SECURITY AND PRIVACY最新文献

PIoT‐fortifying IoT device identity and data access: A security framework empowered by blockchain PIoT 强化物联网设备身份和数据访问：区块链赋能的安全框架

SECURITY AND PRIVACY Pub Date : 2024-08-09 DOI: 10.1002/spy2.443

K. Janani, S. Ramamoorthy

{"title":"PIoT‐fortifying IoT device identity and data access: A security framework empowered by blockchain","authors":"K. Janani, S. Ramamoorthy","doi":"10.1002/spy2.443","DOIUrl":"https://doi.org/10.1002/spy2.443","url":null,"abstract":"The IoT, which refers to the process in which billions of devices are connected to the Internet, has emerged as an essential component of today's society. Yet, the safety of data exchange and the identification of devices in IoT networks have emerged as significant concerns in recent years. Also, there will be a significant drop in the effectiveness of the conventional consensus process. This study presents a novel consensus technique, Proof of IoT (PIoT), to address the security and authentication‐related issues in the IoT Infrastructure. It uses blockchain‐based smart contracts to securely transfer the data and uniquely identify the device on the IoT‐based network. PIoT uses a reputation assessment technique that involves complex cryptographic NuCypher‐based security computations to authenticate and update the data across IoT devices. This contract assures that only authorized parties can access the information recorded in the blockchain. A reward‐based filtering technique is developed for PIoT to identify malicious nodes with harmful actions, preventing them from contributing to consensus. Compared to specific conventional methods, PIoT performs better in simulations. Compared with LPBFT, DAC4SH Consensus, the Point of Interaction in blockchain‐based PIoT improved by 74.7% and 96.8%, respectively. When compared to DAC4SH, PIoT shows an overall 15% improvement in the security of the blockchain under the IoT. In addition to providing a secure method of communication between IoT devices, the given study also provides security against various IoT attacks.","PeriodicalId":506233,"journal":{"name":"SECURITY AND PRIVACY","volume":"47 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141924441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Kafka‐Shield: Kafka Streams‐based distributed detection scheme for IoT traffic‐based DDoS attacks Kafka-Shield：针对基于物联网流量的 DDoS 攻击的基于 Kafka 流的分布式检测方案

SECURITY AND PRIVACY Pub Date : 2024-05-21 DOI: 10.1002/spy2.416

Praveen Shukla, C. R. Krishna, N. Patil

{"title":"Kafka‐Shield: Kafka Streams‐based distributed detection scheme for IoT traffic‐based DDoS attacks","authors":"Praveen Shukla, C. R. Krishna, N. Patil","doi":"10.1002/spy2.416","DOIUrl":"https://doi.org/10.1002/spy2.416","url":null,"abstract":"With the rapid proliferation of insecure Internet of Things (IoT) devices, the security of Internet‐based applications and networks has become a prominent concern. One of the most significant security threats encountered in IoT environments is a Distributed Denial of Service (DDoS) attack. This attack can severely disrupt critical services and prevent smart devices from functioning normally, leading to severe consequences for businesses and individuals. It aims to overwhelm victims' resources, websites, and other services by flooding them with massive attack packets, making them inaccessible to legitimate users. Researchers have developed multiple detection schemes to detect DDoS attacks. As technology advances and other facilitating factors have increased, it is a challenge to identify such powerful attacks in real‐time. In this paper, we propose a novel distributed detection scheme for IoT network traffic‐based DDoS attacks by deploying it in a Kafka Streams processing framework named Kafka‐Shield. The Kafka‐Shield comprises two stages: design and deployment. Firstly, the detection scheme is designed on the Hadoop cluster employing a highly scalable H2O.ai machine learning platform. Secondly, a portable, scalable, and distributed detection scheme is deployed on the Kafka Streams processing framework. To analyze the incoming traffic data and categorize it into nine target classes in real time. Additionally, Kafka‐Shield stores each network flow with significant input features and the predicted outcome in the Hadoop Distributed File System (HDFS). It enables the development of new models or updating current ones. To validate the effectiveness of the Kafka‐Shield, we performed critical analysis using various configured attack scenarios. The experimental results affirm Kafka‐Shield's remarkable efficiency in detecting DDoS attacks. It has a detection rate of over 99% and can process 0.928 million traces in nearly 3.027 s.","PeriodicalId":506233,"journal":{"name":"SECURITY AND PRIVACY","volume":"34 31","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141117770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel Bayesian optimizable ensemble bagged trees model for cryptocurrency fraud prediction approach 用于加密货币欺诈预测方法的新型贝叶斯可优化集合袋装树模型

