Intelligent Intrusion Detection for Industrial Internet of Things Using Clustering Techniques

The rapid growth of the Internet of Things (IoT) in the industrial sector has given rise to a new term: the Industrial Internet of Things (IIoT). The IIoT is a collection of devices, apps, and services that connect physical and virtual worlds to create smart, cost-effective, and scalable systems. Although the IIoT has been implemented and incorporated into a wide range of industrial control systems, maintaining its security and privacy remains a significant concern. In the IIoT contexts, an intrusion detection system (IDS) can be an effective security solution for ensuring data confidentiality, integrity, and availability. In this paper, we propose an intelligent intrusion detection technique that uses principal components analysis (PCA) as a feature engineering method to choose the most significant features, minimize data dimensionality, and enhance detection performance. In the classification phase, we use clustering algorithms such as K-medoids and K-means to determine whether a given flow of IIoT traffic is normal or attack for binary classification and identify the group of cyberattacks according to its specific type for multi-class classification. To validate the effectiveness and robustness of our proposed model, we validate the detection method on a new driven IIoT dataset called X-IIoTID. The performance results showed our proposed detection model obtained a higher accuracy rate of 99.79% and reduced error rate of 0.21% when compared to existing techniques.     

物联网和服务架构的食品安全信息平台模型

针对食品供应链管理和质量安全的跟踪和追溯需求,利用物联网技术,参照EPC标准,提出了一种基于物联网和服务架构的食品安全信息平台模型,描述了RFID技术在Internet基础上实现食品的全程跟踪管理的E-R模型、网络架构、技术框架和功能模块,可通过Web Service和智能手机等多种方式查询追溯详细的电子信息.     

Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies

This paper presents a comprehensive review of emerging technologies for the internet of things(IoT)-based smart agriculture.We begin by summarizing the existing surveys and describing emergent technologies for the agricultural IoT,such as unmanned aerial vehicles,wireless technologies,open-source IoT platforms,software defined networking(SDN),network function virtualization(NFV)technologies,cloud/fog computing,and middleware platforms.We also provide a classification of IoT applications for smart agriculture into seven categories:including smart monitoring,smart water management,agrochemicals applications,disease management,smart harvesting,supply chain management,and smart agricultural practices.Moreover,we provide a taxonomy and a side-by-side comparison of the state-ofthe-art methods toward supply chain management based on the blockchain technology for agricultural IoTs.Furthermore,we present real projects that use most of the aforementioned technologies,which demonstrate their great performance in the field of smart agriculture.Finally,we highlight open research challenges and discuss possible future research directions for agricultural IoTs.     

物联网技术在军事领域中的应用

为了进一步满足当今信息化战争中高精确性、高可靠性和高实时性的战场信息需要,文中通过分析物联网的概念,研究了物联网的定义、本质和特征。阐述了物联网的基本构架,展望了物联网在军事领域的典型应用,最后提出了对于军队物联网建设的几点思考。     

物联网技术于人文艺术之应用

近年来,物联网(Internet of Things,IoT)产业受到许多的关注,世界各国均视其为潜在无限商机的高科技产业,并投入大量的资源从事研发与推广。由于物联网的应用非常广泛,且透过物联网技术人类得以提升生活质量,让生活更加便利,因此,本论文首先简介物联网的背景及应用,并介绍其基本概念与架构。接着,本论文以「无线感测真菌人文树道」为例,针对物联网技术应用于人文艺术领域进行说明,并详细叙述其所使用到之各项软件、韧体及硬件技术,透过真菌的感测、无线通信及异质网络连网功能的设计,使真菌网络成为物联网在人文艺术应用的一个重要典范。     

智能仓储物联网的设计与实现

物联网因其巨大应用前景受到各国政府和学术、工业界的重视,＂智能物流＂也被广泛关注。在对物联网概念、技术体系、网络结构、工作原理等研究的基础上,提出了一种基于物联网的高智能化物流仓储管理系统设计方案。重点分析了系统的总体架构、工作流程及功能模块,进而分析了系统物联网中的RFID系统、无线传感器监控网络和业务系统的实现方法。系统解决了传统仓储管理过程中物流信息处理效率低和出入库盘点不准确等问题,在出入库、监控、盘点、拣货等方面具有快速、便捷、准确、高效及高度自动化等优点,但在降低成本和提高安全性方面,还需进一步研究。     

A Methodology for Reliability of WSN Based on Software Defined Network in Adaptive Industrial Environment

As communication technology and smart manufacturing have developed, the industrial internet of things (IIoT) has gained considerable attention from academia and industry. Wireless sensor networks (WSNs) have many advantages with broad applications in many areas including environmental monitoring, which makes it a very important part of IIoT. However, energy depletion and hardware malfunctions can lead to node failures in WSNs. The industrial environment can also impact the wireless channel transmission, leading to network reliability problems, even with tightly coupled control and data planes in traditional networks, which obviously also enhances network management cost and complexity. In this paper, we introduce a new software defined network (SDN), and modify this network to propose a framework called the improved software defined wireless sensor network (improved SD-WSN). This proposed framework can address the following issues. 1) For a large scale heterogeneous network, it solves the problem of network management and smooth merging of a WSN into IIoT. 2) The network coverage problem is solved which improves the network reliability. 3) The framework addresses node failure due to various problems, particularly related to energy consumption. Therefore, it is necessary to improve the reliability of wireless sensor networks, by developing certain schemes to reduce energy consumption and the delay time of network nodes under IIoT conditions. Experiments have shown that the improved approach significantly reduces the energy consumption of nodes and the delay time, thus improving the reliability of WSN.      

