Container-Based Internet of Vehicles Edge Application Migration Mechanism

Internet of Vehicles (IoV) applications integrating with edge computing will significantly drive the growth of IoV. However, the contradiction between the high-speed mobility of vehicles, the delay sensitivity of corresponding IoV applications and the limited coverage and resource capacity of distributed edge servers will pose challenges to the service continuity and stability of IoV applications. IoV application migration is a promising solution that can be supported by application containerization, a technology forseamless cross-edge-server application migration without user perception. Therefore, this paper proposes the container-based IoV edge application migration mechanism, consisting of three parts. The first is the migration trigger determination algorithm for cross-border migration and service degradation migration, respectively, based on trajectory prediction and traffic awareness to improve the determination accuracy. The second is the migration target decision calculation model for minimizing the average migration time and maximizing the average service time to reduce migration times and improve the stability and adaptability of migration decisions. The third is the migration decision algorithm based on the improved artificial bee colony algorithm to avoid local optimal migration decisions. Simulation results show that the proposed migration mechanism can reduce migration times, reduce average migration time, improve average service time and enhance the stability and adaptability of IoV application services.     

车联网情境下提升新手驾驶员信心的交互策略研究

目的在车联网中,人作为控制和平衡人—车—环境的核心,同时也是整体系统的不安全因素之一。本文旨在深入探索新手驾驶员的驾驶特征,挖掘痛点和需求,有针对性地提出交互策略,帮助新手驾驶员改善交互体验,提升驾驶信心。方法通过心理学定量研究的方法收集相关数据,结合定性分析得出人车交互特质,绘制用户旅程,并提出符合驾驶特征的交互策略。结论结合心理学、用户研究的人车交互策略,对于新手驾驶员的实际训练具有一定的指导作用,对于车联网下的道路安全具有重大意义。     

基于车联网的HMI交互体验流程与方法探究

目的探索交互设计的方法与流程在基于车联网的HMI交互体验设计过程中的应用方式,推进车联网技术在HMI交互产品中的应用。方法以交互设计方法与流程为基础,分析和对比不同课题中交互设计的方法和流程的应用方式,利用策略性设计成果检验方法的有效性。探讨了交互设计方法与流程在HMI交互体验研究和设计中的有效应用方式。结论结合案例表明了交互设计方法与流程在HMI交互体验设计过程中的重要指导作用,时刻基于用户中心理念对具体方法进行灵活组合运用是必要的。     

基于车联网的汽车大数据创新应用路径研究

目的为利用汽车大数据产生创新应用方案提供路径。方法分析汽车大数据的类型及创新应用方向,并从数据的收集、使用和挖掘出发,在数据感知、数据关联、模式挖掘、数据开放和数据平台使用等方面展开创新路径的探索。结论提出了不同的大数据创新应用路径,以支持创新方案的产生。     

Traffic Management in Internet of Vehicles Using Improved Ant Colony Optimization

The Internet of Vehicles (IoV) is a networking paradigm related to the intercommunication of vehicles using a network. In a dynamic network, one of the key challenges in IoV is traffic management under increasing vehicles to avoid congestion. Therefore, optimal path selection to route traffic between the origin and destination is vital. This research proposed a realistic strategy to reduce traffic management service response time by enabling real-time content distribution in IoV systems using heterogeneous network access. Firstly, this work proposed a novel use of the Ant Colony Optimization (ACO) algorithm and formulated the path planning optimization problem as an Integer Linear Program (ILP). This integrates the future estimation metric to predict the future arrivals of the vehicles, searching the optimal routes. Considering the mobile nature of IOV, fuzzy logic is used for congestion level estimation along with the ACO to determine the optimal path. The model results indicate that the suggested scheme outperforms the existing state-of-the-art methods by identifying the shortest and most cost-effective path. Thus, this work strongly supports its use in applications having stringent Quality of Service (QoS) requirements for the vehicles.     

