{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T10:06:38Z","timestamp":1789034798134,"version":"build-2803163510"},"publisher-location":"New York, NY, USA","reference-count":24,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,1,11]],"date-time":"2022-01-11T00:00:00Z","timestamp":1641859200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Science and Technology Program of Shanghai Electric Power Company","award":[", 52094020005N"],"award-info":[{"award-number":[", 52094020005N"]}]},{"name":"Shanghai Electric Power AI Research Center","award":[", 19DZ2252800"],"award-info":[{"award-number":[", 19DZ2252800"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,1,11]]},"DOI":"10.1145\/3512850.3512862","type":"proceedings-article","created":{"date-parts":[[2022,4,18]],"date-time":"2022-04-18T10:08:07Z","timestamp":1650276487000},"page":"92-97","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["MLPNeuzz: A Novel Neural Program Smoothing Method Based on Multi-Layer Perceptron"],"prefix":"10.1145","author":[{"given":"Binbin","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Information Technology, State Grid Shanghai Electric Power Research Institute, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mi","family":"Wen","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Shanghai University of Electric Power, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Information Technology, State Grid Shanghai Electric Power Research Institute, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liangliang","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Shanghai University of Electric Power, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zihan","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Shanghai University of Electric Power, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qifan","family":"Mao","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Shanghai University of Electric Power, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,4,18]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Neural byte sieve for fuzzing.\"[J]","author":"Rajpal M","year":"2017","unstructured":"Rajpal M , Blum W , Singh R. \" Not all bytes are equal : Neural byte sieve for fuzzing.\"[J] . 2017 . Rajpal M, Blum W, Singh R. \"Not all bytes are equal: Neural byte sieve for fuzzing.\"[J]. 2017."},{"key":"e_1_3_2_1_2_1","first-page":"2121","volume":"12","author":"Methods","year":"2011","unstructured":"Methods for Online Learning and Stochastic Optimization . Journal of Machine Learning Research , 12 : 2121 \u2013 2159 , 2011 . Methods for Online Learning and Stochastic Optimization. Journal of Machine Learning Research, 12:2121\u20132159, 2011.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_3_1","volume-title":"X. Wang, and Y. Wang. \"An Empirical Study of Counterexample-Guided Fuzzing for Neural Networks Verification.\" 2020 7th International Conference on Dependable Systems and Their Applications (DSA)","author":"Yi","year":"2020","unstructured":"Yi , Gao lei , X. Wang, and Y. Wang. \"An Empirical Study of Counterexample-Guided Fuzzing for Neural Networks Verification.\" 2020 7th International Conference on Dependable Systems and Their Applications (DSA) 2020 . Yi, Gao lei, X. Wang, and Y. Wang. \"An Empirical Study of Counterexample-Guided Fuzzing for Neural Networks Verification.\" 2020 7th International Conference on Dependable Systems and Their Applications (DSA) 2020."},{"key":"e_1_3_2_1_4_1","first-page":"928","article-title":"Generating valid grammar based test inputs by means of genetic programming and annotated grammars","volume":"2017","author":"Kifetew FM","unstructured":"Kifetew FM , Tiella R , Tonella P. \" Generating valid grammar based test inputs by means of genetic programming and annotated grammars .\" In: Empirical Software Engineering; 2017 Apr 14; 22(2). p. 928 \u2013 961 . Kifetew FM, Tiella R, Tonella P. \"Generating valid grammar based test inputs by means of genetic programming and annotated grammars.\" In: Empirical Software Engineering; 2017 Apr 14; 22(2). p. 928\u2013961.","journal-title":"Empirical Software Engineering;"},{"key":"e_1_3_2_1_5_1","first-page":"39","volume-title":"Proceedings of the Fourth ACM International Workshop on Security and Privacy Analytics ACM.","author":"Chernis B","year":"2018","unstructured":"Chernis B , Verma R. \" Machine Learning Methods for Software Vulnerability Detection.