IET Information Security最新文献_第2页

Securing Machine-Type Communications: A Survey on Privacy Threats and Countermeasures 保护机器类型通信：隐私威胁与对策综述

IF 2.6 4区计算机科学

IET Information Security Pub Date : 2026-06-11 DOI: 10.1049/ise2/7728869

Amirhosein Imani, Alireza Keshavarz-Haddad

{"title":"Securing Machine-Type Communications: A Survey on Privacy Threats and Countermeasures","authors":"Amirhosein Imani, Alireza Keshavarz-Haddad","doi":"10.1049/ise2/7728869","DOIUrl":"https://doi.org/10.1049/ise2/7728869","url":null,"abstract":"Machine-type communication (MTC) is a fundamental enabler of the Internet of Things (IoT) and emerging 5G/6G networks, supporting massive deployments of heterogeneous and resource-constrained devices. However, large-scale data collection, persistent connectivity, and limited device capabilities introduce critical privacy challenges that are not adequately addressed by conventional security mechanisms designed for human-centric or homogeneous networks. This survey presents a comprehensive analysis of privacy threats and countermeasures in MTC networks. Using a domain-based approach aligned with the ETSI M2M architecture, we examine privacy vulnerabilities and attacks across the device, network, and application domains. We further provide a structured classification of privacy-preserving solutions, encompassing identity protection, data confidentiality, and behavioral obfuscation, and compare them in terms of effectiveness and deployment feasibility. Finally, we identify open challenges and research directions for scalable and lightweight privacy protection in massive MTC environments and propose a cybersecurity framework that integrates technical, regulatory, and operational considerations to support trustworthy MTC systems.","PeriodicalId":50380,"journal":{"name":"IET Information Security","volume":"2026 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ise2/7728869","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148237841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MPC-Facilitated Adaptive Security Framework for BFT Protocols 基于mpc的BFT协议自适应安全框架

IF 2.6 4区计算机科学

IET Information Security Pub Date : 2026-06-03 DOI: 10.1049/ise2/7043746

Jie Niu, Baocang Wang

{"title":"MPC-Facilitated Adaptive Security Framework for BFT Protocols","authors":"Jie Niu, Baocang Wang","doi":"10.1049/ise2/7043746","DOIUrl":"https://doi.org/10.1049/ise2/7043746","url":null,"abstract":"The growing use of blockchain and distributed systems requires Byzantine fault tolerant (BFT) protocols that remain secure under dynamic adversaries. However, existing BFT protocols often rely on static assumptions and lack clear mechanisms to detect and remove malicious or denial-of-service (DoS) nodes during execution. We present MBFT, a BFT framework that combines secure multi-party computation (MPC) with protocol-level node verification. MBFT integrates ElGamal threshold encryption with an SPDZ-style preprocessing phase and uses MAC-based checks to detect inconsistent behavior. It also adopts a hybrid timestamp oracle with off-chain aggregation and on-chain validation to support time-bounded decisions. We specify its trust assumptions and analyze its failure cases within the protocol. Our analysis shows that MBFT maintains safety and liveness under adaptive adversaries, including censorship, internal Byzantine faults, and DoS attacks. Experimental results show that, for a network with n = 32 nodes, MBFT achieves an average per-round latency of about 0.5 s on desktop platforms, which is comparable to Dumbo BFT under the same setting. The additional cost introduced by node verification remains small, contributing less than 5% of the total latency. In terms of communication, MBFT incurs approximately 27.2 kB total traffic per round, reducing communication overhead by about 50% compared to HoneyBadger BFT and remaining within 4%–6% of Dumbo BFT. These results indicate that MBFT preserves the efficiency of asynchronous BFT protocols while providing explicit support for node accountability.","PeriodicalId":50380,"journal":{"name":"IET Information Security","volume":"2026 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ise2/7043746","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148173844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IF 2.6 4区计算机科学

IET Information Security Pub Date : 2026-05-20

引用次数: 0

IF 2.6 4区计算机科学

IET Information Security Pub Date : 2026-05-09

引用次数: 0

Automated and Explainable Denial of Service Analysis for AI-Driven Intrusion Detection Systems 人工智能驱动的入侵检测系统的自动和可解释的拒绝服务分析

IF 2.6 4区计算机科学

IET Information Security Pub Date : 2026-04-08 DOI: 10.1049/ise2/7264961

Paul Badu Yakubu, Lesther Santana, Mohamed Rahouti, Yufeng Xin, Abdellah Chehri, Mohammed Aledhari