SDN-Enabled Content Dissemination Scheme for the Internet of Vehicles

The content-centric networking (CCN) architecture allows access to the content through name, instead of the physical location where the content is stored, which makes it a more robust and flexible content-based architecture. Nevertheless, in CCN, the broadcast nature of vehicles on the Internet of Vehicles (IoV) results in latency and network congestion. The IoV-based content distribution is an emerging concept in which all the vehicles are connected via the internet. Due to the high mobility of vehicles, however, IoV applications have different network requirements that differ from those of many other networks, posing new challenges. Considering this, a novel strategy mediator framework is presented in this paper for managing the network resources efficiently. Software-defined network (SDN) controller is deployed for improving the routing flexibility and facilitating in the inter-interoperability of heterogeneous devices within the network. Due to the limited memory of edge devices, the delectable bloom filters are used for caching and storage. Finally, the proposed scheme is compared with the existing variants for validating its effectiveness.     

Security Analysis of Smart Speaker: Security Attacks and Mitigation

The speech recognition technology has been increasingly common in our lives. Recently, a number of commercial smart speakers containing the personal assistant system using speech recognition came out. While the smart speaker vendors have been concerned about the intelligence and the convenience of their assistants, but there have been little mentions of the smart speakers in security aspects. As the smart speakers are becoming the hub for home automation, its security vulnerabilities can cause critical problems. In this paper, we categorize attack vectors and classify them into hardware-based, network-based, and software-based. With the attack vectors, we describe the detail attack scenarios and show the result of tests on several commercial smart speakers. In addition, we suggest guidelines to mitigate various attacks against smart speaker ecosystem.     

A New Model for Network Security Situation Assessment of the Industrial Internet

To address the problem of network security situation assessment in the Industrial Internet, this paper adopts the evidential reasoning (ER)algorithm and belief rule base (BRB) method to establish an assessment model. First, this paper analyzes the influencing factors of the Industrial Internet and selects evaluation indicators that contain not only quantitative data but also qualitative knowledge. Second, the evaluation indicators are fused with expert knowledge and the ER algorithm. According to the fusion results, a network security situation assessment model of the Industrial Internet based on the ER and BRB method is established, and the projection covariance matrix adaptive evolution strategy (P-CMA-ES) is used to optimize the model parameters. This method can not only utilize semiquantitative information effectively but also use more uncertain information and prevent the problem of combinatorial explosion. Moreover, it solves the problem of the uncertainty of expert knowledge and overcomes the problem of low modeling accuracy caused by insufficient data. Finally, a network security situation assessment case of the Industrial Internet is analyzed to verify the effectiveness and superiority of the method. The research results show that this method has strong applicability to the network security situation assessment of complex Industrial Internet systems. It can accurately reflect the actual network security situation of Industrial Internet systems and provide safe and reliable suggestions for network administrators to take timely countermeasures, thereby improving the risk monitoring and emergency response capabilities of the Industrial Internet.     

A Secure Communication Protocol for Unmanned Aerial Vehicles

Mavlink is a lightweight and most widely used open-source communication protocol used for Unmanned Aerial Vehicles. Multiple UAVs and autopilot systems support it, and it provides bi-directional communication between the UAV and Ground Control Station. The communications contain critical information about the UAV status and basic control commands sent from GCS to UAV and UAV to GCS. In order to increase the transfer speed and efficiency, the Mavlink does not encrypt the messages. As a result, the protocol is vulnerable to various security attacks such as Eavesdropping, GPS Spoofing, and DDoS. In this study, we tackle the problem and secure the Mavlink communication protocol. By leveraging the Mavlink packet’s vulnerabilities, this research work introduces an experiment in which, first, the Mavlink packets are compromised in terms of security requirements based on our threat model. The results show that the protocol is insecure and the attacks carried out are successful. To overcome Mavlink security, an additional security layer is added to encrypt and secure the protocol. An encryption technique is proposed that makes the communication between the UAV and GCS secure. The results show that the Mavlink packets are encrypted using our technique without affecting the performance and efficiency. The results are validated in terms of transfer speed, performance, and efficiency compared to the literature solutions such as MAVSec and benchmarked with the original Mavlink protocol. Our achieved results have significant improvement over the literature and Mavlink in terms of security.     

车联网时代的安全与隐私

随着车联网时代的到来,汽车智能化的飞速发展也给车主带来安全上的隐患.本文对目前智能网联汽车几个常见的安全问题:OBD、远程控制、无钥匙进入、车主隐私等做了逐一的分析,并探讨了几个解决问题的方法.     

