IEEE Open Journal of the Computer Society最新文献_第7页

Real-Time High-Quality Visualization for Volumetric Contents Rendering: A Lyapunov Optimization Framework 体积内容绘制的实时高质量可视化：一个Lyapunov优化框架

IEEE Open Journal of the Computer Society Pub Date : 2023-09-06 DOI: 10.1109/OJCS.2023.3312371

Hankyul Baek;Rhoan Lee;Soyi Jung;Joongheon Kim;Soohyun Park

引用次数: 0

MetaCIDS: Privacy-Preserving Collaborative Intrusion Detection for Metaverse based on Blockchain and Online Federated Learning MetaCIDS:基于区块链和在线联合学习的Metaverse隐私保护协同入侵检测

IEEE Open Journal of the Computer Society Pub Date : 2023-09-05 DOI: 10.1109/OJCS.2023.3312299

Vu Tuan Truong;Long Bao Le

{"title":"MetaCIDS: Privacy-Preserving Collaborative Intrusion Detection for Metaverse based on Blockchain and Online Federated Learning","authors":"Vu Tuan Truong;Long Bao Le","doi":"10.1109/OJCS.2023.3312299","DOIUrl":"https://doi.org/10.1109/OJCS.2023.3312299","url":null,"abstract":"Metaverse is expected to rely on massive Internet of Things (IoT) connections so it inherits various security threats from the IoT network and also faces other sophisticated attacks related to virtual reality technology. As traditional security approaches show various limitations in the large-scale distributed metaverse, this paper proposes MetaCIDS, a novel collaborative intrusion detection (CID) framework that leverages metaverse devices to collaboratively protect the metaverse. In MetaCIDS, a federated learning (FL) scheme based on unsupervised autoencoder and an attention-based supervised classifier enables metaverse users to train a CID model using their local network data, while the blockchain network allows metaverse users to train a machine learning (ML) model to detect intrusion network flows over their monitored local network traffic, then submit verifiable intrusion alerts to the blockchain to earn metaverse tokens. Security analysis shows that MetaCIDS can efficiently detect zero-day attacks, while the training process is resistant to SPoF, data tampering, and up to 33% poisoning nodes. Performance evaluation illustrates the efficiency of MetaCIDS with 96% to 99% detection accuracy on four different network intrusion datasets, supporting both multi-class detection using labeled data and anomaly detection trained on unlabeled data.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"4 ","pages":"253-266"},"PeriodicalIF":0.0,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8782664/10016900/10239541.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67880865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Co-Existence With IEEE 802.11 Networks in the ISM Band Without Channel Estimation 在没有信道估计的ISM频带中与IEEE 802.11网络共存

IEEE Open Journal of the Computer Society Pub Date : 2023-08-31 DOI: 10.1109/OJCS.2023.3310913

Muhammad Naveed Aman;Muhammad Ishfaq;Biplab Sikdar

{"title":"Co-Existence With IEEE 802.11 Networks in the ISM Band Without Channel Estimation","authors":"Muhammad Naveed Aman;Muhammad Ishfaq;Biplab Sikdar","doi":"10.1109/OJCS.2023.3310913","DOIUrl":"https://doi.org/10.1109/OJCS.2023.3310913","url":null,"abstract":"Any new deployment of networks in the industrial, scientific, and medical (ISM) band, even though it is license-free, has to co-exist with IEEE 802.11 networks. IoT devices are typically deployed in the ISM band, creating a spectrum bottleneck for competing networks. This article investigates the issue of co-existence of wireless networks with WiFi networks. In our scenario, we consider WiFi as the “primary” or higher priority network co-existing with multiple “secondary” networks that may be used for low priority devices, with both networks operating in the ISM band. Towards this end, we first develop an analytical model for a metric called the “received symbol distance” at the primary receiver to obtain a power control parameter for secondary users. This power control parameter is used to scale the power of the secondary user according to the wireless channel between the primary transmitter and primary receiver. The proposed approach is computationally simple and does not require any estimation of channel coefficients. Simulation results show that the proposed technique can be used to effectively increase the spectrum utilization and the probability of a successful transmission by the secondary user, while not having any harmful effect on the primary user.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"4 ","pages":"267-279"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8782664/10016900/10236489.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67880866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Identity-Based Adaptor Signature Scheme and its Applications in the Blockchain System 一种基于身份的适配器签名方案及其在区块链系统中的应用

IEEE Open Journal of the Computer Society Pub Date : 2023-08-29 DOI: 10.1109/OJCS.2023.3309836

