Group and hierarchical key management for secure communications in internet of things

Different devices with different characteristics form a network to communicate among themselves in Internet of Things (IoT). Thus, IoT is of heterogeneous in nature. Also, Internet plays a major role in IoT. So, issues related to security in Internet become issues of IoT also. Hence, the group and hierarchical management scheme for solving security issues in Internet of Things is proposed in this paper. The devices in the network are formed into groups. One of the devices is selected as a leader of each group. The communication of the devices from each group takes place with the help of the leader of the corresponding group using encrypted key to enhance the security in the network. Blom's key predistribution technique is used to establish secure communication among any nodes of group. The hierarchy is maintained such that the security can be increased further, but the delay is increased as it takes time to encrypt at every level of hierarchy. Hence, the numbers of levels of hierarchy need to be optimized such that delay is balanced. Hence, this algorithm is more suitable for delay‐tolerant applications. The performance of the proposed Algorithm is evaluated and is proved to perform better when compared with the legacy systems like Decentralized Batch‐based Group Key Management Protocol for Mobile Internet of Things (DBGK).     

An SDN approach to route massive data flows of sensor networks

With the advent of the Internet of Things (IoT), more and more devices can establish a connection with local area networks and use routing protocols to forward all information to the sink. But these devices may not have enough resources to execute a complex routing protocol or to memorize all information about the network. With proactive routing protocols, each node calculates the best path, and it needs enough resources to memorize the network topology. With reactive routing protocols, each node has to broadcast the message to learn the right path that the packets must follow. In all cases, in large networks such as IoT, this is not an appropriate mechanism. This paper presents a new software‐defined network (SDN)–based network architecture to optimize the resource consumption of each IoT object while securing the exchange of messages between the embedded devices. In this architecture, the controller is in charge of all decisions, and objects only exchange messages and forward packets among themselves. In the case of large networks, the network is organized into clusters. Our proposed network architectures are tested with 1000 things grouped in five clusters and managed by one SDN controller. The tests using OpenDayLight and IoT embedded applications have been implemented on several scenarios providing the ability and the scalability from dynamic reorganization of the end‐devices. This approach explores the network performance issues using a virtualized SDN‐clustered environment which contributes to a new model for future network architectures.     

物联网的安全威胁及需求分析

物联网分布范围的广泛性、节点的移动性以及业务应用的复杂性给物联网的安全带来严峻挑战。根据物联网的架构和特点,划分物联网的安全体系,并分析了不同层面所面临的多种安全问题。分别从物联网末端节点、感知层、网络层、应用层、管理控制五个层面全面分析了物联网可能面临的多种安全威胁,并在此基础上提出了物联网面临的安全需求。     

Security and Privacy in IoT: A Survey

The Internet of Things (IoT) is a network of globally connected physical objects, which are associated with each other via Internet. The IoT foresees the interconnection of few trillions of intelligent objects around us, uniquely and addressable every day, these objects have the ability to accumulate process and communicate data about themselves and their surrounding environment. The best examples of IoT systems are health care, building smart city with advance construction management system, public and defense surveillance and data acquisition. Recent advancement in the technology has developed smart and intelligent sensor nodes and RFIDs lead to a large number of wireless networks with smart and intelligent devices (object, or things) connected to the Internet continuously transmit the data. So to provide security and privacy to this data in IoT is a very challenging task, which is to be concerned at highest priority for several current and future applications of IoT. Devices such as smart phone, WSNs and RFIDs etc., are the major components of IoT network which are basically resource constrained devices. Design and development of security and privacy management schemes for these devices is guided by factors like good performance, low power consumption, robustness to attacks, tampering of the data and end to end security. Security schemes in IoT provide unauthorized access to information or other objects by protecting against alterations or destruction. Privacy schemes maintain the right to control about the collected information for its usage and purpose. In this paper, we have surveyed major challenges such as Confidentiality, Integrity, Authentication, and Availability for IoT in a brief manner.

     

Integration of IoT and DRAGON-lab in cloud environment

Distributed research & academic gigabits open network lab (DRAGON-lab) is the only test-bed for research purpose related to next generation internct (NGI) which based on the confederation network using...     

使用深度学习的社交物联网信任预测模型

社交物联网是社交网络概念在物联网中整合后兴起的一个蓬勃发展的研究领域。提出了一种适用于社交物联网网络的改进型节点级信任模型,并通过与其他信任模型的对比仿真实验证明在恶意节点的攻击下,提出的模型拥有更好的稳定性和适用性,总体波动较小。同时,针对实际社交物联网网络中新加入网络的陌生节点可能遇到的网络延迟影响信任值评估的问题,在改进型节点级信任模型的基础上进一步使用了深度学习模型对其进行信任值预测。仿真证明,使用深度学习预测后模型的系统性能明显优于不使用深度学习的模型,成功交互率提升约1.8%。     

物联网中信任管理机制(英)

Trust management has been proven to be a useful technology for providing security service and as a consequence has been used in many applications such as P2P,Grid,ad hoc network and so on.However,few researches about trust mechanism for Internet of Things(IoT) could be found in the literature,though we argue that considerable necessity is held for applying trust mechanism to IoT.In this paper,we establish a formal trust management control mechanism based on architecture modeling of IoT.We decompose the IoT into three layers,which are sensor layer,core layer and application layer,from aspects of network composition of IoT.Each layer is controlled by trust management for special purpose:self-organized,affective routing and multi-service respectively.And the final decision-making is performed by service requester according to the collected trust information as well as requester' policy.Finally,we use a formal semantics-based and fuzzy set theory to realize all above trust mechanism,the result of which provides a general framework for the development of trust models of IoT.     

Unsupervised learning with hierarchical feature selection for DDoS mitigation within the ISP domain

A new Mirai variant found recently was equipped with a dynamic update ability, which increases the level of difficulty for DDoS mitigation. Continuous development of 5G technology and an increasing number of Internet of Things (IoT) devices connected to the network pose serious threats to cyber security. Therefore, researchers have tried to develop better DDoS mitigation systems. However, the majority of the existing models provide centralized solutions either by deploying the system with additional servers at the host site, on the cloud, or at third party locations, which may cause latency. Since Internet service providers (ISP) are links between the internet and users, deploying the defense system within the ISP domain is the panacea for delivering an efficient solution. To cope with the dynamic nature of the new DDoS attacks, we utilized an unsupervised artificial neural network to develop a hierarchical two‐layered self‐organizing map equipped with a twofold feature selection for DDoS mitigation within the ISP domain.     

基于可信计算构筑物联网安全边界

近年来，中国物联网政策支持力度不断加大，技术创新成果接连涌现，各领域应用持续深化，产业规模保持快速增长。本论文以物联网接入边界为切入点，探讨了物联网安全接入问题的解决方案。设计了基于可信计算3.0的物联网可信网关，以及安全管理中心，构建了可信的物联网安全边界接入系统。为各种异构物联网终端设备提供了安全屏障，隔绝了针对于物联网设备的网络安全威胁。     

EPC物联网技术在供应链管理中应用研究

近年来,物联网受到了业界广泛的关注,并被看做是推动经济发展新的驱动力,被世界各国视为应对金融危机、振兴经济的重点技术领域。物联网的不断发展,已对企业供应链管理产生越来越显著的影响。通过介绍物联网的概念,分析了当前供应链管理存在的诸多问题,阐述了物联网的基本构成、结构,结合物联网在供应链的采购、生产、运输、仓储、销售各环节的应用情况,阐述了物联网对供应链管理过程的影响,展望了供应链发展趋势。