SECURITY AND PRIVACY Pub Date : 2024-05-19 DOI: 10.1002/spy2.417

Monire Norouzi

引用次数: 0

Malicious clouds coalition management for business processes deployment 针对业务流程部署的恶意云联盟管理

SECURITY AND PRIVACY Pub Date : 2024-03-25 DOI: 10.1002/spy2.395

Amina Ahmed Nacer, Mohammed Riyadh Abdmeziem, Asma Aid

引用次数: 0

Physical‐layer security enhancement in wireless sensor networks through artificial noise optimization 通过人工噪音优化增强无线传感器网络的物理层安全性

SECURITY AND PRIVACY Pub Date : 2024-03-24 DOI: 10.1002/spy2.385

A. Qasem, Mona Shokair, F. A. Abd El‑Samie

{"title":"Physical‐layer security enhancement in wireless sensor networks through artificial noise optimization","authors":"A. Qasem, Mona Shokair, F. A. Abd El‑Samie","doi":"10.1002/spy2.385","DOIUrl":"https://doi.org/10.1002/spy2.385","url":null,"abstract":"Ensuring network security is of utmost importance, especially in wireless sensor networks (WSNs), where the confidentiality of data is at risk due to eavesdropping. This paper introduces an artificial‐noise‐aided secure communication scheme for WSNs. This scheme comprises numerous sensor nodes, the sink, a friendly jammer, and an eavesdropper. The primary aim is to enhance the secrecy rate of the network by optimizing the jamming power. The friendly jammer plays a crucial role in degrading the wiretap channel between the sensor nodes and the eavesdropper. The optimization process revolves around maximizing the secrecy rate, while carefully managing the jamming power to prevent any negative impact on the main transmission link between the sink node and the sensor nodes. Due to the nonconvexity of the secrecy rate problem, the convex approximation‐based algorithm is recommened to get a safe convex approximation of the original solution. To address this optimization problem, an iterative algorithm based on quadratic transformation is proposed. Afterwards, the optimum jamming power to achieve high security is obtained. The simulation outcomes underscore the dual impact of the jammer in WSNs. The jammer diminishes the eavesdropper channel. Unfortunately, it introduces interference that consequently affects the security enhancement. In response, we concentrate on the optimization of jamming power. The proposed scheme consistently elevates secrecy rates across a spectrum of eavesdropper positions, adeptly addressing worst‐case scenarios. Notably, the algorithm showcases resilience across diverse node distributions.","PeriodicalId":506233,"journal":{"name":"SECURITY AND PRIVACY","volume":" 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140385403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cryptography algorithms for improving the security of cloud‐based internet of things 提高云端物联网安全性的加密算法

SECURITY AND PRIVACY Pub Date : 2024-03-04 DOI: 10.1002/spy2.378

Mohammed Ali Qasem, Fursan Thabit, Ozgu Can, Ebrahim Naji, Hoda AlKhzaimi, P. R. Patil, S. B. Thorat

{"title":"Cryptography algorithms for improving the security of cloud‐based internet of things","authors":"Mohammed Ali Qasem, Fursan Thabit, Ozgu Can, Ebrahim Naji, Hoda AlKhzaimi, P. R. Patil, S. B. Thorat","doi":"10.1002/spy2.378","DOIUrl":"https://doi.org/10.1002/spy2.378","url":null,"abstract":"In today's fast‐paced society, the Internet of Things (IoT) is revolutionizing businesses by bridging the gap between the digital and physical realms. This transformative technology enables rapid changes in the way people conduct business. Its fundamental aim is to connect everything in our world—objects, individuals, locations, and processes—under a unified infrastructure, providing valuable information and control over the state of our environment. The IoT represents a novel approach to developing diverse and distributed systems, which have now evolved into a pervasive computing cloud infrastructure. However, due to limitations in computing power and storage resources dedicated to handling the vast amounts of IoT data, a cloud‐based architecture is often employed in the IoT realm. Unfortunately, this shift has introduced a range of complex security and trust concerns within the cloud‐based IoT environment. As the demand for widespread deployment of cloud‐based IoT continues to soar, significant security‐related threats have emerged, prompting numerous researchers to develop cryptographic algorithms aimed at enhancing the security of both the Cloud and IoT. This paper provides an overview of cloud‐based IoT technology and seeks to fulfill the primary objective of conducting a survey on encryption algorithms in the context of the cloud and IoT. The research delves into the strategies, challenges, and variations associated with encryption in cloud and IoT systems. Additionally, this work includes a comparative analysis of the computational complexity of these techniques.","PeriodicalId":506233,"journal":{"name":"SECURITY AND PRIVACY","volume":"74 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140080219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A lightweight Intrusion Detection for Internet of Things‐based smart buildings 基于物联网的智能楼宇的轻量级入侵检测