{"title":"Automated and Explainable Denial of Service Analysis for AI-Driven Intrusion Detection Systems","authors":"Paul Badu Yakubu, Lesther Santana, Mohamed Rahouti, Yufeng Xin, Abdellah Chehri, Mohammed Aledhari","doi":"10.1049/ise2/7264961","DOIUrl":"10.1049/ise2/7264961","url":null,"abstract":"With the increasing frequency and sophistication of distributed denial of service (DDoS) attacks, it has become critical to develop more efficient and interpretable detection methods. Traditional detection systems often struggle with scalability and transparency, hindering real-time response and understanding of attack vectors. This article presents an automated framework for detecting and interpreting DDoS attacks using machine learning (ML). The proposed method leverages the tree-based pipeline optimization tool (TPOT) to automate the selection and optimization of ML models and features, reducing the need for manual experimentation. SHapley Additive exPlanations (SHAPs) are incorporated to enhance model interpretability, providing detailed insights into the contribution of individual features to the detection process. By combining TPOT’s automated pipeline selection with SHAP’s interpretability, this approach improves the accuracy and transparency of DDoS detection. Experimental results demonstrate that key features such as mean backward packet length and minimum forward packet header length are critical in detecting DDoS attacks, offering a scalable and explainable cybersecurity solution.","PeriodicalId":50380,"journal":{"name":"IET Information Security","volume":"2026 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ise2/7264961","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IF 2.6 4区计算机科学

IET Information Security Pub Date : 2026-04-08

引用次数: 0

IF 2.6 4区计算机科学

IET Information Security Pub Date : 2026-04-05

引用次数: 0

Fusion of Siamese Network-Based Sclera and Iris Detection: A Multimodal Biometrics Approach Using a Sclera Detection Tracing Algorithm 基于Siamese网络的巩膜和虹膜检测融合：一种使用巩膜检测跟踪算法的多模态生物识别方法

IF 2.6 4区计算机科学

IET Information Security Pub Date : 2026-04-05 DOI: 10.1049/ise2/5569382

Jide Kehinde Adeniyi, Tunde Taiwo Adeniyi, Sunday Adeola Ajagbe, Precious Ikpemhinogena Ogie, Emmanuel Oluwatobi Asani, Matthew O. Adigun

{"title":"Fusion of Siamese Network-Based Sclera and Iris Detection: A Multimodal Biometrics Approach Using a Sclera Detection Tracing Algorithm","authors":"Jide Kehinde Adeniyi, Tunde Taiwo Adeniyi, Sunday Adeola Ajagbe, Precious Ikpemhinogena Ogie, Emmanuel Oluwatobi Asani, Matthew O. Adigun","doi":"10.1049/ise2/5569382","DOIUrl":"10.1049/ise2/5569382","url":null,"abstract":"Traditional security methods need to be improved as a result of security difficulties over time. Biometrics was introduced as a result of this. The sclera has been an area of extensive study recently as far as biometrics is concerned. This is because it is accurate; nevertheless, the application of this biometric feature has been limited by its segmentation. It is still necessary to improve segmentation accuracy even though several techniques have been published in the literature. This study recommends using a sclera detection tracing (SDT) approach in conjunction with the circular Hough transform. Additionally, a system based on the discrete wavelet transform (DWT) fusion of local binary-based features of the iris and sclera was proposed by the study. The fusion was passed to a Siamese network for classification. A comparison between the outcomes of the unimodal and bimodal systems was conducted. The result showed that the best performance of 98.5 was obtained for the fusion of the two biometrics. Likewise, the sclera result based on the sclera detection algorithm performed better than the segmentation that was done with the convolutional neural network (CNN).","PeriodicalId":50380,"journal":{"name":"IET Information Security","volume":"2026 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ise2/5569382","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IF 2.6 4区计算机科学

IET Information Security Pub Date : 2026-03-24

引用次数: 0

Utilising Video Deepfakes for Paper Voting Privacy Defence 利用视频深度造假进行纸质投票隐私保护

IF 2.6 4区计算机科学

IET Information Security Pub Date : 2026-03-24 DOI: 10.1049/ise2/2236872

Anette Habanen, Jan Willemson, Sven Laur

{"title":"Utilising Video Deepfakes for Paper Voting Privacy Defence","authors":"Anette Habanen, Jan Willemson, Sven Laur","doi":"10.1049/ise2/2236872","DOIUrl":"https://doi.org/10.1049/ise2/2236872","url":null,"abstract":"The recent rise of artificial intelligence (AI) solutions has also had a significant impact on electoral processes. Most notably, deepfakes created by generative AI applications can (and have been) used to spread misinformation during the campaigns, but they can also be used for cyberattack automation, biased social media bots, etc. We instead present a positive use case for generative AI in manipulating video material required as proof of voting by potential coercers. For this, we have created a pipeline that takes a video of a voting ballot and replaces its critical content (in our case, the digits on the ballot). To achieve this, a YOLOv11 model is used to find the digits, a WavePaint image inpainting model is used to cover up the old digits and a separate image of the new digits is used to place them into the video. Additionally, we implemented the prototype application in the form of a web service and validated the outcome by asking the humans to distinguish fake ballot images and videos from the real ones. Our results show that humans can still recognise fake ballot videos relatively well, implying that requesting ballot videos is still an efficient attack against voter freedom in the case of paper voting. However, future developments in the generative AI techniques are likely to improve the situation significantly.","PeriodicalId":50380,"journal":{"name":"IET Information Security","volume":"2026 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ise2/2236872","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147568970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0