Zijian Bao;Debiao He;Cong Peng;Min Luo;Kim-Kwang Raymond Choo

{"title":"An Identity-Based Adaptor Signature Scheme and its Applications in the Blockchain System","authors":"Zijian Bao;Debiao He;Cong Peng;Min Luo;Kim-Kwang Raymond Choo","doi":"10.1109/OJCS.2023.3309836","DOIUrl":"https://doi.org/10.1109/OJCS.2023.3309836","url":null,"abstract":"Adaptor signature, as a new emerging cryptographic primitive, has become one promising method to mitigate the \u0000<italic>scalability</i>\u0000 issue on blockchain. It can transform an incomplete signature into a complete signature by revealing the witness of a pre-set hard relation, which can be applied to atomic swap, payment channel, payment hub, and other blockchain scenarios. Recently, a general transformation for constructing adaptor signatures has been proposed for some signature schemes with specific structures, e.g., Schnorr, ECDSA, SM2 signatures. However, we note that there is no identity-based adaptor signature method so far. In this article, we put forward an adaptor signature scheme for the identity-based signature scheme in the IEEE P1363 standard. Then, we formally prove the security of our scheme under the random oracle model. We also present the computation and communication costs, compared with other adaptor signatures. Finally, we show our scheme's potential use in atomic swaps and payment channel networks of blockchain.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"4 ","pages":"231-242"},"PeriodicalIF":0.0,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8782664/10016900/10234020.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67880873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Survey on ChatGPT: AI–Generated Contents, Challenges, and Solutions ChatGPT调查：人工智能生成的内容、挑战和解决方案

IEEE Open Journal of the Computer Society Pub Date : 2023-08-16 DOI: 10.1109/OJCS.2023.3300321

Yuntao Wang;Yanghe Pan;Miao Yan;Zhou Su;Tom H. Luan

{"title":"A Survey on ChatGPT: AI–Generated Contents, Challenges, and Solutions","authors":"Yuntao Wang;Yanghe Pan;Miao Yan;Zhou Su;Tom H. Luan","doi":"10.1109/OJCS.2023.3300321","DOIUrl":"https://doi.org/10.1109/OJCS.2023.3300321","url":null,"abstract":"With the widespread use of large artificial intelligence (AI) models such as ChatGPT, AI-generated content (AIGC) has garnered increasing attention and is leading a paradigm shift in content creation and knowledge representation. AIGC uses generative large AI algorithms to assist or replace humans in creating massive, high-quality, and human-like content at a faster pace and lower cost, based on user-provided prompts. Despite the recent significant progress in AIGC, security, privacy, ethical, and legal challenges still need to be addressed. This paper presents an in-depth survey of working principles, security and privacy threats, state-of-the-art solutions, and future challenges of the AIGC paradigm. Specifically, we first explore the enabling technologies, general architecture of AIGC, and discuss its working modes and key characteristics. Then, we investigate the taxonomy of security and privacy threats to AIGC and highlight the ethical and societal implications of GPT and AIGC technologies. Furthermore, we review the state-of-the-art AIGC watermarking approaches for regulatable AIGC paradigms regarding the AIGC model and its produced content. Finally, we identify future challenges and open research directions related to AIGC.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"4 ","pages":"280-302"},"PeriodicalIF":0.0,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8782664/10016900/10221755.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67880863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Twitter Bot Detection Using Neural Networks and Linguistic Embeddings 使用神经网络和语言嵌入的Twitter Bot检测

IEEE Open Journal of the Computer Society Pub Date : 2023-08-07 DOI: 10.1109/OJCS.2023.3302286

Feng Wei;Uyen Trang Nguyen

{"title":"Twitter Bot Detection Using Neural Networks and Linguistic Embeddings","authors":"Feng Wei;Uyen Trang Nguyen","doi":"10.1109/OJCS.2023.3302286","DOIUrl":"https://doi.org/10.1109/OJCS.2023.3302286","url":null,"abstract":"Twitter is a web application playing the dual role of online social networking and micro-blogging. The popularity and open structure of Twitter have attracted a large number of automated programs, known as bots. In this article, we propose a Twitter bot detection model using recurrent neural networks, specifically bidirectional lightweight gated recurrent unit (BiLGRU), and linguistic embeddings. To the best of our knowledge, our Twitter bot detection model is the first that does not require any handcrafted features, or prior knowledge or assumptions about account profiles, friendship networks or historical behavior. The proposed model uses only textual content of tweets and linguistic embeddings to classify bot and human accounts on Twitter. Experimental results show that the proposed model performs better or comparably to state-of-the-art Twitter bot detection models while requiring no feature engineering, making it faster and easier to train and deploy in a real network. We also present experimental results that show the performance and computational costs of different types of linguistic embeddings and recurrence network variants for the task of Twitter bot detection. The results will potentially help researchers design high-performance deep-learning models for similar tasks.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"4 ","pages":"218-230"},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8782664/10016900/10210119.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67880872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Practical Anti-Fuzzing Techniques With Performance Optimization 具有性能优化的实用反引信技术

