{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T02:29:54Z","timestamp":1769740194360,"version":"3.49.0"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2020,6,13]],"date-time":"2020-06-13T00:00:00Z","timestamp":1592006400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,6,13]],"date-time":"2020-06-13T00:00:00Z","timestamp":1592006400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2021,3]]},"DOI":"10.1007\/s00521-020-05039-7","type":"journal-article","created":{"date-parts":[[2020,6,13]],"date-time":"2020-06-13T20:02:32Z","timestamp":1592078552000},"page":"1497-1513","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Format-aware learn&fuzz: deep test data generation for efficient fuzzing"],"prefix":"10.1007","volume":"33","author":[{"given":"Morteza","family":"Zakeri Nasrabadi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4381-2773","authenticated-orcid":false,"given":"Saeed","family":"Parsa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Akram","family":"Kalaee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,6,13]]},"reference":[{"issue":"12","key":"5039_CR1","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1145\/96267.96279","volume":"33","author":"BP Miller","year":"1990","unstructured":"Miller BP, Fredriksen L, So B (1990) An empirical study of the reliability of Unix utilities. Commun ACM 33(12):32\u201344. https:\/\/doi.org\/10.1145\/96267.96279","journal-title":"Commun ACM"},{"key":"5039_CR2","unstructured":"Miller BP, Koski D, Pheow C, Maganty LV, Murthy R, Natarajan A, Steidl J (1995) Fuzz revisited: a re-examination of the reliability of Unix utilities and services. Tech. rep, University of Wisconsin-Madison"},{"key":"5039_CR3","unstructured":"Forrester JE, Miller BP (2000) An empirical study of the robustness of Windows NT applications using random testing. In: Proceedings of the 4th Conference on USENIX Windows Systems Symposium\u2014Volume 4, WSS\u201900, USENIX Association, Berkeley, CA, p 6"},{"key":"5039_CR4","doi-asserted-by":"publisher","unstructured":"Miller BP, Cooksey G, Moore F (2006) An empirical study of the robustness of MacOS applications using random testing. In: Proceedings of the 1st International Workshop on Random Testing, RT \u201906, ACM, New York, pp 46\u201354. https:\/\/doi.org\/10.1145\/1145735.1145743","DOI":"10.1145\/1145735.1145743"},{"key":"5039_CR5","volume-title":"Fuzzing: brute force vulnerability discovery","author":"M Sutton","year":"2007","unstructured":"Sutton M, Greene A, Amini P (2007) Fuzzing: brute force vulnerability discovery. Addison-Wesley Professional, Boston http:\/\/fuzzing.org\/"},{"key":"5039_CR6","doi-asserted-by":"crossref","unstructured":"Rathaus N, Evron G (2007) Open source fuzzing tools. Syngress Publishing","DOI":"10.1016\/B978-159749195-2.00004-8"},{"key":"5039_CR7","doi-asserted-by":"publisher","unstructured":"Pham V-T, B\u00f6hme M, Roychoudhury A (2016) Model-based whitebox fuzzing for program binaries. In: Proceedings of the 31st IEEE\/ACM international conference on automated software engineering, ASE 2016, ACM, New York, pp 543\u2013553. https:\/\/doi.org\/10.1145\/2970276.2970316","DOI":"10.1145\/2970276.2970316"},{"key":"5039_CR8","doi-asserted-by":"crossref","unstructured":"Godefroid P, Peleg H, Singh R (2017) Learn&fuzz: machine learning for input fuzzing. In: Proceedings of the 32nd IEEE\/ACM international conference on automated software engineering, ASE 2017, IEEE Press, Piscataway, pp 50\u201359","DOI":"10.1109\/ASE.2017.8115618"},{"key":"5039_CR9","doi-asserted-by":"crossref","unstructured":"Rawat S, Jain V, Kumar A, Cojocar L, Giuffrida C, Bos H (2017) Vuzzer: application-aware evolutionary fuzzing. In: Proceedings of the network and distributed system security symposium (NDSS)","DOI":"10.14722\/ndss.2017.23404"},{"key":"5039_CR10","unstructured":"Adobe Systems Inc (2006) PDF reference, version 