Security challenges in internet of things: Distributed denial of service attack detection using support vector machine-based expert systems

The rapid development of internet of things (IoT) is to be the next generation of the IoT devices are a simple target for attackers due to the lack of security. Attackers can easily hack the IoT devices that can be used to form botnets, which can be used to launch distributed denial of service (DDoS) attack against networks. Botnets are the most dangerous threat to the security systems. Software-defined networking (SDN) is one of the developing filed, which introduce the capacity of dynamic program to the network. Use the flexibility and multidimensional characteristics of SDN used to prevent DDoS attacks. The DDoS attack is the major attack to the network, which makes the entire network down, so that normal users might not avail the services from the server. In this article, we proposed the DDoS attack detection model based on SDN environment by combining support vector machine classification algorithm is used to collect flow table values in sampling time periods. From the flow table values, the five-tuple characteristic values extracted and based on it the DDoS attack can be detected. Based on the experimental results, we found the average accuracy rate is 96.23% with a normal amount of traffic flow. Proposed research offers a better DDoS detection rate on SDN.     

Authentication of WSN for Secured Medical Data Transmission Using Diffie Hellman Algorithm

The applications of wireless sensor network (WSN) exhibits a significant rise in recent days since it is enveloped with various advantageous benefits. In the medical field, the emergence of WSN has created marvelous changes in monitoring the health conditions of the patients and so it is attracted by doctors and physicians. WSN assists in providing health care services without any delay and so it plays predominant role in saving the life of human. The data of different persons, time, places and networks have been linked with certain devices, which are collectively known as Internet of Things (IOT); it is regarded as the essential requirement of people in recent days. In the health care monitoring system, IOT plays a magnificent role, which has produced the real time monitoring of patient’s condition. However the medical data transmission is accomplished quickly with high security by the routing and key management. When the data from the digital record system (cloud) is accessed by the patients or doctors, the medical data is transferred quickly through WSN by performing routing. The Probabilistic Neural Network (PNN) is utilized, which authenticates the shortest path to reach the destination and its performance is identified by comparing it with the Dynamic Source Routing (DSR) protocol and Energy aware and Stable Routing (ESR) protocol. While performing routing, the secured transmission is achieved by key management, for which the Diffie Hellman key exchange is utilized, which performs encryption and decryption to secure the medical data. This enables the quick and secured transmission of data from source to destination with improved throughput and delivery ratio.     

射频识别与北斗卫星导航系统在物联网中的应用

物联网是上个世纪末提出的新概念,其发展历史比较短。本文是基于家电物联网项目的技术应用,以三洋荣 事达企业的实际物流配送为原型,将无线射频识别（RFID）技术以标签的形式用于对物品进行唯一标识,并采用帧时隙算法解 决RFID 系统中应答碰撞的问题,保证在读取RFID 标签发出的信号时做到既不丢失也不重复。将北斗卫星导航系统用在对 在途车辆及货物的跟踪定位上,降低货物丢失的风险,降低产品成本,提高企业利润。     

物联网WSS簇间节点安全链路模型

针对物联网无线服务系统通信中易遭受数据窃听、恶意行为攻击和用户平台隐私泄露问题,提出了一个基于可信第三方的簇间节点安全链路模型.该模型基于离散对数困难问题和双线性对映射建立节点可信匿名认证及簇形结构地址查询机制,利用杂凑函数和随机数生成的临时身份代替节点的真实身份以实现匿名性,将可信第三方嵌入认证机制以防止匿名认证机构与协调器共谋对用户平台实施Rudolph攻击,同时仅对控制中心授权的可信簇形结构提供查询服务.通过源簇形结构与链路中各节点的证书验证、密钥协商和填充机制实现数据的嵌套加解密及防流量分析服务,保证簇间节点数据传输安全.在此基础上,给出了链路模型的UC安全性证明.理论分析和实验结果表明:该模型在抑制数据窃听、流量分析和保护节点匿名性方面有明显优势.     

On the use of calibration sensors in source localization using TDOA and FDOA measurements

The accuracy of a source location estimate is very sensitive to the presence of the random noise in the known sensor positions. This paper investigates the use of calibration sensors, each of which is capable of broadcasting calibration signals to other sensors as well as receiving the signals from the source and other calibration sensors, to reduce the loss in the source localization accuracy due to uncertainties in sensor positions. We begin the study with deriving the Cramer–Rao lower bound (CRLB) for source localization using time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements when a single calibration sensor is available. The obtained CRLB result is then extended to the more general case with multiple calibration sensors. The performance improvement due to the use of calibration sensors is established analytically. We then propose a closed-form algorithm that can explore efficiently the calibration sensors to improve the source localization accuracy when the sensor positions are subject to random errors. We prove analytically that the newly developed localization method attains the CRLB accuracy under some mild approximations. Simulations verify the theoretical developments.     

基于区块链的物联网数据服务信誉评估模型

地质大数据共享与应用平台、专业移动大数据服务平台等现有集中式物联网数据服务平台多数存在缺乏信誉评估体系、用户隐私泄露、数据防篡改能力弱等安全性问题。为使用户能从海量物联网数据中精准快速地检索出高质量数据,设计并实现基于区块链的数据服务信誉评估模型。利用层次分析法进行信誉评估指标权重计算,采用智能合约和星际文件系统实现物联网数据的存储、验证、保护和共享,通过区块链和Redis缓存技术完成物联网数据和信誉数据的安全快速存取,同时使用环签名技术保证评价真实性并隐藏用户个人信息。测试结果表明,该模型具有去中心化、可信、安全高效和不可篡改的特性,能够满足物联网数据服务平台的信誉评估需求。