IEEE Open Journal of the Computer Society Pub Date : 2023-08-04 DOI: 10.1109/OJCS.2023.3301883

Zhengxiang Zhou;Cong Wang

{"title":"Practical Anti-Fuzzing Techniques With Performance Optimization","authors":"Zhengxiang Zhou;Cong Wang","doi":"10.1109/OJCS.2023.3301883","DOIUrl":"https://doi.org/10.1109/OJCS.2023.3301883","url":null,"abstract":"Fuzzing, an automated software testing technique, has achieved remarkable success in recent years, aiding developers in identifying vulnerabilities. However, fuzzing can also be exploited by attackers to discover zero-day vulnerabilities. To counter this threat, researchers have proposed anti-fuzzing techniques, which aim to impede the fuzzing process by slowing the program down, providing misleading coverage feedback, and complicating data flow, etc. Unfortunately, current anti-fuzzing approaches primarily focus on enhancing defensive capabilities while underestimating the associated overhead and manual efforts required. In our paper, we present No-Fuzz, an efficient and practical anti-fuzzing technique. No-Fuzz stands out in binary-only fuzzing by accurately determining running environments, effectively reducing unnecessary fake block overhead, and replacing resource-intensive functions with lightweight arithmetic operations in anti-hybrid techniques. We have implemented a prototype of No-Fuzz and conducted evaluations to compare its performance against existing approaches. Our evaluations demonstrate that No-Fuzz introduces minimal performance overhead, accounting for less than 10% of the storage cost for a single fake block. Moreover, it achieves a significant 92.2% reduction in total storage costs compared to prior works for an equivalent number of branch reductions. By emphasizing practicality, our study sheds light on improving anti-fuzzing techniques for real-world deployment.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"4 ","pages":"206-217"},"PeriodicalIF":0.0,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8782664/10016900/10209185.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67880871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reverse Self-Distillation Overcoming the Self-Distillation Barrier 反自蒸馏克服自蒸馏障碍

IEEE Open Journal of the Computer Society Pub Date : 2023-06-21 DOI: 10.1109/OJCS.2023.3288227

Shuiping Ni;Xinliang Ma;Mingfu Zhu;Xingwang Li;Yu-Dong Zhang

引用次数: 0

IEEE Computer Society Information IEEE计算机学会信息

IEEE Open Journal of the Computer Society Pub Date : 2023-06-08 DOI: 10.1109/OJCS.2023.3243827

引用次数: 0

Disjunctive Threshold Networks for Tabular Data Classification 用于表格数据分类的虚拟阈值网络

IEEE Open Journal of the Computer Society Pub Date : 2023-06-05 DOI: 10.1109/OJCS.2023.3282948

Weijia Wang;Litao Qiao;Bill Lin

{"title":"Disjunctive Threshold Networks for Tabular Data Classification","authors":"Weijia Wang;Litao Qiao;Bill Lin","doi":"10.1109/OJCS.2023.3282948","DOIUrl":"https://doi.org/10.1109/OJCS.2023.3282948","url":null,"abstract":"While neural networks have been achieving increasingly significant excitement in solving classification tasks such as natural language processing, their lack of interpretability becomes a great challenge for neural networks to be deployed in certain high-stakes human-centered applications. To address this issue, we propose a new approach for generating interpretable predictions by inferring a simple three-layer neural network with threshold activations, so that it can benefit from effective neural network training algorithms and at the same time, produce human-understandable explanations for the results. In particular, the hidden layer neurons in the proposed model are trained with floating point weights and binary output activations. The output neuron is also trainable as a threshold logic function that implements a disjunctive operation, forming the logical-OR of the first-level threshold logic functions. This neural network can be trained using state-of-the-art training methods to achieve high prediction accuracy. An important feature of the proposed architecture is that only a simple greedy algorithm is required to provide an explanation with the prediction that is human-understandable. In comparison with other explainable decision models, our proposed approach achieves more accurate predictions on a broad set of tabular data classification datasets.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"4 ","pages":"185-194"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8782664/10016900/10144404.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67880869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1