Pub Date : 2026-03-09DOI: 10.1109/tifs.2026.3672018
Shanshan Li, Mengfan Ma, Yunxia Han
{"title":"SE-ASSO: A Security-Enhanced Anonymous Single-Sign-On Authentication Scheme","authors":"Shanshan Li, Mengfan Ma, Yunxia Han","doi":"10.1109/tifs.2026.3672018","DOIUrl":"https://doi.org/10.1109/tifs.2026.3672018","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"16 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147380597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-09DOI: 10.1109/tifs.2026.3672386
Yugeng Liu, Tianshuo Cong, Zhengyu Zhao, Michael Backes, Yun Shen, Yang Zhang
{"title":"Robustness Over Time: Understanding Adversarial Examples’ Effectiveness on Longitudinal Versions of Large Language Models","authors":"Yugeng Liu, Tianshuo Cong, Zhengyu Zhao, Michael Backes, Yun Shen, Yang Zhang","doi":"10.1109/tifs.2026.3672386","DOIUrl":"https://doi.org/10.1109/tifs.2026.3672386","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"5 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147380601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-09DOI: 10.1109/tifs.2026.3672007
Menghao Li, Mingxun Wang, Weiwei Zhang, Wenfeng Guo, Jun Li
{"title":"RFFRDet: A Refined Feature Fusion Rotation Detector for Prohibited Item Recognition in X-ray Images","authors":"Menghao Li, Mingxun Wang, Weiwei Zhang, Wenfeng Guo, Jun Li","doi":"10.1109/tifs.2026.3672007","DOIUrl":"https://doi.org/10.1109/tifs.2026.3672007","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"31 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147380596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-09DOI: 10.1109/tifs.2026.3672383
Anli Yan, Huali Ren, Kanghua Mo, Peigen Ye, Zhenxin Zhang, Hongyang Yan, Jin Li
{"title":"Your Non-Transferable Learning is Fragile: Practical Breach of Protected Models","authors":"Anli Yan, Huali Ren, Kanghua Mo, Peigen Ye, Zhenxin Zhang, Hongyang Yan, Jin Li","doi":"10.1109/tifs.2026.3672383","DOIUrl":"https://doi.org/10.1109/tifs.2026.3672383","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"40 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147380598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-09DOI: 10.1109/tifs.2026.3672000
Yunlu Tu, Siyang Li, Xiaoqing Chen, Dongrui Wu
{"title":"BrainprintNet: A Multiscale Cross-Band Fusion Network for EEG-based Brainprint Recognition","authors":"Yunlu Tu, Siyang Li, Xiaoqing Chen, Dongrui Wu","doi":"10.1109/tifs.2026.3672000","DOIUrl":"https://doi.org/10.1109/tifs.2026.3672000","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"127 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147380600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-09DOI: 10.1109/tifs.2026.3671018
, Nand Kishor, S. Purwar, V. S. Rajkumar
{"title":"State Partition-Particle Filter Detection for Cyber-Physical Attacks","authors":", Nand Kishor, S. Purwar, V. S. Rajkumar","doi":"10.1109/tifs.2026.3671018","DOIUrl":"https://doi.org/10.1109/tifs.2026.3671018","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"5 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147380599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-06DOI: 10.1109/tifs.2026.3671577
Yang Liu, Man Sun, Zhuzhu Wang, Xinjing Liu, Yong Zeng, Jiayu Jin, Zhuo Ma
{"title":"Urey-ML: A Machine Learning-based Distance Deception Attack against Apple UWB Interaction Frameworks","authors":"Yang Liu, Man Sun, Zhuzhu Wang, Xinjing Liu, Yong Zeng, Jiayu Jin, Zhuo Ma","doi":"10.1109/tifs.2026.3671577","DOIUrl":"https://doi.org/10.1109/tifs.2026.3671577","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"16 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147371489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-05DOI: 10.1109/tifs.2026.3671064
Ziyuan Yang, Yingyu Chen, Chengrui Gao, Andrew Beng Jin Teoh, Bob Zhang, Yi Zhang
{"title":"FedPalm: A General Federated Learning Framework for Closed- and Open-Set Palmprint Verification","authors":"Ziyuan Yang, Yingyu Chen, Chengrui Gao, Andrew Beng Jin Teoh, Bob Zhang, Yi Zhang","doi":"10.1109/tifs.2026.3671064","DOIUrl":"https://doi.org/10.1109/tifs.2026.3671064","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"3 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147371544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-05DOI: 10.1109/TIFS.2026.3671095
Yu Zheng;Zhuoxun Li;Bingyao Yu;Jie Zhou;Jiwen Lu
In this paper, we propose a hyperparameter-specialized adaptive fingerprinting framework named AdaParse for model reverse engineering, which aims at predicting hyperparameters of interest in generative models from the given AI-generated images. Existing methods rely on a single coarse model fingerprint that is originally designed for model-level attribution, which makes it difficult to distinguish fine-grained traces corresponding to different hyperparameter configurations in a multitude of generative models. To address this, our AdaParse dynamically responds to instance-level variations by estimating hyperparameter-specific fingerprints via personalizing estimation networks tailored for each input image. Specifically, our approach simultaneously learns two-branch hypernetworks that balance instance-aware and model-agnostic prior knowledge for fingerprint generation. To enable efficient network personalization, we further propose a Broadcasted Fusion module that transforms condensed feature codes into adaptive parameters through factorized weight generation with enhanced representative capacity. Extensive experiments on the large-scale public dataset across 123 generative models demonstrate that our approach outperforms previous state-of-the-art methods. Code available at https://github.com/lizhuoxun/AdaParse/
{"title":"AdaParse: Personalized Fingerprinting for Visual Generative Model Reverse Engineering","authors":"Yu Zheng;Zhuoxun Li;Bingyao Yu;Jie Zhou;Jiwen Lu","doi":"10.1109/TIFS.2026.3671095","DOIUrl":"10.1109/TIFS.2026.3671095","url":null,"abstract":"In this paper, we propose a hyperparameter-specialized adaptive fingerprinting framework named AdaParse for model reverse engineering, which aims at predicting hyperparameters of interest in generative models from the given AI-generated images. Existing methods rely on a single coarse model fingerprint that is originally designed for model-level attribution, which makes it difficult to distinguish fine-grained traces corresponding to different hyperparameter configurations in a multitude of generative models. To address this, our AdaParse dynamically responds to instance-level variations by estimating hyperparameter-specific fingerprints via personalizing estimation networks tailored for each input image. Specifically, our approach simultaneously learns two-branch hypernetworks that balance instance-aware and model-agnostic prior knowledge for fingerprint generation. To enable efficient network personalization, we further propose a Broadcasted Fusion module that transforms condensed feature codes into adaptive parameters through factorized weight generation with enhanced representative capacity. Extensive experiments on the large-scale public dataset across 123 generative models demonstrate that our approach outperforms previous state-of-the-art methods. Code available at <uri>https://github.com/lizhuoxun/AdaParse/</uri>","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"21 ","pages":"2682-2697"},"PeriodicalIF":8.0,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147371543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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