{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T07:03:48Z","timestamp":1751267028072,"version":"3.40.3"},"publisher-location":"Cham","reference-count":37,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030630850"},{"type":"electronic","value":"9783030630867"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-63086-7_20","type":"book-chapter","created":{"date-parts":[[2020,12,11]],"date-time":"2020-12-11T08:07:25Z","timestamp":1607674045000},"page":"360-380","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Integrity: Finding Integer Errors by Targeted Fuzzing"],"prefix":"10.1007","author":[{"given":"Yuyang","family":"Rong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,12,12]]},"reference":[{"key":"20_CR1","unstructured":"American fuzzy lop. http:\/\/lcamtuf.coredump.cx\/afl\/"},{"key":"20_CR2","unstructured":"Batchoverflow exploit creates trillions of ethereum tokens, major exchanges halt erc20 deposits|cryptoslate. https:\/\/cryptoslate.com\/batchoverflow-exploit-creates-trillions-of-ethereum-tokens\/"},{"key":"20_CR3","unstructured":"Beautychain (bec) withdrawal and trading suspended. https:\/\/support.okex.com\/hc\/en-us\/articles\/360002944212-BeautyChain-BEC-Withdrawal-and-Trading-Suspended-Update-"},{"key":"20_CR4","unstructured":"Cwe - common weakness enumeration. https:\/\/cwe.mitre.org\/"},{"key":"20_CR5","unstructured":"libfuzzer \u2013 a library for coverage-guided fuzz testing, https:\/\/llvm.org\/docs\/LibFuzzer.html"},{"key":"20_CR6","unstructured":"LLVM dataflowsanitizer https:\/\/clang.llvm.org\/docs\/DataFlowSanitizer.html"},{"key":"20_CR7","unstructured":"LLVM threadsanitizer. https:\/\/clang.llvm.org\/docs\/ThreadSanitizer.html"},{"key":"20_CR8","unstructured":"LLVM undefinedbehaviorsanitizer. https:\/\/clang.llvm.org\/docs\/UndefinedBehaviorSanitizer.html"},{"key":"20_CR9","unstructured":"Software assurance reference dataset. https:\/\/samate.nist.gov\/SARD\/testsuite.php"},{"key":"20_CR10","doi-asserted-by":"crossref","unstructured":"Aschermann, C., Schumilo, S., Blazytko, T., Gawlik, R., Holz, T.: Redqueen: fuzzing with input-to-state correspondence (2019)","DOI":"10.14722\/ndss.2019.23371"},{"key":"20_CR11","doi-asserted-by":"crossref","unstructured":"B\u00f6hme, M., Pham, V.T., Nguyen, M.D., Roychoudhury, A.: Directed greybox fuzzing. In: Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, pp. 2329\u20132344. ACM (2017)","DOI":"10.1145\/3133956.3134020"},{"key":"20_CR12","doi-asserted-by":"crossref","unstructured":"Chen, H., et al.: Hawkeye: towards a desired directed grey-box fuzzer. In: Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, pp. 2095\u20132108. ACM (2018)","DOI":"10.1145\/3243734.3243849"},{"key":"20_CR13","doi-asserted-by":"crossref","unstructured":"Chen, P., Chen, H.: Angora: Efficient fuzzing by principled search. In: 2018 IEEE Symposium on Security and Privacy (SP), pp. 711\u2013725. IEEE (2018)","DOI":"10.1109\/SP.2018.00046"},{"key":"20_CR14","unstructured":"Chen, P., Liu, J., Chen, H.: Matryoshka: fuzzing deeply nested branches. In: ACM Conference on Computer and Communications Security (CCS), London, UK"},{"key":"20_CR15","unstructured":"Dietz, W., Li, P., Regehr, J., Adve, V.: Understanding integer overflow in C\/C++. In: 34th International Conference on Software Engineering, ICSE 2012 (2012)"},{"issue":"1","key":"20_CR16","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1145\/2743019","volume":"25","author":"W Dietz","year":"2015","unstructured":"Dietz, W., Li, P., Regehr, J., Adve, V.: Understanding integer overflow in C\/C++. ACM Trans. Softw. Eng. Methodol. (TOSEM) 25(1), 2 (2015)","journal-title":"ACM Trans. Softw. Eng. Methodol. (TOSEM)"},{"key":"20_CR17","unstructured":"Haller, I., Slowinska, A., Neugschwandtner, M., Bos, H.: Dowsing for overflows: a guided fuzzer to find buffer boundary violations. In: USENIX Security, pp. 49\u201364 (2013)"},{"key":"20_CR18","doi-asserted-by":"crossref","unstructured":"Han, W., Joe, B., Lee, B., Song, C., Shin, I.: Enhancing memory error detection for large-scale applications and fuzz testing. In: Symposium on Network and Distributed Systems Security (NDSS), p. 148 (2018)","DOI":"10.14722\/ndss.2018.23312"},{"key":"20_CR19","doi-asserted-by":"crossref","unstructured":"Jain, V., Rawat, S., Giuffrida, C., Bos, H.: Tiff: Using input type inference to improve fuzzing. In: Proceedings of the 34th Annual Computer Security Applications Conference, pp. 505\u2013517. ACM (2018)","DOI":"10.1145\/3274694.3274746"},{"key":"20_CR20","doi-asserted-by":"crossref","unstructured":"Jeong, D.R., Kim, K., Shivakumar, B., Lee, B., Shin, I.: Razzer: finding kernel race bugs through fuzzing. In: Razzer: Finding Kernel Race Bugs through Fuzzing. IEEE (2018)","DOI":"10.1109\/SP.2019.00017"},{"key":"20_CR21","unstructured":"Martin, B., Brown, M., Paller, A., Kirby, D., Christey, S.: 2011 CWE\/SANS top 25 most dangerous software errors. Common Weakness Enumer 7515 (2011)"},{"key":"20_CR22","unstructured":"Moy, Y., Bj\u00f8rner, N., Sielaff, D.: Modular bug-finding for integer overflows in the large: Sound, efficient, bit-precise static analysis. Microsoft Res. 11, 57 (2009)"},{"key":"20_CR23","unstructured":"Odena, A., Goodfellow, I.: Tensorfuzz: debugging neural networks with coverage-guided fuzzing. arXiv preprint arXiv:1807.10875 (2018)"},{"key":"20_CR24","doi-asserted-by":"crossref","unstructured":"Peng, H., Shoshitaishvili, Y., Payer, M.: T-fuzz: fuzzing by program transformation. In: 2018 IEEE Symposium on Security and Privacy (SP), pp. 697\u2013710. IEEE (2018)","DOI":"10.1109\/SP.2018.00056"},{"key":"20_CR25","doi-asserted-by":"crossref","unstructured":"Petsios, T., Tang, A., Stolfo, S., Keromytis, A.D., Jana, S.: Nezha: efficient domain-independent differential testing. In: 2017 IEEE Symposium on Security and Privacy (SP), pp. 615\u2013632. IEEE (2017)","DOI":"10.1109\/SP.2017.27"},{"key":"20_CR26","doi-asserted-by":"crossref","unstructured":"Petsios, T., Zhao, J., Keromytis, A.D., Jana, S.: Slowfuzz: automated domain-independent detection of algorithmic complexity vulnerabilities. In: Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, pp. 2155\u20132168. ACM (2017)","DOI":"10.1145\/3133956.3134073"},{"key":"20_CR27","doi-asserted-by":"crossref","unstructured":"Pomonis, M., Petsios, T., Jee, K., Polychronakis, M., Keromytis, A.D.: Intflow: improving the accuracy of arithmetic error detection using information flow tracking. In: Proceedings of the 30th Annual Computer Security Applications Conference, pp. 416\u2013425. ACM (2014)","DOI":"10.1145\/2664243.2664282"},{"key":"20_CR28","doi-asserted-by":"crossref","unstructured":"Rawat, S., Jain, V., Kumar, A., Cojocar, L., Giuffrida, C., Bos, H.: VUzzer: application-aware evolutionary fuzzing. In: NDSS, February 2017","DOI":"10.14722\/ndss.2017.23404"},{"key":"20_CR29","unstructured":"Serebryany, K., Bruening, D., Potapenko, A., Vyukov, D.: Addresssanitizer: a fast address sanity checker. In: USENIX ATC 2012 (2012)"},{"key":"20_CR30","doi-asserted-by":"crossref","unstructured":"She, D., Pei, K., Epstein, D., Yang, J., Ray, B., Jana, S.: Neuzz: efficient fuzzing with neural program learning (2019)","DOI":"10.1109\/SP.2019.00052"},{"key":"20_CR31","doi-asserted-by":"crossref","unstructured":"Song, D., et al.: SoK: sanitizing for security (2019)","DOI":"10.1109\/SP.2019.00010"},{"key":"20_CR32","doi-asserted-by":"crossref","unstructured":"Stepanov, E., Serebryany, K.: Memorysanitizer: fast detector of uninitialized memory use in C++. In: Proceedings of the 13th Annual IEEE\/ACM International Symposium on Code Generation and Optimization, pp. 46\u201355. IEEE Computer Society (2015)","DOI":"10.1109\/CGO.2015.7054186"},{"key":"20_CR33","doi-asserted-by":"crossref","unstructured":"Stephens, N., et al.: Driller: augmenting fuzzing through selective symbolic execution. In: Proceedings of the Network and Distributed System Security Symposium (2016)","DOI":"10.14722\/ndss.2016.23368"},{"key":"20_CR34","doi-asserted-by":"crossref","unstructured":"Sun, H., Zhang, X., Zheng, Y., Zeng, Q.: Inteq: recognizing benign integer overflows via equivalence checking across multiple precisions. In: Proceedings of the 38th International Conference on Software Engineering, pp. 1051\u20131062. ACM (2016)","DOI":"10.1145\/2884781.2884820"},{"key":"20_CR35","doi-asserted-by":"crossref","unstructured":"Wang, T., Wei, T., Gu, G., Zou, W.: Taintscope: a checksum-aware directed fuzzing tool for automatic software vulnerability detection. In: 2010 IEEE symposium on Security and privacy (SP), pp. 497\u2013512 (2010)","DOI":"10.1109\/SP.2010.37"},{"key":"20_CR36","unstructured":"Wang, T., Wei, T., Lin, Z., Zou, W.: Intscope: automatically detecting integer overflow vulnerability in x86 binary using symbolic execution. In: NDSS. Citeseer (2009)"},{"key":"20_CR37","unstructured":"Yun, I., Lee, S., Xu, M., Jang, Y., Kim, T.: QSYM : a practical concolic execution engine tailored for hybrid fuzzing. In: 27th USENIX Security Symposium (USENIX Security 18), pp. 745\u2013761. USENIX Association, Baltimore, MD (2018)"}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","Security and Privacy in Communication Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-63086-7_20","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,24]],"date-time":"2021-04-24T12:10:50Z","timestamp":1619266250000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-63086-7_20"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030630850","9783030630867"],"references-count":37,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-63086-7_20","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"type":"print","value":"1867-8211"},{"type":"electronic","value":"1867-822X"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"12 December 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SecureComm","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Security and Privacy in Communication Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Washington, WA","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 October 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 October 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"securecomm2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/securecomm.eai-conferences.org\/2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Confy","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"120","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"50","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"42% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2,86","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The conference was held virtually due to COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}