{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T11:49:52Z","timestamp":1773316192894,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819562084","type":"print"},{"value":"9789819562091","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026]]},"DOI":"10.1007\/978-981-95-6209-1_19","type":"book-chapter","created":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T02:26:14Z","timestamp":1767320774000},"page":"349-368","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["CANalyze-AI: Semantic Zero-Day Detection and\u00a0Rule Synthesis via\u00a0LoRA-Fine-Tuned LLM for\u00a0CAN Security"],"prefix":"10.1007","author":[{"given":"Awais","family":"Bilal","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liehuang","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kashif","family":"Sharif","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fan","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sadaf","family":"Bukhari","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,1,2]]},"reference":[{"key":"19_CR1","doi-asserted-by":"crossref","unstructured":"Almehdhar, M., et al.: Deep learning in the fast lane: a survey on advanced intrusion detection systems for intelligent vehicle networks. IEEE Open J. Veh. Technol. (2024)","DOI":"10.1109\/OJVT.2024.3422253"},{"issue":"3","key":"19_CR2","doi-asserted-by":"publisher","first-page":"1445","DOI":"10.1109\/COMST.2023.3264928","volume":"25","author":"A Buscemi","year":"2023","unstructured":"Buscemi, A., Turcanu, I., Castignani, G., Panchenko, A., Engel, T., Shin, K.G.: A survey on controller area network reverse engineering. IEEE Commun. Surv. Tutor. 25(3), 1445\u20131481 (2023)","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"19_CR3","doi-asserted-by":"crossref","unstructured":"Chatterjee, R., Green, C., Daily, J.: Exploiting diagnostic protocol vulnerabilities on embedded networks in commercial vehicles. In: Symposium on Vehicles Security and Privacy (VehicleSec) (2024)","DOI":"10.14722\/vehiclesec.2024.23046"},{"key":"19_CR4","unstructured":"Chen, X., Xu, L.: Lora-enabled lightweight LLMs for IoT malware classification. In: USENIX Security (2023)"},{"key":"19_CR5","doi-asserted-by":"crossref","unstructured":"Chen, Y., et al.: A survey of large language models for cyber threat detection. Comput. Secur. 104016 (2024)","DOI":"10.1016\/j.cose.2024.104016"},{"key":"19_CR6","doi-asserted-by":"publisher","first-page":"9015","DOI":"10.52202\/075280-0396","volume":"36","author":"P Dong","year":"2023","unstructured":"Dong, P., et al.: PackQViT: faster sub-8-bit vision transformers via full and packed quantization on the mobile. Adv. Neural. Inf. Process. Syst. 36, 9015\u20139028 (2023)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"issue":"5","key":"19_CR7","doi-asserted-by":"publisher","first-page":"3843","DOI":"10.1109\/TITS.2023.3323622","volume":"25","author":"Y Jeong","year":"2023","unstructured":"Jeong, Y., Kim, H., Lee, S., Choi, W., Lee, D.H., Jo, H.J.: In-vehicle network intrusion detection system using can frame-aware features. IEEE Trans. Intell. Transp. Syst. 25(5), 3843\u20133853 (2023)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"19_CR8","doi-asserted-by":"crossref","unstructured":"Jin, S., Chung, J.G., Xu, Y.: Signature-based intrusion detection system (IDS) for in-vehicle can bus network. In: 2021 IEEE International Symposium on Circuits and Systems (ISCAS), pp.\u00a01\u20135. IEEE (2021)","DOI":"10.1109\/ISCAS51556.2021.9401087"},{"key":"19_CR9","volume":"50","author":"H Kang","year":"2024","unstructured":"Kang, H., Vo, T., Kim, H.K., Hong, J.B.: Canival: a multimodal approach to intrusion detection on the vehicle can bus. Veh. Commun. 50, 100845 (2024)","journal-title":"Veh. Commun."},{"key":"19_CR10","unstructured":"Kumar, A., Singh, R.: Automated security rule induction using GPT-3.5. ACM TISSEC (2024)"},{"key":"19_CR11","doi-asserted-by":"crossref","unstructured":"Lee, D., Han, C., Lee, S.: Hardware design of intrusion detection system for automotive can bus using random forest. In: 2023 International Conference on Electronics, Information, and Communication (ICEIC), pp.