Pub Date : 2026-01-23DOI: 10.1109/TIFS.2026.3657031
Arman Ahmad;S. Jagatheswari
Blockchain-enabled Internet of Medical Things (BIoMT) systems require secure and anonymous authentication. However, existing mechanisms rely on classical cryptography, which becomes vulnerable to quantum attacks. This creates a critical need for post-quantum secure authentication that can preserve anonymity while remaining lightweight for large-scale deployments. To address this gap, we propose a module-lattice based Post-Quantum Aggregate Blind Signature (PQ-ABS) scheme that combines message blindness, signature aggregation, and Module-LWE hardness to achieve anonymous and quantum-resistant authentication. The scheme integrates with a lightweight blockchain architecture in which multiple signatures from distributed medical entities are aggregated into a single compact proof, significantly reducing verification overhead as the number of nodes increases. Formal analysis demonstrates resistance against correctness, unforgeability, blindness, unlinkability, and its resilience against quantum polynomial-time (QPT) adversaries under Module-SIS and Module-LWE assumptions. A full implementation on Hyperledger Fabric shows that, under growing network size, proposed PQ-ABS framework reduces verification latency by up to 71%, improves throughput by 62%, and maintains stable performance as the blockchain scales, confirming both its security and efficiency for real-time BIoMT environments.
{"title":"PQ-ABS: Post-Quantum Aggregate Blind Signature-Based Anonymous Authentication for Blockchain-Enabled IoMT","authors":"Arman Ahmad;S. Jagatheswari","doi":"10.1109/TIFS.2026.3657031","DOIUrl":"10.1109/TIFS.2026.3657031","url":null,"abstract":"Blockchain-enabled Internet of Medical Things (BIoMT) systems require secure and anonymous authentication. However, existing mechanisms rely on classical cryptography, which becomes vulnerable to quantum attacks. This creates a critical need for post-quantum secure authentication that can preserve anonymity while remaining lightweight for large-scale deployments. To address this gap, we propose a module-lattice based Post-Quantum Aggregate Blind Signature (PQ-ABS) scheme that combines message blindness, signature aggregation, and Module-LWE hardness to achieve anonymous and quantum-resistant authentication. The scheme integrates with a lightweight blockchain architecture in which multiple signatures from distributed medical entities are aggregated into a single compact proof, significantly reducing verification overhead as the number of nodes increases. Formal analysis demonstrates resistance against correctness, unforgeability, blindness, unlinkability, and its resilience against quantum polynomial-time (QPT) adversaries under Module-SIS and Module-LWE assumptions. A full implementation on Hyperledger Fabric shows that, under growing network size, proposed PQ-ABS framework reduces verification latency by up to 71%, improves throughput by 62%, and maintains stable performance as the blockchain scales, confirming both its security and efficiency for real-time BIoMT environments.","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"21 ","pages":"1542-1551"},"PeriodicalIF":8.0,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146043058","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}
{"title":"PHANTOM: Power Hammering Attack and Countermeasure on Multi-Tenant ReRAM Compute-in-Memory Accelerators","authors":"Ashish Reddy Bommana, Rajendra Bishnoi, Naghmeh Karimi, Farshad Firouzi, Krishnendu Chakrabarty","doi":"10.1109/tifs.2026.3657612","DOIUrl":"https://doi.org/10.1109/tifs.2026.3657612","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"57 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146043056","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}
{"title":"Cross-Region Feature Reformer with Semantic Preservation for Adversarial Malware Detection","authors":"Qian Li, Di Wu, Chenhao Lin, Shuai Liu, Cong Wang, Chao Shen","doi":"10.1109/tifs.2026.3657117","DOIUrl":"https://doi.org/10.1109/tifs.2026.3657117","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"40 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146043060","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 : 2026-01-22DOI: 10.1109/tifs.2026.3657043
Jie Gui, Yu-Xin Zhang, Xiaofeng Cong, Baosheng Yu, Zhipeng Gui, Yuan Yan Tang, James Tin-Yau Kwok
{"title":"Axial-View-Oriented Contrastive Adversarial Training for Robust Point Cloud Recognition","authors":"Jie Gui, Yu-Xin Zhang, Xiaofeng Cong, Baosheng Yu, Zhipeng Gui, Yuan Yan Tang, James Tin-Yau Kwok","doi":"10.1109/tifs.2026.3657043","DOIUrl":"https://doi.org/10.1109/tifs.2026.3657043","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"40 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146043078","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 : 2026-01-22DOI: 10.1109/tifs.2026.3657099
Yizhong Liu, Boyu Zhao, Mingzhe Zhai, Xun Lin, Chenhao Ying, Zhenyu Guan, Dawei Li, Qianhong Wu, Jianwei Liu, Willy Susilo, Robert H. Deng
