A Dual-Chaining Watermark Scheme for Data Integrity Protection in Internet of Things

Chaining watermark is an effective way to verify the integrity of streaming data in wireless network environment, especially in resource-constrained sensor networks, such as the perception layer of Internet of Things applications. However, in all existing single chaining watermark schemes, how to ensure the synchronization between the data sender and the receiver is still an unsolved problem. Once the synchronization points are attacked by the adversary, existing data integrity authentication schemes are difficult to work properly, and the false negative rate might be up to 50 percent. And the additional fixed group delimiters not only increase the data size, but are also easily detected by adversaries. In this paper, we propose an effective dual-chaining watermark scheme, called DCW, for data integrity protection in smart campus IoT applications. The proposed DCW scheme has the following three characteristics: (1) In order to authenticate the integrity of the data, fragile watermarks are generated and embedded into the data in a chaining way using dynamic grouping; (2) Instead of additional fixed group delimiters, chained watermark delimiters are proposed to synchronize the both transmission sides in case of the synchronization points are tampered; (3) To achieve lossless integrity authentication, a reversible watermarking technique is applied. The experimental results and security analysis can prove that the proposed DCW scheme is able to effectively authenticate the integrity of the data with free distortion at low cost in our smart meteorological Internet of Things system.     

Smart Security Framework for Educational Institutions Using Internet of Things (IoT)

Educational institutions are soft targets for the terrorist with massive and defenseless people. In the recent past, numbers of such attacks have been executed around the world. Conducting research, in order to provide a secure environment to the educational institutions is a challenging task. This effort is motivated by recent assaults, made at Army Public School Peshawar, following another attack at Charsada University, Khyber Pukhtun Khwa, Pakistan and also the Santa Fe High School Texas, USA massacre. This study uses the basic technologies of edge computing, cloud computing and IoT to design a smart emergency alarm system framework. IoT is engaged in developing this world smarter, can contribute significantly to design the Smart Security Framework (SSF) for educational institutions. In the emergency situation, all the command and control centres must be informed within seconds to halt or minimize the loss. In this article, the SSF is proposed. This framework works on three layers. The first layer is the sensors and smart devices layer. All these sensors and smart devices are connected to the Emergency Control Room (ECR), which is the second layer of the proposed framework. The second layer uses edge computing technologies to process massive data and information locally. The third layer uses cloud computing techniques to transmit and process data and information to different command and control centres. The proposed system was tested on Cisco Packet Tracer 7. The result shows that this approach can play an efficient role in security alert, not only in the educational institutions but also in other organizations too.     

物联网时代下减少二次包装的新思考

目的研究商品在包装功能发生改变时如何尽量减少二次包装给资源和环境造成的浪费和污染。方法结合目前市场上的商品包装形式,探析在物联网时代背景下的商品包装,明确研究的目的与意义。结论物流功能方面尝试减少物流过程中的二次包装,减少包装材料的浪费和二次污染;市场需求方面包装设计为了满足物流需要应在包装纹饰上简约、明了,这有利于节约成本。物联网时代包装的发展出现了信息化和互动性的新趋向,信息化体现在能够准确查询物品的位置信息、物品安全、物品送达以及库存信息;互动性体现在包装设计中应充分考虑包装的信息功能,从消费者的角度出发,通过利用物联网技术融入互动性的元素,寻求商品与消费者之间的情感交流。     

Smart-City-based Data Fusion Algorithm for Internet of Things

Increasingly, Wireless Sensor Networks (WSNs) are contributing enormous amounts of data. Since the recent deployments of wireless sensor networks in Smart City infrastructures, significant volumes of data have been produced every day in several domains ranging from the environment to the healthcare system to transportation. Using wireless sensor nodes, a Smart City environment may now be shown for the benefit of residents. The Smart City delivers intelligent infrastructure and a stimulating environment to citizens of the Smart Society, including the elderly and others. Weak, Quality of Service (QoS) and poor data performance are common problems in WSNs, caused by the data fusion method, where a small amount of bad data can significantly impact the total fusion outcome. In our proposed research, a WSN multi-sensor data fusion technique employing fuzzy logic for event detection. Using the new proposed Algorithm, sensor nodes will collect less repeated data, and redundant data will be used to increase the data's overall reliability. The network's fusion delay problem is investigated, and a minimum fusion delay approach is provided based on the nodes’ fusion waiting time. The proposed algorithm performs well in fusion, according to the results of the experiment. As a result of these discoveries, It is concluded that the algorithm describe here is effective and dependable instrument with a wide range of applications.     

