{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T18:04:32Z","timestamp":1783965872959,"version":"3.55.0"},"reference-count":58,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers &amp; Security"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.cose.2026.105025","type":"journal-article","created":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T06:48:59Z","timestamp":1782542939000},"page":"105025","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["CFuzz: Lightweight fuzzing optimization method based on dynamic clustering"],"prefix":"10.1016","volume":"170","author":[{"given":"Guangkuan","family":"Yang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gang","family":"Hou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiqiang","family":"Kong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiming","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjie","family":"Jin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.cose.2026.105025_b1","first-page":"337","article-title":"NAUTILUS: Fishing for deep bugs with grammars","volume":"vol. 19","author":"Aschermann","year":"2019"},{"key":"10.1016\/j.cose.2026.105025_b2","doi-asserted-by":"crossref","unstructured":"B\u00f6hme, M., Pham, V.-T., Roychoudhury, A., 2016. Coverage-based greybox fuzzing as markov chain. In: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. pp. 1032\u20131043.","DOI":"10.1145\/2976749.2978428"},{"key":"10.1016\/j.cose.2026.105025_b3","series-title":"2018 IEEE Security and Privacy Workshops","first-page":"116","article-title":"Deep reinforcement fuzzing","author":"B\u00f6ttinger","year":"2018"},{"key":"10.1016\/j.cose.2026.105025_b4","series-title":"2018 IEEE Symposium on Security and Privacy","first-page":"711","article-title":"Angora: Efficient fuzzing by principled search","author":"Chen","year":"2018"},{"key":"10.1016\/j.cose.2026.105025_b5","doi-asserted-by":"crossref","DOI":"10.23919\/cje.2024.00.174","article-title":"FMutator: A probabilistic mutation-based model for enhanced industrial control fuzz testing","author":"Chen","year":"2025","journal-title":"Chin. J. Electron."},{"key":"10.1016\/j.cose.2026.105025_b6","doi-asserted-by":"crossref","unstructured":"Chen, P., Liu, J., Chen, H., 2019. Matryoshka: fuzzing deeply nested branches. In: Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security. pp. 499\u2013513.","DOI":"10.1145\/3319535.3363225"},{"key":"10.1016\/j.cose.2026.105025_b7","series-title":"2019 IEEE\/ACM 41st International Conference on Software Engineering","first-page":"736","article-title":"Grey-box concolic testing on binary code","author":"Choi","year":"2019"},{"key":"10.1016\/j.cose.2026.105025_b8","series-title":"2025 10th International Conference on Computer and Communication System","first-page":"998","article-title":"OptionFuzz: The fuzzer with coverage-guided dynamic configuration scheduling","author":"Chu","year":"2025"},{"issue":"7","key":"10.1016\/j.cose.2026.105025_b9","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1145\/359636.359712","article-title":"Certification of programs for secure information flow","volume":"20","author":"Denning","year":"1977","journal-title":"Commun. ACM"},{"key":"10.1016\/j.cose.2026.105025_b10","series-title":"Fuzzergym: A competitive framework for fuzzing and learning","author":"Drozd","year":"2018"},{"key":"10.1016\/j.cose.2026.105025_b11","first-page":"226","article-title":"A density-based algorithm for discovering clusters in large spatial databases with noise","volume":"vol. 96, no. 34","author":"Ester","year":"1996"},{"key":"10.1016\/j.cose.2026.105025_b12","unstructured":"Fioraldi, A., Maier, D., Ei\u00dffeldt, H., Heuse, M., 2020. AFL++: Combining incremental steps of fuzzing research. In: 14th USENIX Workshop on Offensive Technologies. WOOT 20."},{"key":"10.1016\/j.cose.2026.105025_b13","unstructured":"Gan, S., Zhang, C., Chen, P., Zhao, B., Qin, X., Wu, D., Chen, Z., 2020. {GREYONE}: Data flow sensitive fuzzing. In: 29th USENIX Security Symposium. USENIX Security 20, pp. 2577\u20132594."