{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T16:55:51Z","timestamp":1782233751830,"version":"3.54.5"},"reference-count":0,"publisher":"Association for the Advancement of Artificial Intelligence (AAAI)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AAAI-SS"],"abstract":"<jats:p>Phishing URLs remain a major cybersecurity threat because\ntheir development is constantly changing and becoming more\ndeceptive. This study presented an agentic adaptive AI\nframework that utilizes a large language model as a\nreasoning agent operating multiple external tools instead\nof performing a classification, to detect phishing URLs. An\nlightweight tabular classifier with just 9,662 trainable\nparameters delivers predictions very efficiently, and\nexplains the relevance of features in terms of attack\nsimilarity based on SHAP-based feature attribution and\nepisodic memory retrieval. The agent combines these outputs\nfrom the tools to generate structured explanations and\nsecurity recommendations. Experiments demonstrate strong\nperformance, with accuracy up to 95.6% and AUC values\nabove 0.99.<\/jats:p>","DOI":"10.1609\/aaaiss.v9i1.42903","type":"journal-article","created":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T16:33:30Z","timestamp":1782232410000},"page":"35-42","source":"Crossref","is-referenced-by-count":0,"title":["A Lightweight Agentic AI Framework with DeepSeek-R1 for Adaptive Phishing URL Detection"],"prefix":"10.1609","volume":"9","author":[{"given":"Akshat","family":"Gaurav","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Varsha","family":"Arya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amiya","family":"Nayak","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kwok","family":"Tai Chui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brij","family":"B. Gupta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"9382","published-online":{"date-parts":[[2026,6,23]]},"container-title":["Proceedings of the AAAI Symposium Series"],"original-title":[],"link":[{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI-SS\/article\/download\/42903\/50463","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI-SS\/article\/download\/42903\/50463","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T16:33:30Z","timestamp":1782232410000},"score":1,"resource":{"primary":{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI-SS\/article\/view\/42903"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,23]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,6,23]]}},"URL":"https:\/\/doi.org\/10.1609\/aaaiss.v9i1.42903","relation":{},"ISSN":["2994-4317"],"issn-type":[{"value":"2994-4317","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,23]]}}}