\" In: Proceedings of the Fourth ACM International Workshop on Security and Privacy Analytics ACM. 2018 . p. 31\u2013 39 . Chernis B, Verma R. \"Machine Learning Methods for Software Vulnerability Detection.\" In: Proceedings of the Fourth ACM International Workshop on Security and Privacy Analytics ACM. 2018. p. 31\u201339."},{"key":"e_1_3_2_1_6_1","unstructured":"Wikipedia. \"WannaCry ransomware attack.\" 2019. [cited 6 Jul 2019].  Wikipedia. \"WannaCry ransomware attack.\" 2019. [cited 6 Jul 2019]."},{"key":"e_1_3_2_1_7_1","volume-title":"Jana S. NEUZZ: Efficient Fuzzing with Neural Program Smoothing. 2019 IEEE Symposium on Security and Privacy (SP). IEEE,2019","author":"She D","unstructured":"She D , Pei K , Epstein D , Yang J , Jana S. NEUZZ: Efficient Fuzzing with Neural Program Smoothing. 2019 IEEE Symposium on Security and Privacy (SP). IEEE,2019 . She D, Pei K, Epstein D, Yang J, Jana S. NEUZZ: Efficient Fuzzing with Neural Program Smoothing. 2019 IEEE Symposium on Security and Privacy (SP). IEEE,2019."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"crossref","unstructured":"Wang Y Jia P Liu L Huang C Liu Z. \"A systematic review of fuzzing based on machine learning techniques.\" PLoS ONE 15(8) e0237749.2020.  Wang Y Jia P Liu L Huang C Liu Z. \"A systematic review of fuzzing based on machine learning techniques.\" PLoS ONE 15(8) e0237749.2020.","DOI":"10.1371\/journal.pone.0237749"},{"key":"e_1_3_2_1_9_1","unstructured":"Ruder S. \"An overview of gradient descent optimization algorithms.\" 2016.  Ruder S. \"An overview of gradient descent optimization algorithms.\" 2016."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/0893-6080(89)90003-8"},{"key":"e_1_3_2_1_11_1","first-page":"292","volume-title":"InInternational Conference on Computer Aided V erification","author":"Chaudhuri A.","unstructured":"S. Chaudhuri and A. Solar-Lezama . Smoothing a program soundly and robustly . InInternational Conference on Computer Aided V erification , pages 277\u2013 292 . Springer, 2011. S. Chaudhuri and A. Solar-Lezama. Smoothing a program soundly and robustly. InInternational Conference on Computer Aided V erification, pages 277\u2013292. Springer, 2011."},{"key":"e_1_3_2_1_12_1","first-page":"450","volume-title":"Security and Privacy in Computing and Communications (TrustCom)","author":"Li X.","year":"2020","unstructured":"Y. Li , X. Xiao , X. Zhu , X. Chen , S. Wen and B. Zhang , \" SpeedNeuzz: Speed Up Neural Program Approximation with Neighbor Edge Knowledge,\" 2020 IEEE 19th International Conference on Trust , Security and Privacy in Computing and Communications (TrustCom) , 2020 , pp. 450 - 457 , doi: 10.1109\/TrustCom50675.2020.00068. 10.1109\/TrustCom50675.2020.00068 Y. Li, X. Xiao, X. Zhu, X. Chen, S. Wen and B. Zhang, \"SpeedNeuzz: Speed Up Neural Program Approximation with Neighbor Edge Knowledge,\" 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 2020, pp. 450-457, doi: 10.1109\/TrustCom50675.2020.00068."},{"key":"e_1_3_2_1_13_1","first-page":"13","volume-title":"International Conference on Learning Representations","author":"Diederik P.","year":"2015","unstructured":"Diederik P. Kingma and Jimmy Lei Ba. Adam: a Method for Stochastic Optimization . International Conference on Learning Representations , pages 1\u2013 13 , 2015 . Diederik P. Kingma and Jimmy Lei Ba. Adam: a Method for Stochastic Optimization. International Conference on Learning Representations, pages 1\u201313, 2015."},{"key":"e_1_3_2_1_14_1","volume-title":"ICLR Workshop, (1):2013\u20132016","author":"Timothy Dozat","year":"2016","unstructured":"Timothy Dozat . Incorporating Nesterov Momentum into Adam . ICLR Workshop, (1):2013\u20132016 , 2016 . Timothy Dozat. Incorporating Nesterov Momentum into Adam. ICLR Workshop, (1):2013\u20132016,2016."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1109\/SP.2018.00046","volume-title":"Angora: Efficient Fuzzing by Principled Search,\" 2018 IEEE Symposium on Security and Privacy (SP)","author":"Chen H.","year":"2018","unstructured":"P. Chen and H. Chen , \" Angora: Efficient Fuzzing by Principled Search,\" 2018 IEEE Symposium on Security and Privacy (SP) , 2018 , pp. 711 - 725 , doi: 10.1109\/SP.2018.00046. 