},{"key":"10.1016\/j.cose.2026.105025_b14","series-title":"2018 IEEE Symposium on Security and Privacy","first-page":"679","article-title":"Collafl: Path sensitive fuzzing","author":"Gan","year":"2018"},{"issue":"1","key":"10.1016\/j.cose.2026.105025_b15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TSE.2023.3326144","article-title":"Fa-fuzz: A novel scheduling scheme using firefly algorithm for mutation-based fuzzing","volume":"50","author":"Gao","year":"2023","journal-title":"IEEE Trans. Softw. Eng."},{"key":"10.1016\/j.cose.2026.105025_b16","series-title":"2023 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking","first-page":"508","article-title":"Efficient hybrid fuzzing with syntax-aware input trim based on lightweight taint analysis","author":"Gao","year":"2023"},{"key":"10.1016\/j.cose.2026.105025_b17","series-title":"2020 IEEE Symposium on Security and Privacy","first-page":"1613","article-title":"Pangolin: Incremental hybrid fuzzing with polyhedral path abstraction","author":"Huang","year":"2020"},{"key":"10.1016\/j.cose.2026.105025_b18","doi-asserted-by":"crossref","unstructured":"Jain, V., Rawat, S., Giuffrida, C., Bos, H., 2018. TIFF: Using input type inference to improve fuzzing. In: Proceedings of the 34th Annual Computer Security Applications Conference. pp. 505\u2013517.","DOI":"10.1145\/3274694.3274746"},{"key":"10.1016\/j.cose.2026.105025_b19","series-title":"Network and Distributed System Security Symposium, NDSS","article-title":"DARWIN: Survival of the fittest fuzzing mutators","author":"Jauernig","year":"2023"},{"issue":"5s","key":"10.1016\/j.cose.2026.105025_b20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3760529","article-title":"Fuss: Coverage-directed hardware fuzzing with selective symbolic execution","volume":"24","author":"Jayasena","year":"2025","journal-title":"ACM Trans. Embed. Comput. Syst."},{"key":"10.1016\/j.cose.2026.105025_b21","article-title":"AFLPro: Direction sensitive fuzzing","volume":"54","author":"Ji","year":"2020","journal-title":"J. Inf. Secur. Appl."},{"key":"10.1016\/j.cose.2026.105025_b22","series-title":"29th USENIX Security Symposium","first-page":"2595","article-title":"Fuzzing error handling code using {Context\u2212Sensitive} software fault injection","author":"Jiang","year":"2020"},{"issue":"7","key":"10.1016\/j.cose.2026.105025_b23","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1145\/360248.360252","article-title":"Symbolic execution and program testing","volume":"19","author":"King","year":"1976","journal-title":"Commun. ACM"},{"key":"10.1016\/j.cose.2026.105025_b24","doi-asserted-by":"crossref","unstructured":"Klees, G., Ruef, A., Cooper, B., Wei, S., Hicks, M., 2018. Evaluating fuzz testing. In: Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. pp. 2123\u20132138.","DOI":"10.1145\/3243734.3243804"},{"key":"10.1016\/j.cose.2026.105025_b25","doi-asserted-by":"crossref","DOI":"10.1016\/j.jss.2025.112340","article-title":"BaSFuzz: Fuzz testing based on difference analysis for seed bytes","volume":"222","author":"Lan","year":"2025","journal-title":"J. Syst. Softw."},{"key":"10.1016\/j.cose.2026.105025_b26","doi-asserted-by":"crossref","unstructured":"Lemieux, C., Sen, K., 2018. Fairfuzz: A targeted mutation strategy for increasing greybox fuzz testing coverage. In: Proceedings of the 33rd ACM\/IEEE International Conference on Automated Software Engineering. pp. 475\u2013485.","DOI":"10.1145\/3238147.3238176"},{"key":"10.1016\/j.cose.2026.105025_b27","series-title":"30th USENIX Security Symposium","first-page":"2777","article-title":"{UNIFUZZ}: A holistic and pragmatic {Metrics\u2212Driven} platform for evaluating fuzzers","author":"Li","year":"2021"},{"key":"10.1016\/j.cose.2026.105025_b28","doi-asserted-by":"crossref","unstructured":"Li, Y., Xue, Y., Chen, H., Wu, X., Zhang, C., Xie, X., Wang, H., Liu, Y., 2019. Cerebro: context-aware adaptive fuzzing for effective vulnerability detection. In: Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering. pp. 533\u2013544.","DOI":"10.1145\/3338906.3338975"},{"issue":"6","key":"10.1016\/j.cose.2026.105025_b29","first-page":"2675","article-title":"Deepfuzzer: Accelerated deep greybox fuzzing","volume":"18","author":"Liang","year":"2019","journal-title":"IEEE Trans. Dependable Secur. Comput."