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An introduction is presented in which the editor discusses articles in the issue on topics including the integrity of multimedia and multimodal data in the Internet of Things (IoT), privacy protection methods, and advanced data analysis techniques.

Routing Protocol for Low-Power and Lossy Networks (RPL) is a standard routing protocol for the Low Power and Lossy Networks (LLNs). It is a part of the IPv6 over Low-Power Wireless Personal Area Network (6LoWPAN) protocol stack. Features such as energy-efficient mechanisms and availability of the secure modes of operations make RPL suitable for the constrained Internet of Things (IoT) devices. Hence, the majority of IoT applications rely on RPL for data communication. However, routing security in RPL-based IoT networks is a significant concern, motivating us to study and analyze routing attacks and suggested countermeasures against them. To this end, we provide a comprehensive survey on the state-of-the-art security threats and their corresponding countermeasures in RPL-based IoT networks. Based on our study, we propose a novel classification scheme that uses a mapping between RPL attacks and their countermeasure techniques to the RPL control messages used to develop these techniques. Furthermore, we provide an in-depth statistical analysis that includes analysis of routing attacks through the RPL control messages, distribution of various mitigation techniques as per the method used, RPL control messages involved in the mitigation techniques, and details of the tools used by multiple researchers. In the end, we highlight some open challenges and future research opportunities on this topic. We believe that this survey will be beneficial to researchers and practitioners working in the area of RPL security. [ABSTRACT FROM AUTHOR]

In recent years, the Underwater Internet of Things (IoUT) has become a popular technology for exploring the underwater environment. IoUT enables administrators to explore and monitor underwater environmental phenomena from anywhere in the world where there is Internet access. Due to the harsh underwater environment, the reliability of communication between sensor nodes deteriorates, causing certain performance issues such as higher packet loss rate and long end-to-end delay. Therefore, it is essential to manage the communications between the sensors to address these problems in order to improve the QoS. Software-defined networking (SDN) is one of the most promising architectures for providing efficient network management by decoupling the data plane from the control plane of the network. This paper proposes a new QoS routing technique for SDN-based IoUT aiming at improving QoS by establishing reliable paths between sensor nodes. To do this, the controller gathers the 3D coordinates of each underwater sensor in order to compute the distance between the nodes. Then, it estimates the reliability of each link by using underwater acoustic equations. Finally, it calculates the most reliable path with minimum delay and installs the path on the nodes located along it. The experimental results show that our mechanism significantly outperforms other non-SDN approaches in terms of several performance measures ranging from packet loss ratio and end-to-end delay to energy consumption. [ABSTRACT FROM AUTHOR]

Cloning is a very serious threat in the Internet of Things (IoT), owing to the simplicity for an attacker to gather configuration and authentication credentials from a non-tamper-proof node, and replicate it in the network. In this paper, we propose MDSClone, a novel clone detection method based on multidimensional scaling (MDS). MDSClone appears to be very well suited to IoT scenarios, as it: 1) detects clones without the need to know the geographical positions of nodes; 2) unlike prior methods, it can be applied to hybrid networks that comprise both static and mobile nodes, for which no mobility pattern may be assumed a priori. Moreover, a further advantage of MDSClone is that 3) the core part of the detection algorithm can be parallelized, resulting in an acceleration of the whole detection mechanism. Our thorough analytical and experimental evaluations demonstrate that MDSClone can achieve a 100% clone detection probability. Moreover, we propose several modifications to the original MDS calculation, which lead to over a 75% speed up in large scale scenarios. The demonstrated efficiency of MDSClone proves that it is a promising method towards a practical clone detection design in IoT. [ABSTRACT FROM PUBLISHER]

Internet of Things (IoT) is a novel paradigm attracting significant attention in the modern wireless telecommunications field. However, in some scenarios, the performance of IoT network is limited by energy-constrained devices. In order to improve the energy efficiency of such IoT devices, researchers have proposed several approaches based on duty cycle operation (switching devices between sleeping and active mode). However, current solutions adopting duty cycle (i.e., the fraction of time in which a node is active) have three issues: (i) they assign the same duty cycle ratio to all the nodes without balancing energy consumption; or (ii) they distribute different duty cycle ratios without considering the energy consumption during network construction phase; or (iii) their network structure models are based on concentric corona, instead of clustering structure. In this paper, we propose EnergIoT, a hierarchical clustering approach based on duty cycle ratio to maximize network lifetime of battery-powered IoT devices. In particular, we assign different duty cycle ratios to devices according to their distance from the sink, since different duty cycle ratios balance the energy consumption among devices at different layers. Furthermore, we calculate the energy consumption of IoT devices, considering both network construction phase and data processing phase. We evaluate EnergIoT through extensive simulation analyses on the OMNet++ platform. The result shows that EnergIoT is not only feasible but also efficient. Moreover, EnergIoT improves the network lifetime by 32%, compared to the uniform duty cycle approach, without sacrificing the network performance (i.e., end-to-end delay). [ABSTRACT FROM AUTHOR]

In this paper, we discuss the most significant application opportunities and outline the challenges in real-time and energy-efficient management of the distributed resources available in mobile devices and at the Internet-to-Data Center. We also present an energy-efficient adaptive scheduler for Vehicular Fog Computing (VFC) that operates at the edge of a vehicular network, connected to the served Vehicular Clients (VCs) through an Infrastructure-to-Vehicular (I2V) over multiple Foglets (Fls). The scheduler optimizes the energy by leveraging the heterogeneity of Fls, where the Fl provider shapes the system workload by maximizing the task admission rate over data transfer and computation. The presented scheduling algorithm demonstrates that the resulting adaptive scheduler allows scalable and distributed implementation. [ABSTRACT FROM AUTHOR]

