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Paper Abstract and Keywords
Presentation 2026-07-22 10:35
Continual Malware Classification by Characteristic-Aware Mechanism Assignment for Benign, Known, and Novel Malware
Sho Washika, Tomotaka Kimura, Jun Cheng (Doshisha Univ.) CQ2026-30
Abstract (in Japanese) (See Japanese page) 
(in English) Continual learning is important for malware detection because novel variants and families appear over time. In practical operation, a detector must suppress false positives on benign software, retain known malware families, and adapt to novel malware from only a small number of samples. EWC, Replay, and La-MAML provide constraints on changes in important model parameters, sample replay, and few-shot adaptation, respectively, but applying them alone or uniformly makes it difficult to maintain the benign false positive rate (FPR), known-malware recall (KR), and new-malware recall (NR) simultaneously. This paper proposes a class-wise mechanism assignment model for continual malware classification that assigns a different continual learning mechanism to each of benign, known, and novel malware according to its characteristics. The proposed method protects benign software using EWC based on benign Fisher information, maintains known malware using Reservoir Replay, and adapts to novel malware using La-MAML. Experiments on the BODMAS dataset in a 13-phase continual learning setting show that the proposed method improves NR while maintaining FPR and KR comparable to +MalReplay.
Keyword (in Japanese) (See Japanese page) 
(in English) Continual Learning / Malware Detection / Class-Wise Mechanism Assignment / Catastrophic Forgetting / Replay / La-MAML / Meta-Learning /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 121, CQ2026-30, pp. 95-100, July 2026.
Paper # CQ2026-30 
Date of Issue 2026-07-14 (CQ) 
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 CQ2026-30

Conference Information
Committee CQ  
Conference Date 2026-07-21 - 2026-07-23 
Place (in Japanese) (See Japanese page) 
Place (in English) Eef Jouhou Plaza 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To CQ 
Conference Code 2026-07-CQ 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Continual Malware Classification by Characteristic-Aware Mechanism Assignment for Benign, Known, and Novel Malware 
Sub Title (in English)  
Keyword(1) Continual Learning  
Keyword(2) Malware Detection  
Keyword(3) Class-Wise Mechanism Assignment  
Keyword(4) Catastrophic Forgetting  
Keyword(5) Replay  
Keyword(6) La-MAML  
Keyword(7) Meta-Learning  
Keyword(8)  
1st Author's Name Sho Washika  
1st Author's Affiliation Doshisha University (Doshisha Univ.)
2nd Author's Name Tomotaka Kimura  
2nd Author's Affiliation Doshisha University (Doshisha Univ.)
3rd Author's Name Jun Cheng  
3rd Author's Affiliation Doshisha University (Doshisha Univ.)
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Speaker Author-1 
Date Time 2026-07-22 10:35:00 
Presentation Time 25 minutes 
Registration for CQ 
Paper # CQ2026-30 
Volume (vol) vol.126 
Number (no) no.121 
Page pp.95-100 
#Pages 6 
Date of Issue 2026-07-14 (CQ) 

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