Pub Date : 2025-02-21DOI: 10.1109/tifs.2025.3544485
Marc Dib, Samuel Pierre
{"title":"HSM-Based Architecture to Detect Insider Attacks on Server-Side Data","authors":"Marc Dib, Samuel Pierre","doi":"10.1109/tifs.2025.3544485","DOIUrl":"https://doi.org/10.1109/tifs.2025.3544485","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"3 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143470583","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 : 2025-02-20DOI: 10.1109/tifs.2025.3544034
Ximing Fu, Mo Li, Qingming Zeng, Tianyang Li, Shenghao Yang, Yonghui Guan, Chuanyi Liu
{"title":"Hamster: A Fast Synchronous Byzantine Fault Tolerant Protocol","authors":"Ximing Fu, Mo Li, Qingming Zeng, Tianyang Li, Shenghao Yang, Yonghui Guan, Chuanyi Liu","doi":"10.1109/tifs.2025.3544034","DOIUrl":"https://doi.org/10.1109/tifs.2025.3544034","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"21 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143462597","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 : 2025-02-20DOI: 10.1109/tifs.2025.3544072
Zhenhua Chen, Kaili Long, Junrui Xie, Qiqi Lai, Yilei Wang, Ni Li, Luqi Huang, Aijun Ge
{"title":"A New Functional Encryption Scheme Supporting Privacy-Preserving Maximum Similarity for Web Service Platforms","authors":"Zhenhua Chen, Kaili Long, Junrui Xie, Qiqi Lai, Yilei Wang, Ni Li, Luqi Huang, Aijun Ge","doi":"10.1109/tifs.2025.3544072","DOIUrl":"https://doi.org/10.1109/tifs.2025.3544072","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"18 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143462624","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 : 2025-02-20DOI: 10.1109/tifs.2025.3544088
Shuoyi Chen, Mang Ye, Yan Huang, Bo Du
{"title":"Towards Effective Rotation Generalization in UAV Object Re-Identification","authors":"Shuoyi Chen, Mang Ye, Yan Huang, Bo Du","doi":"10.1109/tifs.2025.3544088","DOIUrl":"https://doi.org/10.1109/tifs.2025.3544088","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"38 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143462594","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 : 2025-02-20DOI: 10.1109/tifs.2025.3544082
Yuanchao Chen, Yuwei Li, Yuliang Lu, Zulie Pan, Yuan Chen Shouling Ji, Yu Chen, Yang Li, Yi Shen
{"title":"Understanding the Security Risks of Websites Using Cloud Storage for Direct User File Uploads","authors":"Yuanchao Chen, Yuwei Li, Yuliang Lu, Zulie Pan, Yuan Chen Shouling Ji, Yu Chen, Yang Li, Yi Shen","doi":"10.1109/tifs.2025.3544082","DOIUrl":"https://doi.org/10.1109/tifs.2025.3544082","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"1 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143462593","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":"Can We Trust the Similarity Measurement in Federated Learning?","authors":"Zhilin Wang, Qin Hu, Xukai Zou, Pengfei Hu, Xiuzhen Cheng","doi":"10.1109/tifs.2024.3516567","DOIUrl":"https://doi.org/10.1109/tifs.2024.3516567","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"14 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143462626","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 : 2025-02-20DOI: 10.1109/tifs.2025.3544066
Charles Gouert, Dimitris Mouris, Nektarios Georgios Tsoutsos
{"title":"HELM: Navigating Homomorphic Encryption through Gates and Lookup Tables","authors":"Charles Gouert, Dimitris Mouris, Nektarios Georgios Tsoutsos","doi":"10.1109/tifs.2025.3544066","DOIUrl":"https://doi.org/10.1109/tifs.2025.3544066","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"25 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143462596","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 : 2025-02-18DOI: 10.1109/tifs.2025.3542959
Huici Wu, Yi Fang, Na Li, Xin Yuan, Zhiqing Wei, Guoshun Nan, Xiaofeng Tao
{"title":"Secret Key Generation With Untrusted Internal Eavesdropper: Token-based Anti-eavesdropping","authors":"Huici Wu, Yi Fang, Na Li, Xin Yuan, Zhiqing Wei, Guoshun Nan, Xiaofeng Tao","doi":"10.1109/tifs.2025.3542959","DOIUrl":"https://doi.org/10.1109/tifs.2025.3542959","url":null,"abstract":"","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"64 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143443668","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 : 2025-02-17DOI: 10.1109/TIFS.2025.3542964
Xiao Li;Hang Chen;Xiaolin Hu
Object detection is a critical component of various security-sensitive applications, such as autonomous driving and video surveillance. However, existing object detectors are vulnerable to adversarial attacks, which poses a significant challenge to their reliability and security. Through experiments, first, we found that existing works on improving the adversarial robustness of object detectors give a false sense of security. Second, we found that adversarially pre-trained backbone networks were essential for enhancing the adversarial robustness of object detectors. We then proposed a simple yet effective recipe for fast adversarial fine-tuning on object detectors with adversarially pre-trained backbones. Without any modifications to the structure of object detectors, our recipe achieved significantly better adversarial robustness than previous works. Finally, we explored the potential of different modern object detector designs for improving adversarial robustness with our recipe and demonstrated interesting findings, which inspired us to design state-of-the-art (SOTA) robust detectors. Our empirical results set a new milestone for adversarially robust object detection. Code and trained checkpoints are available at https://github.com/thu-ml/oddefense.
{"title":"On the Importance of Backbone to the Adversarial Robustness of Object Detectors","authors":"Xiao Li;Hang Chen;Xiaolin Hu","doi":"10.1109/TIFS.2025.3542964","DOIUrl":"10.1109/TIFS.2025.3542964","url":null,"abstract":"Object detection is a critical component of various security-sensitive applications, such as autonomous driving and video surveillance. However, existing object detectors are vulnerable to adversarial attacks, which poses a significant challenge to their reliability and security. Through experiments, first, we found that existing works on improving the adversarial robustness of object detectors give a false sense of security. Second, we found that adversarially pre-trained backbone networks were essential for enhancing the adversarial robustness of object detectors. We then proposed a simple yet effective recipe for fast adversarial fine-tuning on object detectors with adversarially pre-trained backbones. Without any modifications to the structure of object detectors, our recipe achieved significantly better adversarial robustness than previous works. Finally, we explored the potential of different modern object detector designs for improving adversarial robustness with our recipe and demonstrated interesting findings, which inspired us to design state-of-the-art (SOTA) robust detectors. Our empirical results set a new milestone for adversarially robust object detection. Code and trained checkpoints are available at <uri>https://github.com/thu-ml/oddefense</uri>.","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"20 ","pages":"2387-2398"},"PeriodicalIF":6.3,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143443698","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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