\u00a01\u20134. IEEE (2023)","DOI":"10.1109\/ICEIC57457.2023.10049883"},{"key":"19_CR12","unstructured":"Li, Y., Zhao, H.: Adaptive structured pruning for real-time anomaly detection RNNs. IEEE IoT J. (2024)"},{"key":"19_CR13","unstructured":"Liang, X., Wang, J.: Semantic clustering of siem alerts with t5. In: USENIX WOOT (2023)"},{"key":"19_CR14","volume":"35","author":"W Lo","year":"2022","unstructured":"Lo, W., Alqahtani, H., Thakur, K., Almadhor, A., Chander, S., Kumar, G.: A hybrid deep learning based intrusion detection system using spatial-temporal representation of in-vehicle network traffic. Veh. Commun. 35, 100471 (2022)","journal-title":"Veh. Commun."},{"key":"19_CR15","unstructured":"Patel, S., Rao, P.: Instruction-tuned LLMs for threat hunting playbooks. IEEE Trans. Inf. Forensics Secur. (2024)"},{"key":"19_CR16","doi-asserted-by":"crossref","unstructured":"Pinto\u00a0Neto, E.C., et al.: CICIoV2024: advancing realistic IDS approaches against DoS and spoofing attack in IoV CAN bus. Internet Things 101209 (2024)","DOI":"10.1016\/j.iot.2024.101209"},{"key":"19_CR17","doi-asserted-by":"crossref","unstructured":"Purohit, S., Govindarasu, M.: ML-based anomaly detection for intra-vehicular can-bus networks. In: 2022 IEEE International Conference on Cyber Security and Resilience (CSR), pp. 233\u2013238. IEEE (2022)","DOI":"10.1109\/CSR54599.2022.9850292"},{"issue":"4","key":"19_CR18","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1109\/MCOMSTD.0001.2400042","volume":"8","author":"Y Sun","year":"2024","unstructured":"Sun, Y., Li, S., Iqbal, M., Taher, F.: Securing electric vehicles against can bus replay attacks: a message authentication approach. IEEE Commun. Standards Mag. 8(4), 88\u201395 (2024)","journal-title":"IEEE Commun. Standards Mag."},{"key":"19_CR19","doi-asserted-by":"publisher","first-page":"312","DOI":"10.1109\/OJITS.2021.3104495","volume":"2","author":"V Tanksale","year":"2021","unstructured":"Tanksale, V.: Design of anomaly detection functions for controller area networks. IEEE Open J. Intell. Transp. Syst. 2, 312\u2013321 (2021)","journal-title":"IEEE Open J. Intell. Transp. Syst."},{"key":"19_CR20","unstructured":"Wang, J., Li, S.: 4-bit quantized vision transformers for real-time edge inference. In: ACM\/IEEE IPSN (2023)"},{"key":"19_CR21","unstructured":"Wang, L., Zhao, Q., Lee, W.B., Wang, C.: Deploying intrusion detection on in-vehicle networks: challenges and opportunities. IEEE Netw. (2024)"},{"key":"19_CR22","unstructured":"Xu, H., et al.: Large language models for cyber security: a systematic literature review. arXiv preprint arXiv:2405.04760 (2024)"},{"key":"19_CR23","doi-asserted-by":"crossref","unstructured":"Yao, Y., Duan, J., Xu, K., Cai, Y., Sun, Z., Zhang, Y.: A survey on large language model (LLM) security and privacy: the good, the bad, and the ugly. High-Confidence Comput. 100211 (2024)","DOI":"10.1016\/j.hcc.2024.100211"},{"key":"19_CR24","doi-asserted-by":"crossref","unstructured":"Zhang, H., Huang, K., Wang, J., Liu, Z.: Can-FT: a fuzz testing method for automotive controller area network bus. In: 2021 International Conference on Computer Information Science and Artificial Intelligence (CISAI), pp. 225\u2013231. IEEE (2021)","DOI":"10.1109\/CISAI54367.2021.00050"},{"key":"19_CR25","unstructured":"Zhao, L., Chen, Y.: LLM-driven network log analysis for incident summarization. In: IEEE S &P (2023)"}],"container-title":["Lecture Notes in Computer Science","Information Security and Cryptology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-6209-1_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T17:44:39Z","timestamp":1773251079000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-6209-1_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819562084","9789819562091"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-6209-1_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"2 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"Inscrypt","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Information Security and Cryptology","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Xi'an","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 October 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 October 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cisc22025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/inscrypt2025.xidian.edu.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}