{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T05:10:49Z","timestamp":1778130649704,"version":"3.51.4"},"reference-count":36,"publisher":"IEEE","license":[{"start":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T00:00:00Z","timestamp":1773705600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T00:00:00Z","timestamp":1773705600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,3,17]]},"DOI":"10.1109\/saner-c67878.2026.00048","type":"proceedings-article","created":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T19:39:18Z","timestamp":1778096358000},"page":"309-316","source":"Crossref","is-referenced-by-count":0,"title":["From Threat Reports to Security Knowledge: Building an LLM-Based Pipeline for AI Systems"],"prefix":"10.1109","author":[{"given":"Takuma","family":"Tsuchida","sequence":"first","affiliation":[{"name":"Waseda University,Tokyo,Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuya","family":"Fujiwara","sequence":"additional","affiliation":[{"name":"Waseda University,Tokyo,Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hironori","family":"Washizaki","sequence":"additional","affiliation":[{"name":"Waseda University,Tokyo,Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Naoyasu","family":"Ubayashi","sequence":"additional","affiliation":[{"name":"Waseda University,Tokyo,Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","volume-title":"Adversarial threat landscape for artificialintelligence system"},{"key":"ref2","volume-title":"Contribute to atlas","year":"2025"},{"key":"ref3","volume-title":"Threat assessment in machine learning based systems","author":"Tidjon","year":"2022"},{"key":"ref4","volume-title":"Ai incident database","year":"2025"},{"issue":"17","key":"ref5","first-page":"15458","article-title":"Preventing repeated real world ai failures by cataloging incidents: The AI incident database","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"35","author":"McGregor"},{"key":"ref6","volume-title":"Systems and software engineering - Requirements engineering, International Organization for Standardization","year":"2018"},{"key":"ref7","volume-title":"Adversarial tactics, techniques, and common knowledge"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/SaTML54575.2023.00031"},{"key":"ref9","volume-title":"AML.CS0031: Malicious models on hugging face","year":"2024"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3134600.3134646"},{"key":"ref11","volume-title":"Automated retrieval of att&ck tactics and techniques for cyber threat reports","author":"Legoy","year":"2020"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/5586335"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.18653\/vl\/N19-142"},{"key":"ref14","volume-title":"Roberta: A robustly optimized bert pretraining approach","author":"Liu","year":"2019"},{"key":"ref15","volume-title":"Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter","author":"Sanh","year":"2020"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/WCNPS56355.2022.9969697"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3579375.3579391"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3696427"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-17140-6_29"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3607199.3607208"},{"key":"ref21","article-title":"Prediction of vulnerability characteristics based on vulnerability description and prompt learning","volume-title":"Proceedings of the 30th IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2023)","author":"Zhang","year":"2023"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/SANER56733.2023.00057"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/SANER60148.2024.00102"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/SANER64311.2025.00072"},{"issue":"9","key":"ref25","first-page":"1286","volume-title":"VTT-LLM: Advancing vulnerability-to-tactic-and-technique mapping through fine-tuning of large language model","volume":"12","author":"Zhang","year":"2024"},{"key":"ref26","first-page":"103999","volume-title":"Llm-tikg: Threat intelligence knowledge graph construction utilizing large language model","volume":"145","author":"Hu","year":"2024"},{"key":"ref27","first-page":"104220","volume-title":"Attackg+: Boosting attack graph construction with large language models","volume":"150","author":"Zhang","year":"2025"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ACSACW65225.2024.00036"},{"key":"ref29","volume-title":"Attackseqbench: Benchmarking large language models\u2019 understanding of sequential patterns in cyber attacks","author":"Yong","year":"2025"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.5220\/0013289700003899"},{"key":"ref31","volume-title":"MITRE ATLAS Arsenal Plugin for CALDERA and Counterfit","year":"2024"},{"key":"ref32","volume-title":"Thremolia: Threat modeling of large language model-integrated applications","author":"Jedrzejewski","year":"2025"},{"key":"ref33","volume-title":"Tavily extract (API reference)","year":"2025"},{"key":"ref34","volume-title":"Beyond exact match: Semantically reassessing event extraction by large language models","author":"Lu","year":"2025"},{"key":"ref35","volume-title":"Careful Who You Colab With","year":"2025"},{"key":"ref36","article-title":"AML.CS0018: Arbitrary Code Execution with Google Colab","volume-title":"aTLAS Case Study","year":"2024"}],"event":{"name":"2026 IEEE International Conference on Software Analysis, Evolution and Reengineering - Companion (SANER-C)","location":"Limassol, Cyprus","start":{"date-parts":[[2026,3,17]]},"end":{"date-parts":[[2026,3,20]]}},"container-title":["2026 IEEE International Conference on Software Analysis, Evolution and Reengineering - Companion (SANER-C)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11500139\/11499992\/11500170.pdf?arnumber=11500170","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T04:18:02Z","timestamp":1778127482000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11500170\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,17]]},"references-count":36,"URL":"https:\/\/doi.org\/10.1109\/saner-c67878.2026.00048","relation":{},"subject":[],"published":{"date-parts":[[2026,3,17]]}}}