Mitigating and Monitoring Smart City Using Internet of Things

The present trends in smart world reflects the extensive use of limited resources through information and communication technology. The limited resources like space, mobility, energy, etc., have been consumed rigorously towards creating optimized but smart instances. Thus, a new concept of IoT integrated smart city vision is yet to be proposed which includes a combination of systems like noise and air loss monitoring, web monitoring and fire detection systems, smart waste bin systems, etc., that have not been clearly addressed in the previous researches. This paper focuses on developing an effective system for possible monitoring of losses, traffic management, thus innovating smart city at large with digitalized and integrated systems and software for fast and effective implementations. In our proposed system, a real time data analysis is performed. These data are collected by various sensors to analyze different factors that are responsible for such losses. The proposed work is validated on a real case study.     

泛在电力物联网研究现状分析

泛在电力物联网的建设主要是将信息化和人工智能等新技术、新理念应用于企业发展进程中,以提高电力企业的技术水平,同时这也是服务于国家战略需要,符合推动互联网、大数据、人工智能和制造业深度融合的战略要求,其对推动我国的科技进步、产业升级和提高人民生活水平具有重要意义。对泛在电力物联网的提出背景、建设目标和意义等进行介绍;讨论各界对泛在电力物联网的态度和相应措施;对泛在电力物联网建设的技术支持进行分析;举例说明泛在电力物联网在当下的典型应用;最后指出泛在电力物联网发展过程中可能遇到的问题。     

A Formal Testing Model for Operating Room Control System Using Internet of Things

Technological advances in recent years have significantly changed the way an operating room works. This work aims to create a platform to solve the problems of operating room occupancy and prepare the rooms with an environment that is favorable for all operations. Using this system, a doctor can control all operation rooms, especially before an operation, and monitor their temperature and humidity to prepare for the operation. Also, in the event of a problem, an alert is sent to the nurse responsible for the room and medical stuff so that the problem can be resolved. The platform is tested using a Raspberry PI card and sensors. The sensors are connected to a cloud layer that collects and analyzes the temperature and humidity values obtained from the environment during an operation. The result of experimentations is visualized through a web application and an Android application. The platform also considers the security aspects such as authorization to access application functionalities for the Web and the mobile applications. We can also test and evaluate the system’s existing problems and vulnerabilities using the IEEE and owasp IoT standards. Finally, the proposed framework is extended with a model based testing technique that may be adopted for validating thesecurity aspects.     

一种高精度的荧光单分子纳米级定位算法

荧光成像系统的技术指标、采集的荧光图像信噪比和单分子定位算法是影响单分子定位精度的3大因素.在介绍单分子定位的基本极限精度和理论计算精度的基础上,提出了一种被称为图像去噪高斯掩膜算法的单分子定位算法.依据实验用单分子成像系统的具体配置,通过计算机仿真表明,该算法良好的去噪处理和高斯加权质心运算方式,不仅能实现纳米级的定位精度,而且能突破一般理论计算精度的限制,接近基本极限精度,特别是在背景噪声较大的情况下,其优势更加明显.这对单分子的精确定位和跟踪、扩散方式分析、转移速率计算等具有重要的意义.     

QoS-Aware and Resource-Efficient Dynamic Slicing Mechanism for Internet of Things

With the popularization of terminal devices and services in Internet of things (IoT), it will be a challenge to design a network resource allocation method meeting various QoS requirements and effectively using substrate resources. In this paper, a dynamic network slicing mechanism including virtual network (VN) mapping and VN reconfiguration is proposed to provide network slices for services. Firstly, a service priority model is defined to create queue for resource allocation. Then a slice including Virtual Network Function (VNF) placement and routing with optimal cost is generated by VN mapping. Next, considering temporal variations of service resource requirements, the size of network slice is adjusted dynamically to guarantee resource utilization in VN reconfiguration. Additionally, load balancing factors are designed to make traffic balanced. Simulation results show that dynamic slicing mechanism not only saves 22% and 31% cost than static slicing mechanism with extending shortest path (SS_ESP) and dynamic slicing mechanism with embedding single path (DS_ESP), but also maintains high service acceptance rate.     

