The developments of Narrow Band Internet of Things have attracted much attention from both academia and industry nowadays. While Narrow Band Internet of Things is gradually designed for commercial applications, it also confronts with several security concerns such as identification and privacy. Blockchain technique is equipped with authentication, auditing, and accountability, and thus it can serve as a promising tool for providing secure data communication on the network. To enhance the security level and achieve reliable data authentication and accountability for Narrow Band Internet of Things system, in this article, we combine the merits of blockchain technique and propose a blockchain-based architecture for Narrow Band Internet of Things. The presented architecture consists of three layers which are sensing layer, transport layer, and transaction layer. We describe the interaction processes between each layer in detail and construct the algorithms which are used to conduct data authentication and blockchain generation. By evaluation, our scheme is demonstrated to obtain favorable performances in terms of privacy, authentication, accountability, and efficiency, which makes it an appropriate method to be applied for secure data communication in Narrow Band Internet of Things systems.

Software-defined networking (SDN) emerges as an innovative network paradigm, which separates the control plane from the data plane to improve the network programmability and flexibility. It is widely applied in the Internet of Things (IoT). However, SDN is vulnerable to DDoS attacks, which can cause network disasters. In order to protect SDN security, a DDoS detection method using cloud-edge collaboration based on Entropy-Measuring Self-organizing Maps and KD-tree (EMSOM-KD) is designed for SDN. Entropy measurement is utilized to select the ideal SOM map and classify SOM neurons considering the limitation of dead and suspicious neurons. EMSOM can detect most flows directly and filter out a few doubtable flows. Then these flows are fine-grained, identified by KD-tree. Due to the limited and precious resources of the controller, parameter computation is performed in the cloud. The edge controller implements DDoS detection by EMSOM-KD. The experiments are conducted to evaluate the performance of the proposed method. The results show that EMSOM-KD has better detection accuracy; moreover, it improves the KD-tree detection efficiency.

Authentication is crucial for network system security, relying on methods such as passwords, ID cards, biometrics, and behavioral characteristics. The conventional centralized authentication may lead to potential performance bottlenecks and privacy risks such as key exposure, single point of failure. Decentralized authentication systems using cryptographic techniques aim to address these issues but often tradeoff between flexibility and communication efficiency. In this paper we propose a new cryptographic concept called designated private set-based trapdoor authentication (DPSBTA) for flexible and efficient trust management in decentralized systems. DPSBTA eliminates the need for a trusted authority, with users’ access privileges defined by their private sets. During the authentication process, each server can designate an element set and only if a user holds adequate elements which are contained in the designated set can he obtains a credential from the server. The key features of DPSBTA include: decentralized trapdoor authentication management, without a trusted authority, conducted in a double threshold manner; privacy preservation, as servers do not know users’ element holdings or credential generation; round-optimal communication, with only two rounds of interaction between users and servers. We present the generic construction, security models, and concrete algorithms with correctness proof. The theoretical proof and the performance evaluations demonstrate the tangible security and high efficacy of the proposed DPSBTA.