecurity21\/presentation\/ahmadi Mansour Ahmadi, Reza\u00a0Mirzazade farkhani, Ryan Williams, and Long Lu. 2021. Finding Bugs Using Your Own Code: Detecting Functionally-similar yet Inconsistent Code. In 30th USENIX Security Symposium (USENIX Security 21). USENIX Association. https:\/\/www.usenix.org\/conference\/usenixsecurity21\/presentation\/ahmadi"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/390013.808479"},{"key":"e_1_3_2_1_3_1","volume-title":"ACMSIGPLAN Workshop on Compiler Support for System Software (WCSS). Citeseer, 1\u201310","author":"Baker S","year":"1999","unstructured":"Brenda\u00a0 S Baker , Udi Manber , and Robert Muth . 1999 . Compressing differences of executable code . In ACMSIGPLAN Workshop on Compiler Support for System Software (WCSS). Citeseer, 1\u201310 . Brenda\u00a0S Baker, Udi Manber, and Robert Muth. 1999. Compressing differences of executable code. In ACMSIGPLAN Workshop on Compiler Support for System Software (WCSS). Citeseer, 1\u201310."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2430553.2430557"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2950290.2950350"},{"key":"e_1_3_2_1_6_1","volume-title":"International conference on machine learning. PMLR, 2702\u20132711","author":"Dai Hanjun","year":"2016","unstructured":"Hanjun Dai , Bo Dai , and Le Song . 2016 . Discriminative embeddings of latent variable models for structured data . In International conference on machine learning. PMLR, 2702\u20132711 . Hanjun Dai, Bo Dai, and Le Song. 2016. Discriminative embeddings of latent variable models for structured data. In International conference on machine learning. PMLR, 2702\u20132711."},{"key":"e_1_3_2_1_7_1","volume-title":"Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805(2018).","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin , Ming-Wei Chang , Kenton Lee , and Kristina Toutanova . 2018 . Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805(2018). Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805(2018)."},{"key":"e_1_3_2_1_8_1","volume-title":"DeepBinDiff: Learning program-wide code representations for binary diffing. eScholarship","author":"Duan Yue","unstructured":"Yue Duan , Xuezixiang Li , Jinghan Wang , and Heng Yin . 2020. DeepBinDiff: Learning program-wide code representations for binary diffing. eScholarship , University of California . Yue Duan, Xuezixiang Li, Jinghan Wang, and Heng Yin. 2020. DeepBinDiff: Learning program-wide code representations for binary diffing. eScholarship, University of California."},{"key":"e_1_3_2_1_9_1","first-page":"3","article-title":"Graph-based comparison of executable objects (english version)","volume":"5","author":"Dullien Thomas","year":"2005","unstructured":"Thomas Dullien and Rolf Rolles . 2005 . Graph-based comparison of executable objects (english version) . Sstic 5 , 1 (2005), 3 . Thomas Dullien and Rolf Rolles. 2005. Graph-based comparison of executable objects (english version). Sstic 5, 1 (2005), 3.","journal-title":"Sstic"},{"key":"e_1_3_2_1_10_1","volume-title":"23rd {USENIX} Security Symposium ({USENIX} Security 14). 303\u2013317.","author":"Egele Manuel","unstructured":"Manuel Egele , Maverick Woo , Peter Chapman , and David Brumley . 2014. Blanket execution: Dynamic similarity testing for program binaries and components . In 23rd {USENIX} Security Symposium ({USENIX} Security 14). 303\u2013317. Manuel Egele, Maverick Woo, Peter Chapman, and David Brumley. 2014. Blanket execution: Dynamic similarity testing for program binaries and components. In 23rd {USENIX} Security Symposium ({USENIX} Security 14). 303\u2013317."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"crossref","unstructured":"Sebastian Eschweiler Khaled Yakdan and Elmar Gerhards-Padilla. 2016. discovRE: Efficient Cross-Architecture Identification of Bugs in Binary Code.. In NDSS Vol.