Resource Load Prediction of Internet of Vehicles Mobile Cloud Computing

Load-time series data in mobile cloud computing of Internet of Vehicles (IoV) usually have linear and nonlinear composite characteristics. In order to accurately describe the dynamic change trend of such loads, this study designs a load prediction method by using the resource scheduling model for mobile cloud computing of IoV. Firstly, a chaotic analysis algorithm is implemented to process the load-time series, while some learning samples of load prediction are constructed. Secondly, a support vector machine (SVM) is used to establish a load prediction model, and an improved artificial bee colony (IABC) function is designed to enhance the learning ability of the SVM. Finally, a CloudSim simulation platform is created to select the per-minute CPU load history data in the mobile cloud computing system, which is composed of 50 vehicles as the data set; and a comparison experiment is conducted by using a grey model, a back propagation neural network, a radial basis function (RBF) neural network and a RBF kernel function of SVM. As shown in the experimental results, the prediction accuracy of the method proposed in this study is significantly higher than other models, with a significantly reduced real-time prediction error for resource loading in mobile cloud environments. Compared with single-prediction models, the prediction method proposed can build up multidimensional time series in capturing complex load time series, fit and describe the load change trends, approximate the load time variability more precisely, and deliver strong generalization ability to load prediction models for mobile cloud computing resources.     

An Intelligent Forwarding Strategy in SDN-Enabled Named-Data IoV

Internet of Vehicles (IoV), a rapidly growing technology for efficient vehicular communication and it is shifting the trend of traditional Vehicular Ad Hoc Networking (VANET) towards itself. The centralized management of IoV endorses its uniqueness and suitability for the Intelligent Transportation System (ITS) safety applications. Named Data Networking (NDN) is an emerging internet paradigm that fulfills most of the expectations of IoV. Limitations of the current IP internet architecture are the main motivation behind NDN. Software-Defined Networking (SDN) is another emerging networking paradigm of technology that is highly capable of efficient management of overall networks and transforming complex networking architectures into simple and manageable ones. The combination of the SDN controller, NDN, and IoV can be revolutionary in the overall performance of the network. Broadcast storm, due to the broadcasting nature of NDN, is a critical issue in NDN based on IoV. High speed and rapidly changing topology of vehicles in IoV creates disconnected link problem and add unnecessary transmission delay. In order to cop-up with the above-discussed problems, we proposed an efficient SDN-enabled forwarding mechanism in NDN-based IoV, which supports the mobility of the vehicle and explores the cellular network for the low latency control messages. In IoV environment, the concept of Edge Controller (EC) to maintain and manage the in-time and real-time vehicular topology is being introduced. A mathematical estimation model is also proposed in our work that assists the centralized EC and SDN to find not only the shortest and best path but also the most reliable and durable path. The naming scheme and in-network caching property of the NDN nodes reduce the delay. We used ndnSIM and NS-3 for the simulation experiment along with SUMO for the environment generation. The results of NDSDoV illustrate significant performance in terms of availability with limited routing overhead, minimized delay, retransmissions, and increased packet satisfaction ratio. Besides, we explored the properties of EC that contribute mainly in path failure minimization in the network.     

A Phase Estimation Algorithm for Quantum Speed-Up Multi-Party Computing

Security and privacy issues have attracted the attention of researchers in the field of IoT as the information processing scale grows in sensor networks. Quantum computing, theoretically known as an absolutely secure way to store and transmit information as well as a speed-up way to accelerate local or distributed classical algorithms that are hard to solve with polynomial complexity in computation or communication. In this paper, we focus on the phase estimation method that is crucial to the realization of a general multi-party computing model, which is able to be accelerated by quantum algorithms. A novel multi-party phase estimation algorithm and the related quantum circuit are proposed by using a distributed Oracle operator with iterations. The proved theoretical communication complexity of this algorithm shows it can give the phase estimation before applying multi-party computing efficiently without increasing any additional complexity. Moreover, a practical problem of multi-party dating investigated shows it can make a successful estimation of the number of solution in advance with zero communication complexity by utilizing its special statistic feature. Sufficient simulations present the correctness, validity and efficiency of the proposed estimation method.     

Security Requirement Management for Cloud-Assisted and Internet of Things—Enabled Smart City

The world is rapidly changing with the advance of information technology. The expansion of the Internet of Things (IoT) is a huge step in the development of the smart city. The IoT consists of connected devices that transfer information. The IoT architecture permits on-demand services to a public pool of resources. Cloud computing plays a vital role in developing IoT-enabled smart applications. The integration of cloud computing enhances the offering of distributed resources in the smart city. Improper management of security requirements of cloud-assisted IoT systems can bring about risks to availability, security, performance, confidentiality, and privacy. The key reason for cloud- and IoT-enabled smart city application failure is improper security practices at the early stages of development. This article proposes a framework to collect security requirements during the initial development phase of cloud-assisted IoT-enabled smart city applications. Its three-layered architecture includes privacy preserved stakeholder analysis (PPSA), security requirement modeling and validation (SRMV), and secure cloud-assistance (SCA). A case study highlights the applicability and effectiveness of the proposed framework. A hybrid survey enables the identification and evaluation of significant challenges.     

泛在电力物联网实施策略研究

建设泛在电力物联网是实现能源转型目标的必要手段。从电力系统发展历程和面临的问题出发,论述了泛在电力物联网的意义,提出了实施策略和可能遇到的问题。为实现能源转型,风电光电等可再生能源装机容量不断增加。这些能源的随机性给电力系统的功率平衡造成巨大压力,有时不得不弃掉一部分风电光电。为了维持电力系统的稳定运行、提高风电光电的利用率,必须对可控负荷和分散式发电进行控制。因此,需要用互联网连接可控负荷和分散式发电,形成泛在电力物联网。常规发电厂、大型风电场、光电站等已经和电力系统连接了,调度可以直接控制。因此,泛在电力物联网主要任务是连接负荷和分散式发电,尤其是可控负荷。电动汽车是可控负荷中最容易实现可控的,其次是热水器、电热锅炉和空调等。利用泛在电力物联网,协同控制风电光电、可控负荷、分散式发电等,可以提高风电光电利用率,实现能源转型目标。     

Cloud Security Service for Identifying Unauthorized User Behaviour

Recently, an innovative trend like cloud computing has progressed quickly in Information Technology. For a background of distributed networks, the extensive sprawl of internet resources on the Web and the increasing number of service providers helped cloud computing technologies grow into a substantial scaled Information Technology service model. The cloud computing environment extracts the execution details of services and systems from end-users and developers. Additionally, through the system’s virtualization accomplished using resource pooling, cloud computing resources become more accessible. The attempt to design and develop a solution that assures reliable and protected authentication and authorization service in such cloud environments is described in this paper. With the help of multi-agents, we attempt to represent Open-Identity (ID) design to find a solution that would offer trustworthy and secured authentication and authorization services to software services based on the cloud. This research aims to determine how authentication and authorization services were provided in an agreeable and preventive manner. Based on attack-oriented threat model security, the evaluation works. By considering security for both authentication and authorization systems, possible security threats are analyzed by the proposed security systems.     

互联网产品的情感温度提升策略研究

目的 研究互联网产品中的情感温度的设计触点及其提升策略,丰富用户体验设计的相关理论。方法 从用户的感知层面出发,分析互联网产品在视觉、触觉、意觉三个层面的情感交互内容,并以此为设计点,提出设计策略,提升用户体验。结论 指出了提升互联网产品情感温度的重要性。从用户的感知层面将情感温度分为视觉层面、触觉层面和意觉层面,不仅有针对性地探索了优化视觉层面的导流设计、扁平化触觉层面的信息层级、简化触觉层面的行为路径,而且深入地解读了用户在意觉层面的需求等。通过使用这些方面的策略,能有效地提高产品实用性,更好地满足用户情感需求,进而提高产品的竞争力。     

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.     

国家网络空间安全国际战略研究

网络空间安全已成为国家安全的主要组成部分,在经济和社会发展中发挥日益重要的作用。本文立足全球网络空间安全的总体形势,着眼于我国面临的机遇和挑战,研究符合我国价值观和国家利益的国际网络空间安全战略,并提出了相应的战略目标、原则和任务。