LOA-RPL: Novel Energy-Efficient Routing Protocol for the Internet of Things Using Lion Optimization Algorithm to Maximize Network Lifetime

Energy conservation is a significant task in the Internet of Things (IoT) because IoT involves highly resource-constrained devices. Clustering is an effective technique for saving energy by reducing duplicate data. In a clustering protocol, the selection of a cluster head (CH) plays a key role in prolonging the lifetime of a network. However, most cluster-based protocols, including routing protocols for low-power and lossy networks (RPLs), have used fuzzy logic and probabilistic approaches to select the CH node. Consequently, early battery depletion is produced near the sink. To overcome this issue, a lion optimization algorithm (LOA) for selecting CH in RPL is proposed in this study. LOA-RPL comprises three processes: cluster formation, CH selection, and route establishment. A cluster is formed using the Euclidean distance. CH selection is performed using LOA. Route establishment is implemented using residual energy information. An extensive simulation is conducted in the network simulator ns-3 on various parameters, such as network lifetime, power consumption, packet delivery ratio (PDR), and throughput. The performance of LOA-RPL is also compared with those of RPL, fuzzy rule-based energy-efficient clustering and immune-inspired routing (FEEC-IIR), and the routing scheme for IoT that uses shuffled frog-leaping optimization algorithm (RISA-RPL). The performance evaluation metrics used in this study are network lifetime, power consumption, PDR, and throughput. The proposed LOA-RPL increases network lifetime by 20% and PDR by 5%–10% compared with RPL, FEEC-IIR, and RISA-RPL. LOA-RPL is also highly energy-efficient compared with other similar routing protocols.     

Internet of Things Based Solutions for Transport Network Vulnerability Assessment in Intelligent Transportation Systems

Intelligent Transportation System (ITS) is essential for effective identification of vulnerable units in the transport network and its stable operation. Also, it is necessary to establish an urban transport network vulnerability assessment model with solutions based on Internet of Things (IoT). Previous research on vulnerability has no congestion effect on the peak time of urban road network. The cascading failure of links or nodes is presented by IoT monitoring system, which can collect data from a wireless sensor network in the transport environment. The IoT monitoring system collects wireless data via Vehicle-to-Infrastructure (V2I) channels to simulate key segments and their failure probability. Finally, the topological structure vulnerability index and the traffic function vulnerability index of road network are extracted from the vulnerability factors. The two indices are standardized by calculating the relative change rate, and the comprehensive index of the consequence after road network unit is in a failure state. Therefore, by calculating the failure probability of road network unit and comprehensive index of road network unit in failure state, the comprehensive vulnerability of road network can be evaluated by a risk calculation formula. In short, the IoT-based solutions to the new vulnerability assessment can help road network planning and traffic management departments to achieve the ITS goals.     

面向电力物联网URLLC业务的智能网络切片管理方法

基于5G通信技术的电力物联网正在如火如荼地建设,随之产生的是用电信息采集、输变电状态监测以及精准负荷控制等新型电力物联网业务。为了满足这些业务对5G网络的超低时延和超高可靠性的需求,提出一种面向电力物联网URLLC(ultra reliable low latency communication)业务的智能网络切片管理方法。该方法综合运用5G切片和移动边缘计算(mobile edge computing,MEC)技术,建立电力业务传输和计算的时延、能耗以及可靠性模型,并通过DQN(deep Q network)算法对切片资源进行优化。仿真实验表明,所提出的智能网络切片管理方法的可靠性高于98%,且优于经典的基于坐标块下降方法和资源平均分配方法。     

微弱周期脉冲信号的自相关-混沌系统联合检测方法

简述自相关检测的原理及混沌理论,在此基础上,提出将自相关检测与混沌理论相结合检测微弱周期脉冲信号的检测方法。仿真结果表明在相同系统实验背景下,相结合的检测方案优于不加自相关的检测方法。此方法是目前信噪比门限较低的时域信号处理方法,因而具有广泛的应用前景。