{"title":"Multi-Leader Byzantine Fault Tolerance in Blockchain: Performance and Security","authors":"Yizhong Liu, Boyu Zhao, Mingzhe Zhai, Xun Lin, Chenhao Ying, Zhenyu Guan, Dawei Li, Qianhong Wu, Jianwei Liu, Willy Susilo, Robert H. Deng","doi":"10.1109/tifs.2026.3657099","DOIUrl":"https://doi.org/10.1109/tifs.2026.3657099","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"68 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146043081","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 : 2026-01-22DOI: 10.1109/tifs.2026.3657030
Rumia Sultana, Rémi A. Chou
{"title":"Secret Sharing Schemes from Correlated Random Variables and Rate-Limited Public Communication","authors":"Rumia Sultana, Rémi A. Chou","doi":"10.1109/tifs.2026.3657030","DOIUrl":"https://doi.org/10.1109/tifs.2026.3657030","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"3 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146043079","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}
Private protocol reverse engineering is the main way to solve the problem of unknown traffic which brings huge security risks to the current network environment. The network traffic-based protocol reverse engineering approaches are the basis of traffic security supervision and are also widely used and flexible. These approaches utilize multiple algorithms from different perspectives to extract the protocol specifications from messages, but they fail to recognize the importance of message segmentation and do not adequately evaluate the relation of adjacent bytes, leading to imprecise performance. To address these issues, we propose the SLMSP, a self-supervised learning-based message segmentation approach for private protocol reverse engineering in this paper. SLMSP mines the rich information embedded in the word order and word semantics between adjacent bytes through self-supervised learning, and then makes optimal decisions about where the message should be segmented based on the fusion of those information, combing the horizontal inference and vertical correction. After that, SLMSP extracts protocol formats based on fine-grained message segmentation by introducing the progressive sequence merging algorithm. We conduct comprehensive experiments to demonstrate the effectiveness of SLMSP. The experimental results demonstrate that SLMSP achieves the ideal performance both in message segmentation and format inference, and it also has advantages over previous works.
{"title":"Private Protocol Reverse Engineering via Self-Supervised Learning-Based Message Segmentation","authors":"Junchen Li;Guang Cheng;Huimin Tang;Ying Hu;Qinghua Shang","doi":"10.1109/TIFS.2026.3657097","DOIUrl":"10.1109/TIFS.2026.3657097","url":null,"abstract":"Private protocol reverse engineering is the main way to solve the problem of unknown traffic which brings huge security risks to the current network environment. The network traffic-based protocol reverse engineering approaches are the basis of traffic security supervision and are also widely used and flexible. These approaches utilize multiple algorithms from different perspectives to extract the protocol specifications from messages, but they fail to recognize the importance of message segmentation and do not adequately evaluate the relation of adjacent bytes, leading to imprecise performance. To address these issues, we propose the SLMSP, a self-supervised learning-based message segmentation approach for private protocol reverse engineering in this paper. SLMSP mines the rich information embedded in the word order and word semantics between adjacent bytes through self-supervised learning, and then makes optimal decisions about where the message should be segmented based on the fusion of those information, combing the horizontal inference and vertical correction. After that, SLMSP extracts protocol formats based on fine-grained message segmentation by introducing the progressive sequence merging algorithm. We conduct comprehensive experiments to demonstrate the effectiveness of SLMSP. The experimental results demonstrate that SLMSP achieves the ideal performance both in message segmentation and format inference, and it also has advantages over previous works.","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"21 ","pages":"1926-1940"},"PeriodicalIF":8.0,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146043080","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 : 2026-01-22DOI: 10.1109/tifs.2026.3657093
Hua Deng, Letian Sha, Hui Yin, Zheng Qin, Yuying Liu
{"title":"Match on My Own: Fine-Grained Bilateral Access Control with Self-Constrained Matching for Online Social Networks","authors":"Hua Deng, Letian Sha, Hui Yin, Zheng Qin, Yuying Liu","doi":"10.1109/tifs.2026.3657093","DOIUrl":"https://doi.org/10.1109/tifs.2026.3657093","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"29 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146043075","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}
{"title":"Secure and Customized Data Sharing with Identical Sub-Policy and Bilateral Access Control","authors":"Fuyuan Song, Chuan Zhang, Zhangjie Fu, Meng Li, Zheng Qin, Liehuang Zhu","doi":"10.1109/tifs.2026.3657105","DOIUrl":"https://doi.org/10.1109/tifs.2026.3657105","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"17 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146043082","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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