{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T06:22:27Z","timestamp":1775802147366,"version":"3.50.1"},"reference-count":35,"publisher":"Tech Science Press","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2024]]},"DOI":"10.32604\/cmc.2024.041949","type":"journal-article","created":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T03:11:39Z","timestamp":1721185899000},"page":"3263-3287","source":"Crossref","is-referenced-by-count":4,"title":["Software Vulnerability Mining and Analysis Based on Deep Learning"],"prefix":"10.32604","volume":"80","author":[{"given":"Shibin","family":"Zhao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junhu","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianshan","family":"Peng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"17807","published-online":{"date-parts":[[2024]]},"reference":[{"key":"ref1","first-page":"3059","article-title":"A survey of research on smart contract security vulnerability detection technology","volume":"33","author":"Qian","year":"2022","journal-title":"J. Softw."},{"key":"ref2","first-page":"39","article-title":"Mirai botnet malware analysis and monitoring data research","volume":"3","author":"Chen","year":"2017","journal-title":"J. Net. Inform. Security"},{"key":"ref3","first-page":"47","article-title":"Analysis of hacking incidents in the field of digital currency and encryption","volume":"2020","author":"Wang","year":"2020","journal-title":"Comput. Netw."},{"key":"ref4","first-page":"2140","article-title":"Software security vulnerability mining based on deep learning","volume":"58","author":"Gu","year":"2021","journal-title":"J. Compt. Res. Develop."},{"key":"ref5","doi-asserted-by":"crossref","unstructured":"Z. Li et al., \u201cVulDeePecker: A deep learning-based system for vulnerability detection,\u201d arXiv preprint arXiv:1801.01681, 2018.","DOI":"10.14722\/ndss.2018.23158"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TDSC.2019.2942930","volume":"3","author":"Zou","year":"2019","journal-title":"IEEE Trans. Dependable Secure Comput."},{"key":"ref7","first-page":"1","article-title":"Software vulnerability mining techniques based on data fusion and reverse engineering","volume":"2022","author":"Liu","year":"2022","journal-title":"Wirel. Commun. Mob. Comput."},{"key":"ref8","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1016\/j.comcom.2022.10.021","article-title":"Static vulnerability mining of IoT devices based on control flow graph construction and graph embedding network","volume":"197","author":"Cheng","year":"2023","journal-title":"Comput. Commun."},{"key":"ref9","doi-asserted-by":"crossref","first-page":"1305","DOI":"10.1002\/spe.872","article-title":"ANTLRWorks: An ANTLR grammar development environment","volume":"38","author":"Bovet","year":"2008","journal-title":"Softw. Pract. Exper."},{"key":"ref10","series-title":"IEEE INFOCOM, 2020\u2013IEEE Conf. Comput. Commun. Works. (INFOCOM WKSHPS)","first-page":"722","article-title":"Efficient vulnerability detection based on abstract syntax tree and Deep Learning","author":"Feng","year":"2020"},{"key":"ref11","series-title":"2020 IEEE 19th Int. Conf. on Trust, Security and Privacy in Computing and Communications (TrustCom)","first-page":"539","article-title":"FTCLNet: Convolutional LSTM with fourier transform for vulnerability detection","author":"Cao","year":"2020"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2021\/2922728","article-title":"Risk prediction by using artificial neural network in global software development","volume":"2021","author":"Iftikhar","year":"2021","journal-title":"Comput. Intell. Neurosci."},{"key":"ref13","series-title":"2020 IEEE 19th Int. Conf. on Trust, Security and Privacy in Computing and Communications (TrustCom)","first-page":"1664","article-title":"An efficient vulnerability extrapolation using similarity of graph kernel of PDGs","author":"Zeng","year":"2020"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"1692","DOI":"10.3390\/app10051692","article-title":"Automated vulnerability detection in source code using minimum intermediate representation learning","volume":"10","author":"Li","year":"2020","journal-title":"Appl. Sci."},{"key":"ref15","first-page":"17","article-title":"Identity vulnerability fix commits automatically using hierarchical attention network","volume":"7","author":"Sun","year":"2018","journal-title":"Secur. Safe."},{"key":"ref16","first-page":"1","author":"Nembhard","year":"2018","journal-title":"SoutheastCon 2018"},{"key":"ref17","unstructured":"C. D. Sestili, W. S. Snavely, and N. M. VanHoudnos, \u201cTowards security defect prediction with AI,\u201d arXiv preprint arXiv:1808.09897, 2018."