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Paper Abstract and Keywords
Presentation 2026-03-04 15:50
Proposal of a vulnerability assessment environment for prompt injection
Shingo Ogawa, Eiji Kuwana (IISEC) ICSS2025-137
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, with the rapid proliferation of large language models (LLMs), prompt injection (PI) vulnerabilities have been increasingly recognized as a critical security risk. However, much of the existing research has focused on singular evaluations that emphasize either attack prevention or attack detection, and the effectiveness of combining these two defensive approaches has not been sufficiently demonstrated. In addition, evaluation metrics and experimental conditions are not standardized across prior studies, resulting in limited comparability of defensive performance. To address these challenges, this study proposes an Integrated Defense Environment, an evaluation framework that unifies prevention and detection mechanisms. Using this environment, we conduct systematic measurements under three scenarios: no defense, single defense, and the proposed integrated defense by defining evaluation metrics such as attack success rate, false positive rate, and false negative rate. Through empirical evaluation, we demonstrate that the integrated defense outperforms single-defense approaches in terms of robustness and reliability, and we establish a reproducible vulnerability assessment framework for prompt injection attacks.
Keyword (in Japanese) (See Japanese page) 
(in English) Prompt Injection / Large Language Models (LLM) / Security / Vulnerability Assessment / LLM Guard / Guardrails AI / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 381, ICSS2025-137, pp. 386-393, March 2026.
Paper # ICSS2025-137 
Date of Issue 2026-02-24 (ICSS) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF ICSS2025-137

Conference Information
Committee ICSS IPSJ-SPT  
Conference Date 2026-03-03 - 2026-03-04 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa Prefectural Museum & Art Museum 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Security, Trust, etc. 
Paper Information
Registration To ICSS 
Conference Code 2026-03-ICSS-SPT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Proposal of a vulnerability assessment environment for prompt injection 
Sub Title (in English)  
Keyword(1) Prompt Injection  
Keyword(2) Large Language Models (LLM)  
Keyword(3) Security  
Keyword(4) Vulnerability Assessment  
Keyword(5) LLM Guard  
Keyword(6) Guardrails AI  
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Keyword(8)  
1st Author's Name Shingo Ogawa  
1st Author's Affiliation Institute of Information security (IISEC)
2nd Author's Name Eiji Kuwana  
2nd Author's Affiliation Institute of Information security (IISEC)
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Speaker Author-1 
Date Time 2026-03-04 15:50:00 
Presentation Time 20 minutes 
Registration for ICSS 
Paper # ICSS2025-137 
Volume (vol) vol.125 
Number (no) no.381 
Page pp.386-393 
#Pages 8 
Date of Issue 2026-02-24 (ICSS) 

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