1.7. Available: https:\/\/www.adobe.com\/content\/dam\/acom\/en\/devnet\/acrobat\/pdfs\/pdf_reference_1-7.pdf"},{"key":"5039_CR11","unstructured":"Artifex Software Inc., MuPDF, [Online]. Available: https:\/\/mupdf.com\/. Accessed: 25 July 2018"},{"key":"5039_CR12","doi-asserted-by":"publisher","unstructured":"Wang J, Chen B, Wei L, Liu Y (2017) Skyfire: data-driven seed generation for fuzzing. In: IEEE Symposium on Security and Privacy (SP), pp 579\u2013594. https:\/\/doi.org\/10.1109\/SP.2017.23","DOI":"10.1109\/SP.2017.23"},{"key":"5039_CR13","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1016\/j.cose.2018.02.002","volume":"75","author":"C Chen","year":"2018","unstructured":"Chen C, Cui B, Ma J, Wu R, Guo J, Liu W (2018) A systematic review of fuzzing techniques. Comput Secur 75:118\u2013137. https:\/\/doi.org\/10.1016\/j.cose.2018.02.002","journal-title":"Comput Secur"},{"issue":"1","key":"5039_CR14","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1186\/s42400-018-0002-y","volume":"1","author":"J Li","year":"2018","unstructured":"Li J, Zhao B, Zhang C (2018) Fuzzing: a survey. Cybersecurity 1(1):6. https:\/\/doi.org\/10.1186\/s42400-018-0002-y","journal-title":"Cybersecurity"},{"key":"5039_CR15","unstructured":"Mcnally R, Yiu K, Grove D (2012) Fuzzing: the state of the art. DSTO Defence Science and Technology Organisation, 55"},{"key":"5039_CR16","unstructured":"Zalewsky M, American fuzzy lop, [Online]. Available: http:\/\/lcamtuf.coredump.cx\/afl\/. Accessed 11 Oct 2017"},{"key":"5039_CR17","unstructured":"Rajpal M, Blum W, Singh R, Not all bytes are equal: neural byte sieve for fuzzing, CoRR abs\/1711.04596. arXiv:1711.04596"},{"key":"5039_CR18","unstructured":"Sutskever I, Vinyals O, Le QV (2014) Sequence to sequence learning with neural networks. In: Ghahramani Z, Welling M, Cortes C, Lawrence ND, Weinberger KQ (eds) Advances in neural information processing systems 27. Curran Associates Inc, pp 3104\u20133112"},{"key":"5039_CR19","unstructured":"Cho K, van Merrienboer B, G\u00fcl\u00e7ehre \u00c7, Bougares F, Schwenk H, Bengio Y, Learning phrase representations using RNN encoder-decoder for statistical machine translation, CoRR abs\/1406.1078. arXiv:1406.1078"},{"key":"5039_CR20","doi-asserted-by":"crossref","unstructured":"Mikolov T, Karafit M, Burget L, Cernock J, Khudanpur S (2010) Recurrent neural network based language model 2:1045\u20131048","DOI":"10.21437\/Interspeech.2010-343"},{"key":"5039_CR21","unstructured":"DeMott J, Enbody R, Punch W, Revolutionizing the field of grey-box attack surface testing with evolutionary fuzzing. Defcon 15"},{"key":"5039_CR22","doi-asserted-by":"publisher","unstructured":"Cummins C, Petoumenos P, Murray A, Leather H (2018) Compiler fuzzing through deep learning. In: Proceedings of the 27th ACM SIGSOFT international symposium on software testing and analysis, ISSTA 2018, ACM, New York, pp 95\u2013105. https:\/\/doi.org\/10.1145\/3213846.3213848","DOI":"10.1145\/3213846.3213848"},{"issue":"8","key":"5039_CR23","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735\u20131780. https:\/\/doi.org\/10.1162\/neco.1997.9.8.1735","journal-title":"Neural Comput"},{"key":"5039_CR24","unstructured":"Lv C, Ji S, Li Y, Zhou J, Chen J, Zhou P, Chen J, Smartseed: smart seed generation for efficient fuzzing, CoRR abs\/1807.02606. arXiv:1807.02606"},{"key":"5039_CR25","unstructured":"B\u00f6ttinger K, Godefroid P, Singh R, Deep reinforcement fuzzing, CoRR abs\/1801.04589. arXiv:1801.04589"},{"key":"5039_CR26","doi-asserted-by":"publisher","first-page":"36340","DOI":"10.1109\/ACCESS.2019.2903291","volume":"7","author":"Y Wang","year":"2019","unstructured":"Wang Y, Wu Z, Wei Q, Wang Q (2019) Neufuzz: efficient fuzzing with deep neural network. IEEE Access 7:36340\u201336352","journal-title":"IEEE Access"},{"key":"5039_CR27","unstructured":"Jurafsky D, Martin JH (2017) Speech