{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T23:15:33Z","timestamp":1771024533539,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":24,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819980239","type":"print"},{"value":"9789819980246","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-99-8024-6_17","type":"book-chapter","created":{"date-parts":[[2024,1,10]],"date-time":"2024-01-10T05:02:11Z","timestamp":1704862931000},"page":"213-227","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Enriching Vulnerability Reports Through Automated and\u00a0Augmented Description Summarization"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1834-025X","authenticated-orcid":false,"given":"Hattan","family":"Althebeiti","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3227-2505","authenticated-orcid":false,"given":"David","family":"Mohaisen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,1,11]]},"reference":[{"key":"17_CR1","doi-asserted-by":"crossref","unstructured":"Alabduljabbar, A., Abusnaina, A., Meteriz-Yildiran, \u00dc., Mohaisen, D.: Automated privacy policy annotation with information highlighting made practical using deep representations. In: Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security, pp. 2378\u20132380 (2021)","DOI":"10.1145\/3460120.3485335"},{"key":"17_CR2","doi-asserted-by":"crossref","unstructured":"Alabduljabbar, A., Mohaisen, D.: Measuring the privacy dimension of free content websites through automated privacy policy analysis and annotation. In: Companion Proceedings of the Web Conference (2022)","DOI":"10.1145\/3487553.3524663"},{"key":"17_CR3","unstructured":"Anwar, A., Abusnaina, A., Chen, S., Li, F., Mohaisen, D.: Cleaning the NVD: comprehensive quality assessment, improvements, and analyses. CoRR abs\/2006.15074 (2020). https:\/\/arxiv.org\/abs\/2006.15074"},{"issue":"23","key":"17_CR4","first-page":"e1","volume":"7","author":"A Anwar","year":"2020","unstructured":"Anwar, A., et al.: Measuring the cost of software vulnerabilities. EAI Endorsed Trans. Secur. Saf. 7(23), e1\u2013e1 (2020)","journal-title":"EAI Endorsed Trans. Secur. Saf."},{"key":"17_CR5","series-title":"Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1007\/978-3-030-01701-9_21","volume-title":"Security and Privacy in Communication Networks","author":"A Anwar","year":"2018","unstructured":"Anwar, A., Khormali, A., Nyang, D.H., Mohaisen, A.: Understanding the hidden cost of software vulnerabilities: measurements and predictions. In: Beyah, R., Chang, B., Li, Y., Zhu, S. (eds.) SecureComm 2018. LNICST, vol. 254, pp. 377\u2013395. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01701-9_21"},{"key":"17_CR6","unstructured":"Cer, D., et al.: Universal sentence encoder. arXiv preprint arXiv:1803.11175 (2018)"},{"key":"17_CR7","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: 2019 Conference of the North American Chapter of the Association for Computational Linguistics (2018)"},{"key":"17_CR8","unstructured":"Dong, Y., Guo, W., Chen, Y., Xing, X., Zhang, Y., Wang, G.: Towards the detection of inconsistencies in public security vulnerability reports. In: 28th USENIX Security Symposium, pp. 869\u2013885 (2019)"},{"key":"17_CR9","unstructured":"Help Net Security: Still relying solely on CVE and NVD for vulnerability tracking? Bad idea (2018). https:\/\/www.helpnetsecurity.com\/2018\/02\/16\/cve-nvd-vulnerability-tracking\/"},{"key":"17_CR10","unstructured":"Information Security Buzz: Why critical vulnerabilities do not get reported in the CVE\/NVD databases and how organisations can mitigate the risks (2018). https:\/\/informationsecuritybuzz.com\/articles\/why-critical-vulnerabilities\/"},{"key":"17_CR11","doi-asserted-by":"crossref","unstructured":"Kanakogi, K., et al.: Tracing CAPEC attack patterns from CVE vulnerability information using natural language processing technique. In: 54th Hawaii International Conference on System Sciences (2021)","DOI":"10.24251\/HICSS.2021.841"},{"issue":"8","key":"17_CR12","doi-asserted-by":"publisher","first-page":"298","DOI":"10.3390\/info12080298","volume":"12","author":"K Kanakogi","year":"2021","unstructured":"Kanakogi, K., et al.: Tracing CVE vulnerability information to CAPEC attack patterns using natural language processing techniques. Information 12(8), 298 (2021)","journal-title":"Information"},{"key":"17_CR13","doi-asserted-by":"crossref","unstructured":"Kudo, T.: Subword regularization: improving neural network translation models with multiple subword candidates. arXiv preprint arXiv:1804.10959 (2018)","DOI":"10.18653\/v1\/P18-1007"},{"key":"17_CR14","doi-asserted-by":"crossref","unstructured":"Kudo, T., Richardson, J.: Sentencepiece: a simple and language independent subword tokenizer and detokenizer for neural text processing. arXiv preprint arXiv:1808.06226 (2018)","DOI":"10.18653\/v1\/D18-2012"},{"key":"17_CR15","doi-asserted-by":"crossref","unstructured":"Lewis, M., et al.: BART: denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension. arXiv preprint arXiv:1910.13461 (2019)","DOI":"10.18653\/v1\/2020.acl-main.703"},{"key":"17_CR16","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1016\/j.cose.2015.04.001","volume":"52","author":"A Mohaisen","year":"2015","unstructured":"Mohaisen, A., Alrawi, O., Mohaisen, M.: AMAL: high-fidelity, behavior-based automated malware analysis and classification. Comput. Secur. 52, 251\u2013266 (2015)","journal-title":"Comput. Secur."},{"key":"17_CR17","unstructured":"Radford, A., Narasimhan, K., Salimans, T., Sutskever, I.: Improving language understanding by generative pre-training. OpenAI (2018)"},{"key":"17_CR18","unstructured":"Raffel, C., et al.: Exploring the limits of transfer learning with a unified text-to-text transformer. arXiv preprint arXiv:1910.10683 (2019)"},{"key":"17_CR19","doi-asserted-by":"crossref","unstructured":"Sennrich, R., Haddow, B., Birch, A.: Neural machine translation of rare words with subword units. In: 54th Annual Meeting of the Association for Computational Linguistics (2015)","DOI":"10.18653\/v1\/P16-1162"},{"key":"17_CR20","unstructured":"Song, K., Tan, X., Qin, T., Lu, J., Liu, T.Y.: MPNet: masked and permuted pre-training for language understanding. In: Advances in Neural Information Processing Systems, vol. 33, pp. 16857\u201316867 (2020)"},{"key":"17_CR21","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"17_CR22","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-030-52683-2_1","volume-title":"Detection of Intrusions and Malware, and Vulnerability Assessment","author":"E W\u00e5reus","year":"2020","unstructured":"W\u00e5reus, E., Hell, M.: Automated CPE labeling of CVE summaries with machine learning. In: Maurice, C., Bilge, L., Stringhini, G., Neves, N. (eds.) DIMVA 2020. LNCS, vol. 12223, pp. 3\u201322. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-52683-2_1"},{"key":"17_CR23","unstructured":"Yang, Z., Dai, Z., Yang, Y., Carbonell, J., Salakhutdinov, R., Le, Q.V.: XLNet generalized autoregressive pretraining for language understanding (2019). https:\/\/arxiv.org\/abs\/1906.08237. Accessed June 21"},{"key":"17_CR24","unstructured":"Zhang, J., Zhao, Y., Saleh, M., Liu, P.: Pegasus: pre-training with extracted gap-sentences for abstractive summarization. In: International Conference on Machine Learning, pp. 11328\u201311339. PMLR (2020)"}],"container-title":["Lecture Notes in Computer Science","Information Security Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-8024-6_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,10]],"date-time":"2024-01-10T05:03:24Z","timestamp":1704863004000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-8024-6_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819980239","9789819980246"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-8024-6_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"11 January 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"WISA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Information Security Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Jeju Island","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Korea (Republic of)","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 August 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 August 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"wisa2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/wisa.or.kr\/","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":"Easy Chair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"52","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":"26","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":"50% - 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":"3.3","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":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","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)"}}]}}