@inproceedings{oai:ipsj.ixsq.nii.ac.jp:00240774,
 author = {浅田, かんな and 小出, 洋 and 牛尼, 剛聡 and Kanna, Asada and Hiroshi, Koide and Taketoshi, Ushiama},
 book = {コンピュータセキュリティシンポジウム2024論文集},
 month = {Oct},
 note = {本研究では， 従来のセキュリティ質問（秘密の質問）が持つ課題を解決し， より有効な認証方式を提案する． SNSなどで簡単に突破される普遍的な質問ではなく， 他人に話さないような個人的なエピソードを基にすることにより， 強固なセキュリティを実現する． 具体的には， LLM（大規模言語モデル）を用いてユーザーのエピソードを収集・精査し, 認証時にはダミーデータを含む選択肢を提示する． ダミーデータの作成にもLLMを用い， より見破り難い精緻なものとなっている． 実際にデモシステムを実装し，被験者実験を行った．実験の結果，提案手法はユーザーエクスペリエンスを格段に高めることが分かった．また，セキュリティ強度の議論において，現実で使用されているパスワードの強度と，同等以上の性能があることを示す．, This research addresses the limitations of conventional security questions, also known as secret questions, by proposing a more robust authentication method. Traditional security questions are often vulnerable, as answers can be deduced from users’ social media activity or other public information. To enhance security, we propose an approach based on personal anecdotes that are not publicly shared. Specifically, we utilize a large-scale language model (LLM) to gather and analyze user-specific episodes, which are then employed during the authentication process along with carefully crafted dummy data. The LLM is also utilized to generate this dummy data, increasing its plausibility and reducing the likelihood of detection. A demonstration system was implemented, and user experiments were conducted. Experimental results showed that the proposed method significantly enhances the user experience. In addition, in the security strength discussion, it was shown that the proposed method performs as well as or better than the password strength used in the real world.},
 pages = {206--213},
 publisher = {情報処理学会},
 title = {エピソード認証：LLMを活用したエピソードベース認証方式の提案},
 year = {2024}
}