and language processing (3rd ed. draft). https:\/\/web.stanford.edu\/~jurafsky\/slp3\/"},{"key":"5039_CR28","unstructured":"Luong MT (2016) Neural machine translation, Ph.D Thesis, Stanford University"},{"key":"5039_CR29","volume-title":"Deep learning","author":"I Goodfellow","year":"2016","unstructured":"Goodfellow I, Bengio Y, Courville A (2016) Deep learning. MIT Press, Cambridge"},{"key":"5039_CR30","unstructured":"Karpathy A, The unreasonable effectiveness of recurrent neural networks, [Online]. Available: http:\/\/karpathy.github.io\/2015\/05\/21\/rnn-effectiveness\/. Accessed 21 10 2017"},{"key":"5039_CR31","unstructured":"Chollet F, etal (2015) Keras, https:\/\/keras.io"},{"key":"5039_CR32","unstructured":"Abadi M, Agarwal A, Barham P, Brevdo E, Chen Z, Citro C, Corrado GS, Davis A, Dean J, Devin M, Ghemawat S, Goodfellow IJ, Harp A, Irving G, Isard M, Jia Y, J\u00f3zefowicz R, Kaiser L, Kudlur M, Levenberg J, Man\u00e9 D, Monga R, Moore S, Murray DG, Olah C, Schuster M, Shlens J, Steiner B, Sutskever I, Talwar K, Tucker PA, Vanhoucke V, Vasudevan V, Vi\u00e9gas FB, Vinyals O, Warden P, Wattenberg M, Wicke M, Yu Y, Zheng X, Tensorflow: large-scale machine learning on heterogeneous distributed systems, CoRR abs\/1603.04467. arXiv:1603.04467"},{"key":"5039_CR33","unstructured":"Kingma DP, Ba J, Adam: a method for stochastic optimization, CoRR abs\/1412.6980. arXiv:1412.6980"},{"key":"5039_CR34","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava N, Hinton G, Krizhevsky A, Sutskever I, Salakhutdinov R (2014) Dropout: a simple way to prevent neural networks from overfitting. J Mach Learn Res 15:1929\u20131958","journal-title":"J Mach Learn Res"},{"key":"5039_CR35","volume-title":"Fuzzing for software security testing and quality assurance","author":"A Takanen","year":"2018","unstructured":"Takanen A, Demott JD, Miller C (2018) Fuzzing for software security testing and quality assurance, 2nd edn. Artech House Inc, Norwood","edition":"2"},{"key":"5039_CR36","unstructured":"Mikolov T (2012) Statistical language models based on neural networks, Ph.D. Thesis, Brno University of Technology"},{"key":"5039_CR37","unstructured":"Microsoft, VSPerfMon, [Online]. Available: https:\/\/docs.microsoft.com\/en-us\/visualstudio\/profiling\/vsperfmon?view=vs-2017 Accessed 18 July 2018"},{"key":"5039_CR38","unstructured":"Microsoft, Application verifier (appverif.exe), [Online]. Available: https:\/\/docs.microsoft.com\/en-us\/windows-hardware\/drivers\/debugger\/application-verifier. Accessed 18 July 2018"},{"key":"5039_CR39","unstructured":"Mozilla Labs, PDF.js, [Online]. Available: https:\/\/github.com\/mozilla\/pdf.js\/tree\/master\/test\/pdfs. Accessed 15 Oct 2017"},{"key":"5039_CR40","unstructured":"Goodfellow I, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A, Bengio Y (2014) Generative adversarial nets. In: Ghahramani Z, Welling M, Cortes C, Lawrence ND, Weinberger KQ (eds) Advances in neural information processing systems 27. Curran Associates Inc, pp 2672\u20132680"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-020-05039-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-020-05039-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-020-05039-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,28]],"date-time":"2022-10-28T10:40:51Z","timestamp":1666953651000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-020-05039-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,13]]},"references-count":40,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2021,3]]}},"alternative-id":["5039"],"URL":"https:\/\/doi.org\/10.1007\/s00521-020-05039-7","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,13]]},"assertion":[{"value":"1 June 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 May 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 June 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}