10.1109\/SP.2018.00046 P. Chen and H. Chen, \"Angora: Efficient Fuzzing by Principled Search,\" 2018 IEEE Symposium on Security and Privacy (SP), 2018, pp. 711-725, doi: 10.1109\/SP.2018.00046."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"crossref","unstructured":"Kim Y. & Yoon J. \"Maxafl: maximizing code coverage with a gradient-based optimization technique.\" Electronics 10(1) 11.2020.  Kim Y. & Yoon J. \"Maxafl: maximizing code coverage with a gradient-based optimization technique.\" Electronics 10(1) 11.2020.","DOI":"10.3390\/electronics10010011"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Chen C. Cui B. Ma J. Wu R. Guo J. & Liu W. A systematic review of fuzzing techniques.Computers & Security 118-137.2018.  Chen C. Cui B. Ma J. Wu R. Guo J. & Liu W. A systematic review of fuzzing techniques.Computers & Security 118-137.2018.","DOI":"10.1016\/j.cose.2018.02.002"},{"key":"e_1_3_2_1_18_1","first-page":"164","volume-title":"ExploitMeter: Combining Fuzzing with Machine Learning for Automated Evaluation of Software Exploitability,\" 2017 IEEE Symposium on Privacy-Aware Computing (PAC)","author":"Yan J.","year":"2017","unstructured":"G. Yan , J. Lu , Z. Shu and Y. Kucuk , \" ExploitMeter: Combining Fuzzing with Machine Learning for Automated Evaluation of Software Exploitability,\" 2017 IEEE Symposium on Privacy-Aware Computing (PAC) , 2017 , pp. 164 - 175 , doi: 10.1109\/PAC.2017.10. 10.1109\/PAC.2017.10 G. Yan, J. Lu, Z. Shu and Y. Kucuk, \"ExploitMeter: Combining Fuzzing with Machine Learning for Automated Evaluation of Software Exploitability,\" 2017 IEEE Symposium on Privacy-Aware Computing (PAC), 2017, pp. 164-175, doi: 10.1109\/PAC.2017.10."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE-Companion.2019.00096"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1883\/1\/012073"},{"key":"e_1_3_2_1_21_1","first-page":"603","volume-title":"LAFuzz: Neural Network for Efficient Fuzzing,\"ICTAI,2020","author":"Wang C.","year":"2020","unstructured":"X. Wang , C. Hu , R. Ma , B. Li and X. Wang , \" LAFuzz: Neural Network for Efficient Fuzzing,\"ICTAI,2020 , pp. 603 - 611 , doi: 10.1109\/ ICTAI 50040. 2020 .00098. X. Wang, C. Hu, R. Ma, B. Li and X. Wang, \"LAFuzz: Neural Network for Efficient Fuzzing,\"ICTAI,2020, pp.603-611, doi: 10.1109\/ ICTAI 50040.2020.00098."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1186\/s42400-021-00087-5"},{"key":"e_1_3_2_1_23_1","first-page":"594","volume-title":"Liu Y. Skyfire: Data-Driven Seed Generation for Fuzzing. In: 2017 IEEE Symposium on Security and Privacy (SP). IEEE;","author":"Wang J","year":"2017","unstructured":"Wang J , Chen B , Wei L , Liu Y. Skyfire: Data-Driven Seed Generation for Fuzzing. In: 2017 IEEE Symposium on Security and Privacy (SP). IEEE; 2017 . p. 579\u2013 594 . Wang J, Chen B, Wei L, Liu Y. Skyfire: Data-Driven Seed Generation for Fuzzing. In: 2017 IEEE Symposium on Security and Privacy (SP). IEEE; 2017. p. 579\u2013594."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"crossref","unstructured":"Zhang Z. Cui B. & Chen C.\" Reinforcement Learning-Based Fuzzing Technology.\" Innovative Mobile and Internet Services in Ubiquitous Computing.2021.  Zhang Z. Cui B. & Chen C.\" Reinforcement Learning-Based Fuzzing Technology.\" Innovative Mobile and Internet Services in Ubiquitous Computing.2021.","DOI":"10.1007\/978-3-030-50399-4_24"}],"event":{"name":"ICCDE 2022: 2022 The 8th International Conference on Computing and Data Engineering","location":"Bangkok Thailand","acronym":"ICCDE 2022"},"container-title":["2022 The 8th International Conference on Computing and Data Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3512850.3512862","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3512850.3512862","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:12:27Z","timestamp":1750191147000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3512850.3512862"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,11]]},"references-count":24,"alternative-id":["10.1145\/3512850.3512862","10.1145\/3512850"],"URL":"https:\/\/doi.org\/10.1145\/3512850.3512862","relation":{},"subject":[],"published":{"date-parts":[[2022,1,11]]},"assertion":[{"value":"2022-04-18","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}