SECURITY AND PRIVACY Pub Date : 2024-03-01 DOI: 10.1002/spy2.386

Amith Murthy, Muhammad Rizwan Asghar, Wanqing Tu

{"title":"A lightweight Intrusion Detection for Internet of Things‐based smart buildings","authors":"Amith Murthy, Muhammad Rizwan Asghar, Wanqing Tu","doi":"10.1002/spy2.386","DOIUrl":"https://doi.org/10.1002/spy2.386","url":null,"abstract":"The integration of Internet of Things (IoT) devices into commercial or industrial buildings to create smart environments, such as Smart Buildings (SBs), has enabled real‐time data collection and processing to effectively manage building operations. Due to poor security design and implementation in IoT devices, SB networks face an array of security challenges and threats (e.g., botnet malware) that leverage IoT devices to conduct Distributed Denial of Service (DDoS) attacks on the Internet infrastructure. Machine Learning (ML)‐based traffic classification systems aim to automatically detect such attacks by effectively differentiating attacks from benign traffic patterns in IoT networks. However, there is an inherent accuracy‐efficiency tradeoff in network traffic classification tasks. To balance this tradeoff, we develop an accurate yet lightweight device‐specific traffic classification model. This model classifies SB traffic flows into four types of coarse‐grained flows, based on the locations of traffic sources and the directions of traffic transmissions. Through these four types of coarse‐grained flows, the model can extract simple yet effective flow rate features to conduct learning and predictions. Our experiments find the model to achieve an overall accuracy of 96%, with only 32 features to be learned by the ML model.","PeriodicalId":506233,"journal":{"name":"SECURITY AND PRIVACY","volume":"39 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140082488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid KuFaI: A novel secure key generation algorithm using fast independent component analysis for physical layer security techniques 混合 KuFaI：利用快速独立分量分析的新型安全密钥生成算法，用于物理层安全技术

SECURITY AND PRIVACY Pub Date : 2024-02-22 DOI: 10.1002/spy2.381

Tapesh Sarsodia, Uma Rathore Bhatt, R. Upadhyay, Vijaylaxmi S. Bhat

引用次数: 0

A systematic survey on security and privacy issues of medicine supply chain: Taxonomy, framework, and research challenges 关于医药供应链安全和隐私问题的系统调查：分类、框架和研究挑战

SECURITY AND PRIVACY Pub Date : 2024-02-07 DOI: 10.1002/spy2.377

Jigna J. Hathaliya, S. Tanwar

{"title":"A systematic survey on security and privacy issues of medicine supply chain: Taxonomy, framework, and research challenges","authors":"Jigna J. Hathaliya, S. Tanwar","doi":"10.1002/spy2.377","DOIUrl":"https://doi.org/10.1002/spy2.377","url":null,"abstract":"Several decades ago, the medicine supply chain (MSC) transferred the medicines from the manufacturer to the end‐consumer and kept all records in a manual register. The manual intermediary management of MSC and medicine data often leads to issues like unauthorized third parties participating in the process and illegally tempering medicine data. As a result of this medicine temperament, end users get counterfeit medicine that poses severe consequences for patients' health. Over time, manual data management and intermediaries transform into digital platforms that track, manage, and exchange data in real‐time. Real‐time data exchange opens attackers up to target MSCs, access medicine data illegally, and modify medicine conditions, locations, and specifications. With the objective of this, the proposed survey identifies security and privacy issues and discusses security solutions. This security solution involves various data security and privacy frameworks such as micro‐segmentation, zero trust model, and many other software‐based security solutions. Moreover, The proposed survey explores radio frequency identification for medicine tracking in which each intermediary transforms the medicine location over the internet. In contrast, the Internet of Things is used to exchange medicine temperature conditions in real‐time. Furthermore, cybersecurity‐based solutions help protect against malicious threats, and blockchain keeps data private and temper‐proof. Artificial intelligence provides machine learning and deep learning models for analyzing large amounts of data to generate insights from the MSC data. Therefore, this survey addresses the various security and privacy issues and provides solutions that help researchers carry out work in this domain.","PeriodicalId":506233,"journal":{"name":"SECURITY AND PRIVACY","volume":"6 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139796002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Privacy preserving unique identity generation from multimodal biometric data for privacy and security applications 从多模态生物识别数据中生成保护隐私的唯一身份，用于隐私和安全应用

SECURITY AND PRIVACY Pub Date : 2024-02-07 DOI: 10.1002/spy2.375

Priyabrata Dash, M. Sarma, Debasis Samanta

引用次数: 0