},{"key":"10.1016\/j.cose.2026.105025_b30","series-title":"2022 IEEE Symposium on Security and Privacy","first-page":"1","article-title":"Pata: Fuzzing with path aware taint analysis","author":"Liang","year":"2022"},{"key":"10.1016\/j.cose.2026.105025_b31","doi-asserted-by":"crossref","unstructured":"Liang, J., Wang, M., Zhou, C., Wu, Z., Liu, J., Jiang, Y., 2024. Dodrio: Parallelizing Taint Analysis Based Fuzzing via Redundancy-Free Scheduling. In: Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering. pp. 244\u2013254.","DOI":"10.1145\/3663529.3663844"},{"issue":"1","key":"10.1016\/j.cose.2026.105025_b32","article-title":"GSA-fuzz: Optimize seed mutation with gravitational search algorithm","volume":"2022","author":"Lin","year":"2022","journal-title":"Secur. Commun. Netw."},{"key":"10.1016\/j.cose.2026.105025_b33","unstructured":"Lyu, C., Ji, S., Zhang, C., Li, Y., Lee, W.-H., Song, Y., Beyah, R., 2019. {MOPT}: Optimized mutation scheduling for fuzzers. In: 28th USENIX Security Symposium. USENIX Security 19, pp. 1949\u20131966."},{"issue":"11","key":"10.1016\/j.cose.2026.105025_b34","doi-asserted-by":"crossref","first-page":"2312","DOI":"10.1109\/TSE.2019.2946563","article-title":"The art, science, and engineering of fuzzing: A survey","volume":"47","author":"Man\u00e8s","year":"2019","journal-title":"IEEE Trans. Softw. Eng."},{"key":"10.1016\/j.cose.2026.105025_b35","doi-asserted-by":"crossref","unstructured":"Ognawala, S., Hutzelmann, T., Psallida, E., Pretschner, A., 2018. Improving function coverage with munch: a hybrid fuzzing and directed symbolic execution approach. In: Proceedings of the 33rd Annual ACM Symposium on Applied Computing. pp. 1475\u20131482.","DOI":"10.1145\/3167132.3167289"},{"key":"10.1016\/j.cose.2026.105025_b36","series-title":"2018 IEEE Symposium on Security and Privacy","first-page":"697","article-title":"T-fuzz: fuzzing by program transformation","author":"Peng","year":"2018"},{"key":"10.1016\/j.cose.2026.105025_b37","doi-asserted-by":"crossref","DOI":"10.1109\/ACCESS.2024.3421989","article-title":"A coverage-guided fuzzing method for automatic software vulnerability detection using reinforcement learning-enabled multi-level input mutation","author":"Pham","year":"2024","journal-title":"IEEE Access"},{"key":"10.1016\/j.cose.2026.105025_b38","series-title":"2017 Network and Distributed System Security (NDSS) Symposium:[Proceedings]","first-page":"1","article-title":"Vuzzer: Application-aware evolutionary fuzzing","author":"Rawat","year":"2017"},{"key":"10.1016\/j.cose.2026.105025_b39","series-title":"23rd USENIX Security Symposium","first-page":"861","article-title":"Optimizing seed selection for fuzzing","author":"Rebert","year":"2014"},{"key":"10.1016\/j.cose.2026.105025_b40","unstructured":"Serebryany, K., Bruening, D., Potapenko, A., Vyukov, D., 2012. {AddressSanitizer}: A fast address sanity checker. In: 2012 USENIX Annual Technical Conference. USENIX ATC 12, pp. 309\u2013318."},{"key":"10.1016\/j.cose.2026.105025_b41","doi-asserted-by":"crossref","unstructured":"She, D., Krishna, R., Yan, L., Jana, S., Ray, B., 2020. MTFuzz: fuzzing with a multi-task neural network. In: Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering. pp. 737\u2013749.","DOI":"10.1145\/3368089.3409723"},{"key":"10.1016\/j.cose.2026.105025_b42","series-title":"2019 IEEE Symposium on Security and Privacy","first-page":"803","article-title":"Neuzz: Efficient fuzzing with neural program smoothing","author":"She","year":"2019"},{"key":"10.1016\/j.cose.2026.105025_b43","first-page":"1","article-title":"Driller: Augmenting fuzzing through selective symbolic execution","volume":"vol. 16, no. 2016","author":"Stephens","year":"2016"},{"issue":"2","key":"10.1016\/j.cose.2026.105025_b44","first-page":"101","article-title":"A critique and improvement of the CL common language effect size statistics of McGraw and Wong","volume":"25","author":"Vargha","year":"2000","journal-title":"J. Educ. Behav. Stat."