},{"key":"ref18","series-title":"Int. Conf. on Learning Representations","article-title":"Maximal divergence sequential autoencoder for binary software vulnerability detection","author":"Le","year":"2019"},{"key":"ref19","first-page":"10197","article-title":"Devign: Effective vulnerability identification by learning comprehensive program semantics via graph neural networks","volume":"2019","author":"Zhou","year":"2019","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref20","series-title":"2021 IEEE 11th Annu. Comput. Commun. Workshop Conf. (CCWC)","first-page":"1519","article-title":"Vulnerability detection in C\/C++ source code with graph representation learning","author":"Wu","year":"2021"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"197158","DOI":"10.1109\/ACCESS.2020.3034766","article-title":"Software vulnerability analysis and discovery using deep learning techniques: A survey","volume":"8","author":"Zeng","year":"2020","journal-title":"IEEE Access"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"516","DOI":"10.1049\/sfw2.12066","article-title":"A deep learning-based approach for software vulnerability detection using code metrics","volume":"16","author":"Subhan","year":"2022","journal-title":"IET Software"},{"key":"ref23","first-page":"21","article-title":"Source code vulnerability mining method based on graph neural network","volume":"4","author":"Li","year":"2022","journal-title":"Int. J. Front. Eng. Technol."},{"key":"ref24","author":"Koolin","year":"2020","journal-title":"Research on Vulnerability Detection Method Based on BiLSTM Model"},{"key":"ref25","first-page":"1471","article-title":"Evaluating the impact of prediction techniques: Software reliability perspective","volume":"67","author":"Sahu","year":"2021","journal-title":"Comput., Mater. Contin."},{"key":"ref26","first-page":"3","article-title":"A survey of computer security vulnerabilities detection technology","volume":"2012","author":"Song","year":"2012","journal-title":"Inf. Net. Security"},{"key":"ref27","first-page":"1","article-title":"A survey of source code-oriented static detection of software vulnerabilities","volume":"5","author":"Li","year":"2019","journal-title":"J. Net. Inf. Security"},{"key":"ref28","first-page":"27","article-title":"A survey of software and network security research","volume":"29","author":"Liu","year":"2018","journal-title":"J. Softw."},{"key":"ref29","series-title":"Third Int. Conf. on Software Testing, Verification and Validation","first-page":"421","article-title":"Searching for a needle in a haystack: Predicting security vulnerabilities for windows vista","author":"Zimmermann","year":"2010"},{"key":"ref30","first-page":"042197","article-title":"A review on javascript engine vulnerability mining","volume":"1744","author":"Kang","year":"2021","journal-title":"J. Phys.: Conf. Ser."},{"key":"ref31","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1145\/24039.24041","article-title":"The program dependence graph and its use in optimization","volume":"9","author":"Ferrante","year":"1987","journal-title":"ACM Trans. Program. Lang. Syst. (TOPLAS)"},{"key":"ref32","series-title":"Proc. 4th ACM SIGSOFT Int. Workshop on Software Analytics","first-page":"30","article-title":"Towards a framework for generating program dependence graphs from source code","author":"Marin Victor","year":"2018"},{"key":"ref33","doi-asserted-by":"crossref","first-page":"2244","DOI":"10.1109\/TDSC.2021.3051525","article-title":"SySeVR: A framework for using deep learning to detect software vulnerabilities","volume":"19","author":"Li","year":"2021","journal-title":"IEEE Trans. Dependable Secure Comput."},{"key":"ref34","unstructured":"Y. Goldberg and O. Levy, \u201cword2vec Explained: Deriving Mikolov et al.\u2019s negative-sampling word-embedding method,\u201d arXiv preprint arXiv:1402.3722, 2014."},{"key":"ref35","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.neucom.2021.03.091","article-title":"A review on the attention mechanism of deep learning","volume":"452","author":"Niu","year":"2021","journal-title":"Neurocomputing"}],"container-title":["Computers, Materials & Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.techscience.com\/files\/cmc\/2024\/TSP_CMC-80-2\/TSP_CMC_41949\/TSP_CMC_41949.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T12:11:19Z","timestamp":1741263079000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v80n2\/57581"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":35,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2024]]},"published-print":{"date-parts":[[2024]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2024.041949","relation":{},"ISSN":["1546-2226"],"issn-type":[{"value":"1546-2226","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}