Nowadays, some decentralized anonymous payment (DAP) systems have emerged to protect transaction privacy. However, these systems may be strictly limited by certain governments due to the difficulty of tracking financial flow, which severely restricts their circulation. Although several auditable DAP (ADAP) systems permit authorities to monitor transactions, the potential for privacy violations instead makes users hesitate to apply them. As a result, it becomes a dilemma. Thus, this paper proposes an ADAP system that follows the least-privilege principle, called LP-ADAP, to strike a balance between auditability and privacy preservation. First, LP-ADAP employs a consensus audit mechanism to prevent transactions from being investigated by a single malicious auditor. In addition, the proposed method adheres to the least-privilege principle, strictly limiting auditors to only the minimum necessary permissions, thus limiting the privacy leakage of the senders and receivers. Finally, auditors in LP-ADAP can conduct offline audits without participating in the transaction phase, reducing their burden. Experiment results show that LP-ADAP outperforms existing mechanisms in transaction generation and verification. Moreover, the transaction size of LP-ADAP is mostly smaller than that of other methods, even when the number of auditors increases. Consequently, LP-ADAP is the most practical and trustworthy DAP system.

Fog computing is promising for Industrial Internet of Things (IIoT) which are typically large-scale, time-critical, and geo-distributed. However, it needs to address challenges such as scalability and heterogeneity in application provisioning with diverse and strict Quality-of-Service (QoS) requirements from IIoT devices. In this paper, a fog service orchestrator, Q-FSO, is proposed for IIoT application provisioning in which request satisfaction is maximized. With a two-level QoS model that considers key performance metrics for IIoT, including availability, reliability, response time, and cost, Q-FSO can realize large-scale service orchestration by exploiting the advantages of fog computing. Further with a harmonious local QoS assignment model, Q-FSO solves the workflow construction problem by multiple independent local optimization tasks, one for each stage, for the concurrent requests. Each local optimization task can be reduced from the multiple multidimensional knapsack (MMKP) problem. We then propose two practical MMKP heuristic algorithms, namely, Incremental Similarity Matching (ISM) and Greedy Multiple Matching (GMM), to tackle the local QoS assignment problem with polynomial time complexity. The scalability issue in orchestration is then handled by a decentralized workflow construction protocol. The simulation results validate their applicability, demonstrating that Q-FSO is indeed an efficient and effective IIoT application provision mechanism with significant performance benefits in terms of service processing throughput, resource utilization, and speed of service orchestration.

IoT data economy is an emerging concept since sensing data are widely applied in various IoT services. To maintain the stability of data economic system, this paper proposes the Reliable IoT Data Economic System (RIDES) to provide IoT data a reliable, automatic, and intelligent trading environment. Applying the smart contract technique, IoT data in RIDES can be automatically traded without human intervention. As the trading procedure is performed based on blockchain, all transactions can be protected against tampering. Also, the RIDES provides the Smart Decision Making Module for users to develop practical pricing strategies. Thus, a seller can derive a price with the highest expected revenue for its data and a buyer can purchase its desired data referring to cost-performance ratio or data owner's trustworthiness. Even if malicious sellers cheat buyers, the latter can invoke trade dispute procedure to refund their payment, which makes the trading environment more reliable. As the blockchain-based operations usually cost much, the RIDES adopts the edge computing architecture to alleviate the burdens of IoT devices. Finally, the RIDES is implemented in IoT environments. The case study demonstrates that the transactions on IoT data can be performed correctly by RIDES.

Internet of Things (IoT) is an emerging network technology applied to provide various services in our daily life. Generally, IoT environments are composed of numerous heterogeneous devices with constrained resource. The limited capability of IoT devices makes it impractical to perform traditional security mechanisms, and thus IoT services are usually vulnerable to all kinds of security threats, such as impersonation and forgery attacks. Moreover, the inflexible protection provided by these security mechanisms leads to inefficiency because different services haves diverse requirements. To provide IoT services suitable security protection, Multi-graph Zero-knowledge-based Authentication System (M-ZAS), which is not only light-weight but also high-adaptive, is proposed. Compared to traditional authentication mechanisms as well as other Zero-knowledge-proof (ZKP) methods such as GMW-ZKP, M-ZAS provides higher performance and better security protection. In addition, M-ZAS has lower transmission overheads than GMW-ZKP does. Considering relevant contexts as parameters, M-ZAS provides adaptive protection to fulfill what users actually need. Experiment results show that M-ZAS is 3 times faster than GMW-ZKP and even 7 times than traditional authentication mechanisms in IoT devices. Also, M-ZAS reduces 3 times network traffic than GMW-ZKP. Thus, the proposed M-ZAS is the most practical authentication system in IoT environments.

Data dissemination is an essential application in the opportunistic network which has received considerable attention recently. Delivering data effectively and rapidly is the major target of data dissemination. However, many scenarios ask data to be sent to specific locations at designated time. For example, the information of bargain news is useful in shopping streets during business hours. Unfortunately, existing dissemination routing protocols suffer from huge transmission overheads. Moreover, due to the limited capability of devices, context-based routing methods are also inapplicable since their computation complexity is high. This paper therefore presents a novel timesensitive data dissemination scheme (TSDD) composed of three major components including node location prediction, relay node selection, and successor selection. By exploiting some accessible information, TSDD can deliver time-sensitive data efficiently. Simulation results show that TSDD provides higher delivery rate with less transmission overheads than existing methods.

Rendezvous is an essential operation for secondary users communicating in a cognitive radio network (CRN). Because it is infeasible to employ a common control channel in a licensed spectrum, blind rendezvous is an expected solution and generally estimated by the criteria of asynchronous rendezvous support, guaranteed rendezvous, asymmetric model support, heterogeneity of roles, and short time-to-rendezvous (TTR). Most existing blind rendezvous methods fail to fully satisfy these criteria or have considerable TTR significantly increased with the number of channels. This paper presents a new alternate hop-and-wait channel hopping method, called E-AHW, which can support fast blind rendezvous. By assigning each secondary user a unique alternate channel hopping sequence composed of HOP/WAIT-mode subsequences, all blind rendezvous criteria can be satisfied with shorter TTR. According to simulation results, the performance of E-AHW is better than existing methods. Moreover, using E-AHW, the average value and standard deviation of time intervals between two rendezvous are also less than other methods. Thus, E-AHW can provide an efficient and stable communication environment.

Cognitive Radio (CR) is an emerging technology developed to improve the utilization of licensed spectra, and a promising solution to alleviate the spectrum shortage problem. In cognitive radio networks (CRNs), if users want to establish communication links with neighbors, they need to rendezvous on an available channel. However, it is infeasible to employ a common control channel (CCC) in a licensed spectrum, because the CCC will be congested by primary users and degrade the performance of CRNs by the single point of failure problem. Therefore, the channel hopping (CH) based methods without CCC support are usually adopted to establish rendezvous in CRNs. This kind of rendezvous is called blind rendezvous and generally estimated by the following criteria: 1) asynchronous rendezvous support, 2) guaranteed rendezvous, 3) asymmetric model support, 4) multi-user/multi-hop scenario support, and 5) short time-to-rendezvous (TTR). Most existing blind rendezvous methods fail to fully satisfy these criteria or have considerable TTR which is significantly increased with the number of available channels. In this paper, the alternate hop-and-wait CH method is proposed to solve these problems. Furthermore, each user has a unique alternating sequence of HOP and WAIT modes. The theoretical analysis results have confirmed that the proposed method satisfies all evaluation criteria mentioned above and provides shorter TTR. According to simulation results, the performance of the proposed method even is two times better than Jump-Stay algorithm (JS), which is the most efficient blind rendezvous method as we know, under the asymmetric model which is much critical for CRNs.

In this paper, a series of novel secure dynamic routing protocols are proposed to provide the end-to-end security. Unlike the existing dynamic routing protocols with security consideration which focus on a certain specific network threat, in the paper the proposed approach is based on a comprehensive network security evaluation framework. By analyzing the threats, vulnerabilities, countermeasures, and security requirements of networks, the danger intensity of threats is systematically quantified. Then, the risk score of a link can be obtained by integrating danger intensity of all threats on this link. Since a routing path is composed of several links, three secure dynamic routing protocols, with specific security and performance requirements, are proposed to find a secure routing path according to the link risk scores. The simulation results show that the proposed secure dynamic routing protocols are able to derive a more secure routing path than traditional dynamic routing protocols, even with considering routing performance.

A resource-efficient key management protocol is essential for security-sensitive applications in wireless sensor networks (WSN). Moreover, the dynamic pair-wise key and group key management protocols are also important for long-lived and mobile WSN. In this paper, a two-layered dynamic key management (TDKM) approach for cluster-based WSN (CWSN) is proposed. Both pair-wise key and group key are distributed in three rounds for key material exchange without encryption/decryption and exponentiation operations in TDKM. In theoretical analysis, TDKM is compared with other key management protocols to show its efficiency. Finally, the relationships between the number of groups and the system performance including key generation overhead, network security, and secured data transmission overhead in CWSN are analyzed.