\u00a052. 58\u201379.  Sebastian Eschweiler Khaled Yakdan and Elmar Gerhards-Padilla. 2016. discovRE: Efficient Cross-Architecture Identification of Bugs in Binary Code.. In NDSS Vol.\u00a052. 58\u201379.","DOI":"10.14722\/ndss.2016.23185"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978370"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/24039.24041"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-88625-9_16"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3236024.3275524"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3238147.3240480"},{"key":"e_1_3_2_1_17_1","unstructured":"kadiska. 2021. IoT performance: What\u2019s at stake?https:\/\/www.kadiska.com\/go-deeper\/connectivity-performance-monitoring-for-iot-vendors\/  kadiska. 2021. IoT performance: What\u2019s at stake?https:\/\/www.kadiska.com\/go-deeper\/connectivity-performance-monitoring-for-iot-vendors\/"},{"key":"e_1_3_2_1_18_1","volume-title":"International Conference on Machine Learning. PMLR, 3835\u20133845","author":"Li Yujia","year":"2019","unstructured":"Yujia Li , Chenjie Gu , Thomas Dullien , Oriol Vinyals , and Pushmeet Kohli . 2019 . Graph matching networks for learning the similarity of graph structured objects . In International Conference on Machine Learning. PMLR, 3835\u20133845 . Yujia Li, Chenjie Gu, Thomas Dullien, Oriol Vinyals, and Pushmeet Kohli. 2019. Graph matching networks for learning the similarity of graph structured objects. In International Conference on Machine Learning. PMLR, 3835\u20133845."},{"key":"e_1_3_2_1_19_1","unstructured":"Yujia Li Daniel Tarlow Marc Brockschmidt and Richard Zemel. 2015. Gated graph sequence neural networks. arXiv preprint arXiv:1511.05493(2015).  Yujia Li Daniel Tarlow Marc Brockschmidt and Richard Zemel. 2015. Gated graph sequence neural networks. arXiv preprint arXiv:1511.05493(2015)."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2020.102032"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3238147.3238199"},{"key":"e_1_3_2_1_22_1","volume-title":"International Conference on Information Security and Cryptology. Springer, 92\u2013109","author":"Ming Jiang","year":"2012","unstructured":"Jiang Ming , Meng Pan , and Debin Gao . 2012 . iBinHunt: Binary hunting with inter-procedural control flow . In International Conference on Information Security and Cryptology. Springer, 92\u2013109 . Jiang Ming, Meng Pan, and Debin Gao. 2012. iBinHunt: Binary hunting with inter-procedural control flow. In International Conference on Information Security and Cryptology. Springer, 92\u2013109."},{"key":"e_1_3_2_1_23_1","volume-title":"On spectral clustering: Analysis and an algorithm. Advances in neural information processing systems 14","author":"Ng Andrew","year":"2001","unstructured":"Andrew Ng , Michael Jordan , and Yair Weiss . 2001. On spectral clustering: Analysis and an algorithm. Advances in neural information processing systems 14 ( 2001 ), 849\u2013856. Andrew Ng, Michael Jordan, and Yair Weiss. 2001. On spectral clustering: Analysis and an algorithm. Advances in neural information processing systems 14 (2001), 849\u2013856."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2015.49"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/2664243.2664269"},{"key":"e_1_3_2_1_26_1","unstructured":"Zheng Wang Ken Pierce and Scott McFarling. 1999. Bmat-a binary matching tool. Feedback-Directed Optimization (FDO2)(1999).  Zheng Wang Ken Pierce and Scott McFarling. 1999. Bmat-a binary matching tool. Feedback-Directed Optimization (FDO2)(1999)."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134018"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2014.44"},{"key":"e_1_3_2_1_29_1","unstructured":"Cheng Yang Zhiyuan Liu Deli Zhao Maosong Sun and Edward\u00a0Y Chang. 2015. Network representation learning with rich text information.. In IJCAI Vol.