The large spread of sensors and smart devices in urban infrastructures are motivating research in the area of the Internet of Things (IoT) to develop new services and improve citizens' quality of life. Sensors and smart devices generate large amounts of measurement data from sensing the environment, which is used to enable services such as control of power consumption or traffic density. To deal with such a large amount of information and provide accurate measurements, service providers can adopt information fusion, which given the decentralized nature of urban deployments can be performed by means of consensus algorithms. These algorithms allow distributed agents to (iteratively) compute linear functions on the exchanged data, and take decisions based on the outcome, without the need for the support of a central entity. However, the use of consensus algorithms raises several security concerns, especially when private or security critical information is involved in the computation. In this article we propose ODIN, a novel algorithm allowing information fusion over encrypted data. ODIN is a privacy-preserving extension of the popular consensus gossip algorithm, which prevents distributed agents from having direct access to the data while they iteratively reach consensus; agents cannot access even the final consensus value but can only retrieve partial information (e.g., a binary decision). ODIN uses efficient additive obfuscation and proxy re-encryption during the update steps and garbled circuits to make final decisions on the obfuscated consensus. We discuss the security of our proposal and show its practicability and efficiency on real-world resource-constrained devices, developing a prototype implementation for Raspberry Pi devices. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is emerging with the pace of technology evolution, connecting people and things through the Internet. IoT devices enable large-scale data collection and sharing for a wide range of applications. However, it is challenging to securely manage interconnected IoT devices because the collected data could contain sensitive personal information. The authors believe that attribute-based encryption (ABE) could be an effective cryptographic tool for secure management of IoT devices. However, little research has addressed ABE's actual feasibility in the IoT thus far. This article investigates such feasibility considering well-known IoT platforms--specifically, Intel Galileo Gen 2, Intel Edison, Raspberry Pi 1 Model B, and Raspberry Pi Zero. A thorough evaluation confirms that adopting ABE in the IoT is indeed feasible. [ABSTRACT FROM AUTHOR]

Cybercrime in the past decade has experienced an all-time high due to the inclusion of so-called smart devices in our daily lives. These tiny devices with brittle security features are often dubbed as the Internet of Things (IoT). Their inclusion is not only limited to our daily lives but also in different fields, for example, healthcare, smart-industries, aviation, and smart-cities. Although IoT devices make our lives easy and perform our jobs in a smart way, but their fragile security mechanisms pose a severe challenge regarding safety and privacy of its users. Attacks like Stuxnet, and Mirai-botnet are the key examples of the damages that can be caused by maliciously controlling these devices. One effective tool to identify a malicious entity at a network device is to perform Remote Attestation (RA). However, performing RA over a large, heterogeneous IoT network is difficult tasks due to resource constrain nature of these networks. To this end, we propose a novel scheme called SARP , which is an attestation-assisted secure and scalable routing protocol for IoT networks. SARP performs attestation in large scale IoT networks by using Routing Protocol for Low Power and Lossy Networks (RPL) framework and exploiting the inbuilt features of RPL. In particular, SARP uses attestation technique that not only secures the network from internal attacks, but it also provides security to RPL's data communication process, which helps to improve the overall network performance. Moreover, SARP supports network mobility, device heterogeneity, and network scalability, while it does not sacrifice the key requirements of IoT networks such as low energy and memory consumption, and low network overhead. The simulation results obtained in different IoT scenarios in presence of various types of attacks show the effectiveness of SARP, concerning energy consumption, packet delivery ratio, network overhead, data integrity, and communication security. [ABSTRACT FROM AUTHOR]

Summary: The cyber‐security threats to low‐cost end‐user devices could severely undermine the expected deployment of Internet of Thing (IoT) solutions in a range of real‐world applications such as environment monitoring, transportation, and manufacturing. Additionally, the huge amount of data generated by these devices posses new challenges concerning tasks such as efficient information acquisition and analysis, decision making, and action implementation. In this paper, we propose CENSOR, a novel cloud‐enabled secure IoT network architecture based on SDN paradigm. We discuss the significant benefits as well as challenges that are inherent while performing integration of SDN and IoT in CENSOR. We show that the emerging software‐based networking features combined with the cloud computing solutions can significantly improve the security and communication reliability in the target IoT scenarios. In particular, to provide the adequate security measures in the network, CENSOR uses a lightweight and scalable software remote attestation scheme, which ensures the integrity of the software that is being executed by the IoT devices to achieve the application specific goals in the network. We further discuss the improvements in data communication and data overhead that can be achieved in CENSOR due to its convergence with the cloud computing (at back‐end) and fog computing services (at edge routers or front‐end). A Smart City use‐case has been considered as a target IoT scenario to analyze the feasibility and effectiveness of CENSOR concerning the communication security and the network scalability parameters. Additionally, we provide future research directions along with the recent industry initiatives that include open issues in the integration and deployment of cloud‐enabled SDN‐based IoT networks. [ABSTRACT FROM AUTHOR]

Abstract Internet-of-Things (IoT) promises to provide services to the end users by connecting physical things around them through Internet. The conventional services build for web are primarily based on the pull technology, where the user actively engages with system to get the services. However, in IoT environment, the services are based on push-based, where information and value added services will be pushed towards the user. