High-Confidence Computing最新文献_第3页

Federated data acquisition market: Architecture and a mean-field based data pricing strategy 联合数据采集市场：架构和基于均值场的数据定价策略

IF 3.2

High-Confidence Computing Pub Date : 2024-04-22 DOI: 10.1016/j.hcc.2024.100232

Jiejun Hu-Bolz , Martin Reed , Kai Zhang , Zelei Liu , Juncheng Hu

{"title":"Federated data acquisition market: Architecture and a mean-field based data pricing strategy","authors":"Jiejun Hu-Bolz , Martin Reed , Kai Zhang , Zelei Liu , Juncheng Hu","doi":"10.1016/j.hcc.2024.100232","DOIUrl":"10.1016/j.hcc.2024.100232","url":null,"abstract":"<div><div>With the increasing global mobile data traffic and daily user engagement, technologies, such as mobile crowdsensing, benefit hugely from the constant data flows from smartphone and IoT owners. However, the device users, as data owners, urgently require a secure and fair marketplace to negotiate with the data consumers. In this paper, we introduce a novel federated data acquisition market that consists of a group of local data aggregators (LDAs); a number of data owners; and, one data union to coordinate the data trade with the data consumers. Data consumers offer each data owner an individual price to stimulate participation. The mobile data owners naturally cooperate to gossip about individual prices with each other, which also leads to price fluctuation. It is challenging to analyse the interactions among the data owners and the data consumers using traditional game theory due to the complex price dynamics in a large-scale heterogeneous data acquisition scenario. Hence, we propose a data pricing strategy based on mean-field game (MFG) theory to model the data owners’ cost considering the price dynamics. We then investigate the interactions among the LDAs by using the distribution of price, namely the mean-field term. A numerical method is used to solve the proposed pricing strategy. The evaluations demonstrate that the proposed pricing strategy efficiently allows the data owners from multiple LDAs to reach an equilibrium on data quantity to sell regarding the current individual price scheme. The result further demonstrates that the influential LDAs determine the final price distribution. Last but not least, it shows that cooperation among mobile data owners leads to optimal social welfare even with the additional cost of information exchange.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"5 1","pages":"Article 100232"},"PeriodicalIF":3.2,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140768406","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

Modular neural network for edge-based detection of early-stage IoT botnet 基于边缘检测早期物联网僵尸网络的模块化神经网络

IF 3.2

High-Confidence Computing Pub Date : 2024-04-16 DOI: 10.1016/j.hcc.2024.100230

Duaa Alqattan , Varun Ojha , Fawzy Habib , Ayman Noor , Graham Morgan , Rajiv Ranjan

{"title":"Modular neural network for edge-based detection of early-stage IoT botnet","authors":"Duaa Alqattan , Varun Ojha , Fawzy Habib , Ayman Noor , Graham Morgan , Rajiv Ranjan","doi":"10.1016/j.hcc.2024.100230","DOIUrl":"10.1016/j.hcc.2024.100230","url":null,"abstract":"<div><div>The Internet of Things (IoT) has led to rapid growth in smart cities. However, IoT botnet-based attacks against smart city systems are becoming more prevalent. Detection methods for IoT botnet-based attacks have been the subject of extensive research, but the identification of early-stage behaviour of the IoT botnet prior to any attack remains a largely unexplored area that could prevent any attack before it is launched. Few studies have addressed the early stages of IoT botnet detection using monolithic deep learning algorithms that could require more time for training and detection. We, however, propose an edge-based deep learning system for the detection of the early stages of IoT botnets in smart cities. The proposed system, which we call EDIT (<u>E</u>dge-based <u>D</u>etection of early-stage <u>I</u>oT Botne<u>t</u>), aims to detect abnormalities in network communication traffic caused by early-stage IoT botnets based on the modular neural network (MNN) method at multi-access edge computing (MEC) servers. MNN can improve detection accuracy and efficiency by leveraging parallel computing on MEC. According to the findings, EDIT has a lower false-negative rate compared to a monolithic approach and other studies. At the MEC server, EDIT takes as little as 16 ms for the detection of an IoT botnet.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"5 1","pages":"Article 100230"},"PeriodicalIF":3.2,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140778543","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

Unsupervised machine learning approach for tailoring educational content to individual student weaknesses 无监督机器学习法，针对学生个体弱点定制教育内容

IF 3.2

High-Confidence Computing Pub Date : 2024-04-16 DOI: 10.1016/j.hcc.2024.100228

{"title":"Unsupervised machine learning approach for tailoring educational content to individual student weaknesses","authors":"","doi":"10.1016/j.hcc.2024.100228","DOIUrl":"10.1016/j.hcc.2024.100228","url":null,"abstract":"<div><div>By analyzing data gathered through Online Learning (OL) systems, data mining can be used to unearth hidden relationships between topics and trends in student performance. Here, in this paper, we show how data mining techniques such as clustering and association rule algorithms can be used on historical data to develop a unique recommendation system module. In our implementation, we utilize historical data to generate association rules specifically for student test marks below a threshold of 60%. By focusing on marks below this threshold, we aim to identify and establish associations based on the patterns of weakness observed in the past data. Additionally, we leverage K-means clustering to provide instructors with visual representations of the generated associations. This strategy aids instructors in better comprehending the information and associations produced by the algorithms. K-means clustering helps visualize and organize the data in a way that makes it easier for instructors to analyze and gain insights, enabling them to support the verification of the relationship between topics. This can be a useful tool to deliver better feedback to students as well as provide better insights to instructors when developing their pedagogy. This paper further shows a prototype implementation of the above-mentioned concepts to gain opinions and insights about the usability and viability of the proposed system.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 4","pages":"Article 100228"},"PeriodicalIF":3.2,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140782041","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

EPri-MDAS: An efficient privacy-preserving multiple data aggregation scheme without trusted authority for fog-based smart grid EPri-MDAS：基于雾的智能电网的高效隐私保护多数据聚合方案（无需可信机构

IF 3.2

High-Confidence Computing Pub Date : 2024-04-15 DOI: 10.1016/j.hcc.2024.100226

{"title":"EPri-MDAS: An efficient privacy-preserving multiple data aggregation scheme without trusted authority for fog-based smart grid","authors":"","doi":"10.1016/j.hcc.2024.100226","DOIUrl":"10.1016/j.hcc.2024.100226","url":null,"abstract":"<div><div>With the increasingly pervasive deployment of fog servers, fog computing extends data processing and analysis to network edges. At the same time, as the next-generation power grid, the smart grid should meet the requirements of security, efficiency, and real-time monitoring of user energy consumption. By utilizing the low-latency and distributed properties of fog computing, it can improve communication efficiency and user service satisfaction in smart grids. For the sake of providing adequate functionality for the power grid, various schemes have been proposed. Whereas, many methods are vulnerable to privacy leakage since the existence of trusted authority may increase the exposure to threats. In this paper, we propose the EPri-MDAS: an <em>E</em>fficient <em>Pri</em>vacy-preserving <em>M</em>ultiple <em>D</em>ata <em>A</em>ggregation <em>S</em>cheme without trusted authority based on the ElGamal homomorphic cryptosystem, which achieves both data integrity verification and data source authentication with the most efficient block cipher-based authenticated encryption algorithm. It performs well in energy efficiency with strong security. Especially, the proposed multidimensional aggregation statistics scheme can perform the fine-grained data analyses; it also allows for fault tolerance while protecting personal privacy. The security analysis and simulation experiments show that EPri-MDAS can satisfy the security requirements and work efficiently in the smart grid.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 4","pages":"Article 100226"},"PeriodicalIF":3.2,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140782430","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

Optimal filter assignment policy against link flooding attack 针对链路泛洪攻击的最佳滤波器分配策略

IF 3.2

High-Confidence Computing Pub Date : 2024-04-15 DOI: 10.1016/j.hcc.2024.100231

Rajorshi Biswas , Jie Wu , Wei Chang , Pouya Ostovari

{"title":"Optimal filter assignment policy against link flooding attack","authors":"Rajorshi Biswas , Jie Wu , Wei Chang , Pouya Ostovari","doi":"10.1016/j.hcc.2024.100231","DOIUrl":"10.1016/j.hcc.2024.100231","url":null,"abstract":"<div><div>A Link Flooding Attack (LFA) is a special type of Denial-of-Service (DoS) attack in which the attacker sends out a huge number of requests to exhaust the capacity of a link on the path the traffic comes to a server. As a result, user traffic cannot reach the server. As a result, DoS and degradation of Quality-of-Service (QoS) occur. Because the attack traffic does not go to the victim, protecting the legitimate traffic alone is hard for the victim. The victim can protect its legitimate traffic by using a special type of router called filter router (FR). An FR can receive server filters and apply them to block a link incident to it. An FR probabilistically appends its own IP address to packets it forwards, and the victim uses that information to discover the traffic topology. By analyzing traffic rates and paths, the victim identifies some links that may be congested. The victim needs to select some of these possible congested links (PCLs) and send a filter to the corresponding FR so that legitimate traffic avoids congested paths. In this paper, we formulate two optimization problems for blocking the least number of PCLs so that the legitimate traffic goes through a non-congested path. We consider the scenario where every user has at least one non-congested shortest path in the first problem. We extend the first problem to a scenario where there are some users whose shortest paths are all congested. We transform the original problem to the vertex separation problem to find the links to block. We use a custom-built Java multi-threaded simulator and conduct extensive simulations to support our solutions.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"5 1","pages":"Article 100231"},"PeriodicalIF":3.2,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140783141","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 attribute-based access control scheme using blockchain technology for IoT data protection 利用区块链技术保护物联网数据的基于属性的访问控制方案

IF 3.2

High-Confidence Computing Pub Date : 2024-04-09 DOI: 10.1016/j.hcc.2024.100199

{"title":"An attribute-based access control scheme using blockchain technology for IoT data protection","authors":"","doi":"10.1016/j.hcc.2024.100199","DOIUrl":"10.1016/j.hcc.2024.100199","url":null,"abstract":"<div><p>With the wide application of the Internet of Things (IoT), storing large amounts of IoT data and protecting data privacy has become a meaningful issue. In general, the access control mechanism is used to prevent illegal users from accessing private data. However, traditional data access control schemes face some non-ignorable problems, such as only supporting coarse-grained access control, the risk of centralization, and high trust issues. In this paper, an attribute-based data access control scheme using blockchain technology is proposed. To address these problems, attribute-based encryption (ABE) has become a promising solution for encrypted data access control. Firstly, we utilize blockchain technology to construct a decentralized access control scheme, which can grant data access with transparency and traceability. Furthermore, our scheme also guarantees the privacy of policies and attributes on the blockchain network. Secondly, we optimize an ABE scheme, which makes the size of system parameters smaller and improves the efficiency of algorithms. These optimizations enable our proposed scheme supports large attribute universe requirements in IoT environments. Thirdly, to prohibit attribute impersonation and attribute replay attacks, we design a challenge-response mechanism to verify the ownership of attributes. Finally, we evaluate the security and performance of the scheme. And comparisons with other related schemes show the advantages of our proposed scheme. Compared to existing schemes, our scheme has more comprehensive advantages, such as supporting a large universe, full security, expressive policy, and policy hiding.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 3","pages":"Article 100199"},"PeriodicalIF":3.2,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295224000023/pdfft?md5=94aae462b2facd3898d43562d260127f&pid=1-s2.0-S2667295224000023-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140790567","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

Intelligent edge CDN with smart contract-aided local IoT sharing 利用智能合约辅助本地物联网共享的智能边缘 CDN

IF 3.2

High-Confidence Computing Pub Date : 2024-04-04 DOI: 10.1016/j.hcc.2024.100225

{"title":"Intelligent edge CDN with smart contract-aided local IoT sharing","authors":"","doi":"10.1016/j.hcc.2024.100225","DOIUrl":"10.1016/j.hcc.2024.100225","url":null,"abstract":"<div><div>A content delivery network (CDN) aims to reduce the content delivery latency to end-users by using distributed cache servers. Nevertheless, deploying and maintaining cache servers on a large scale is very expensive. To solve this problem, CDN providers have developed a new content delivery strategy: allowing end-users’s IoT edge devices to share their storage/bandwidth resources. This new edge CDN platform must address two core questions: (1) how can we incentivize end users to share IoT devices? (2) how can we facilitate a safe and transparent content transaction environment for end users? This paper introduces SmartSharing, a new content delivery network solution to address these questions. In smartSharing, the over-the-top (OTT) IoT devices belonging to end-users are used as mini-cache servers. To motivate end users to share the idle devices and storage/bandwidth resources, SmartSharing designs the content delivery schedule and the pricing scheme based on game theory and machine learning algorithms (specifically, a tailored expectation-maximization (EM) algorithm). To facilitate content trading among end users, SmartSharing creates a secure and transparent transaction platform based on smart contracts in Ethereum. In addition, SmartSharing’s performance evaluation is through trace-driven simulations in the real world and a prototype using content metadata and the achieved pricing schemes. The evaluation results show that CDN providers, end users and content providers can all benefit from our SmartSharing framework.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 4","pages":"Article 100225"},"PeriodicalIF":3.2,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140771215","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

Aquilo: Temperature-aware scheduler for millimeter-wave devices and networks Aquilo：毫米波设备和网络的温度感知调度器

IF 3.2

High-Confidence Computing Pub Date : 2024-03-27 DOI: 10.1016/j.hcc.2024.100223

{"title":"Aquilo: Temperature-aware scheduler for millimeter-wave devices and networks","authors":"","doi":"10.1016/j.hcc.2024.100223","DOIUrl":"10.1016/j.hcc.2024.100223","url":null,"abstract":"<div><div>Millimeter-wave is the core technology to enable multi-Gbps throughput and ultra-low latency connectivity. But the devices need to operate at very high frequency and ultra-wide bandwidth: They consume more energy, dissipate more power, and subsequently heat up faster. Device overheating is a common concern of many users, and millimeter-wave would exacerbate the problem. In this work, we first thermally characterize millimeter-wave devices. Our measurements reveal that after only 10 s of data transfer at 1.9 Gbps bit-rate, the millimeter-wave antenna temperature reaches 68°C; it reduces the link throughput by 21%, increases the standard deviation of throughput by 6<span><math><mo>×</mo></math></span>, and takes 130 s to dissipate the heat completely. Besides degrading the user experience, exposure to high device temperature also creates discomfort. Based on the measurement insights, we propose <em>Aquilo</em>, a temperature-aware, multi-antenna network scheduler. It maintains relatively high throughput performance but cools down the devices substantially. Our testbed experiments under both static and mobile conditions demonstrate that <em>Aquilo</em> achieves a median peak temperature only 0.5°C to 2°C above the optimal while sacrificing less than 10% of throughput.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 4","pages":"Article 100223"},"PeriodicalIF":3.2,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140404908","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

Device authentication for 5G terminals via Radio Frequency fingerprints 通过射频指纹对 5G 终端进行设备验证

IF 3.2

High-Confidence Computing Pub Date : 2024-03-26 DOI: 10.1016/j.hcc.2024.100222

{"title":"Device authentication for 5G terminals via Radio Frequency fingerprints","authors":"","doi":"10.1016/j.hcc.2024.100222","DOIUrl":"10.1016/j.hcc.2024.100222","url":null,"abstract":"<div><div>The development of wireless communication network technology has provided people with diversified and convenient services. However, with the expansion of network scale and the increase in the number of devices, malicious attacks on wireless communication are becoming increasingly prevalent, causing significant losses. Currently, wireless communication systems authenticate identities through certain data identifiers. However, this software-based data information can be forged or replicated. This article proposes the authentication of device identity using the hardware fingerprint of the terminal’s Radio Frequency (RF) components, which possesses properties of being genuine, unique, and stable, holding significant implications for wireless communication security. Through the collection and processing of raw data, extraction of various features including time-domain and frequency-domain features, and utilizing machine learning algorithms for training and constructing a legal fingerprint database, it is possible to achieve close to a 97% recognition accuracy for Fifth Generation (5G) terminals of the same model. This provides an additional and robust hardware-based security layer for 5G communication security, enhancing monitoring capability and reliability.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 4","pages":"Article 100222"},"PeriodicalIF":3.2,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140404945","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

Graph isomorphism—Characterization and efficient algorithms 图同构--特征和高效算法

IF 3.2

High-Confidence Computing Pub Date : 2024-03-26 DOI: 10.1016/j.hcc.2024.100224

引用次数: 0