\u00a02015. 2111\u20132117.  Cheng Yang Zhiyuan Liu Deli Zhao Maosong Sun and Edward\u00a0Y Chang. 2015. Network representation learning with rich text information.. In IJCAI Vol.\u00a02015. 2111\u20132117."},{"key":"e_1_3_2_1_30_1","volume-title":"Asteria: Deep Learning-based AST-Encoding for Cross-platform Binary Code Similarity Detection. In 2021 51st Annual IEEE\/IFIP International Conference on Dependable Systems and Networks (DSN)","author":"Yang Shouguo","year":"2021","unstructured":"Shouguo Yang , Long Cheng , Yicheng Zeng , Zhe Lang , Hongsong Zhu , and Zhiqiang Shi . 2021 . Asteria: Deep Learning-based AST-Encoding for Cross-platform Binary Code Similarity Detection. In 2021 51st Annual IEEE\/IFIP International Conference on Dependable Systems and Networks (DSN) . IEEE , 224\u2013236. Shouguo Yang, Long Cheng, Yicheng Zeng, Zhe Lang, Hongsong Zhu, and Zhiqiang Shi. 2021. Asteria: Deep Learning-based AST-Encoding for Cross-platform Binary Code Similarity Detection. In 2021 51st Annual IEEE\/IFIP International Conference on Dependable Systems and Networks (DSN). IEEE, 224\u2013236."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5466"},{"key":"e_1_3_2_1_32_1","volume-title":"Devign: Effective vulnerability identification by learning comprehensive program semantics via graph neural networks. arXiv preprint arXiv:1909.03496(2019).","author":"Zhou Yaqin","year":"2019","unstructured":"Yaqin Zhou , Shangqing Liu , Jingkai Siow , Xiaoning Du , and Yang Liu . 2019 . Devign: Effective vulnerability identification by learning comprehensive program semantics via graph neural networks. arXiv preprint arXiv:1909.03496(2019). Yaqin Zhou, Shangqing Liu, Jingkai Siow, Xiaoning Du, and Yang Liu. 2019. Devign: Effective vulnerability identification by learning comprehensive program semantics via graph neural networks. arXiv preprint arXiv:1909.03496(2019)."},{"key":"e_1_3_2_1_33_1","unstructured":"Yanqiao Zhu Yichen Xu Feng Yu Qiang Liu Shu Wu and Liang Wang. 2020. Deep graph contrastive representation learning. arXiv preprint arXiv:2006.04131(2020).  Yanqiao Zhu Yichen Xu Feng Yu Qiang Liu Shu Wu and Liang Wang. 2020. Deep graph contrastive representation learning. arXiv preprint arXiv:2006.04131(2020)."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"crossref","unstructured":"Fei Zuo Xiaopeng Li Patrick Young Lannan Luo Qiang Zeng and Zhexin Zhang. 2018. Neural machine translation inspired binary code similarity comparison beyond function pairs. arXiv preprint arXiv:1808.04706(2018).  Fei Zuo Xiaopeng Li Patrick Young Lannan Luo Qiang Zeng and Zhexin Zhang. 2018. Neural machine translation inspired binary code similarity comparison beyond function pairs. arXiv preprint arXiv:1808.04706(2018).","DOI":"10.14722\/ndss.2019.23492"}],"event":{"name":"ESEM '22: ACM \/ IEEE International Symposium on Empirical Software Engineering and Measurement","location":"Helsinki Finland","acronym":"ESEM '22","sponsor":["SIGSOFT ACM Special Interest Group on Software Engineering"]},"container-title":["Proceedings of the 16th ACM \/ IEEE International Symposium on Empirical Software Engineering and Measurement"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3544902.3546240","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3544902.3546240","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:00:01Z","timestamp":1750186801000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3544902.3546240"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,19]]},"references-count":34,"alternative-id":["10.1145\/3544902.3546240","10.1145\/3544902"],"URL":"https:\/\/doi.org\/10.1145\/3544902.3546240","relation":{},"subject":[],"published":{"date-parts":[[2022,9,19]]},"assertion":[{"value":"2022-09-19","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}