},{"key":"10.1016\/j.cose.2026.105025_b45","series-title":"2017 IEEE Symposium on Security and Privacy","first-page":"579","article-title":"Skyfire: Data-driven seed generation for fuzzing","author":"Wang","year":"2017"},{"key":"10.1016\/j.cose.2026.105025_b46","doi-asserted-by":"crossref","unstructured":"Wang, M., Liang, J., Chen, Y., Jiang, Y., Jiao, X., Liu, H., Zhao, X., Sun, J., 2018. SAFL: increasing and accelerating testing coverage with symbolic execution and guided fuzzing. In: Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings. pp. 61\u201364.","DOI":"10.1145\/3183440.3183494"},{"key":"10.1016\/j.cose.2026.105025_b47","series-title":"2025 IEEE 49th Annual Computers, Software, and Applications Conference","first-page":"1370","article-title":"LSFuzz: Learning adaptive seed selection strategies for fuzzing","author":"Xiao","year":"2025"},{"issue":"1","key":"10.1016\/j.cose.2026.105025_b48","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1109\/TDSC.2024.3391795","article-title":"BazzAFL: Moving fuzzing campaigns towards bugs via grouping bug-oriented seeds","volume":"22","author":"Ye","year":"2024","journal-title":"IEEE Trans. Dependable Secur. Comput."},{"key":"10.1016\/j.cose.2026.105025_b49","series-title":"29th USENIX Security Symposium","first-page":"2307","article-title":"{EcoFuzz}: Adaptive {Energy\u2212Saving} greybox fuzzing as a variant of the adversarial {Multi\u2212Armed} bandit","author":"Yue","year":"2020"},{"key":"10.1016\/j.cose.2026.105025_b50","unstructured":"Yun, I., Lee, S., Xu, M., Jang, Y., Kim, T., 2018. {QSYM}: A practical concolic execution engine tailored for hybrid fuzzing. In: 27th USENIX Security Symposium. USENIX Security 18, pp. 745\u2013761."},{"key":"10.1016\/j.cose.2026.105025_b51","series-title":"American fuzzy lop, 2017","author":"Zalewski","year":"2017"},{"issue":"3","key":"10.1016\/j.cose.2026.105025_b52","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1049\/sfw2.12125","article-title":"CIDFuzz: Fuzz testing for continuous integration","volume":"17","author":"Zhang","year":"2023","journal-title":"IET Softw."},{"key":"10.1016\/j.cose.2026.105025_b53","series-title":"TENCON 2017-2017 IEEE Region 10 Conference","first-page":"822","article-title":"A hybrid symbolic execution assisted fuzzing method","author":"Zhang","year":"2017"},{"key":"10.1016\/j.cose.2026.105025_b54","series-title":"31st Annual Network and Distributed System Security Symposium, NDSS","article-title":"SHAPFUZZ: Efficient fuzzing via Shapley-guided byte selection","author":"Zhang","year":"2024"},{"key":"10.1016\/j.cose.2026.105025_b55","series-title":"Network and Distributed System Security Symposium","article-title":"Send hardest problems my way: probabilistic path prioritization for hybrid fuzzing","author":"Zhao","year":"2019"},{"issue":"11s","key":"10.1016\/j.cose.2026.105025_b56","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3512345","article-title":"Fuzzing: a survey for roadmap","volume":"54","author":"Zhu","year":"2022","journal-title":"ACM Comput. Surv."},{"key":"10.1016\/j.cose.2026.105025_b57","series-title":"29th USENIX Security Symposium","first-page":"2255","article-title":"{FuzzGuard}: Filtering out unreachable inputs in directed grey-box fuzzing through deep learning","author":"Zong","year":"2020"},{"issue":"1","key":"10.1016\/j.cose.2026.105025_b58","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1186\/s42400-023-00143-2","article-title":"PosFuzz: augmenting greybox fuzzing with effective position distribution","volume":"6","author":"Zou","year":"2023","journal-title":"Cybersecurity"}],"container-title":["Computers &amp; Security"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0167404826002014?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0167404826002014?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T17:15:44Z","timestamp":1783962944000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0167404826002014"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":58,"alternative-id":["S0167404826002014"],"URL":"https:\/\/doi.org\/10.1016\/j.cose.2026.105025","relation":{},"ISSN":["0167-4048"],"issn-type":[{"value":"0167-4048","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"CFuzz: Lightweight fuzzing optimization method based on dynamic clustering","name":"articletitle","label":"Article Title"},{"value":"Computers & Security","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cose.2026.105025","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"105025"}}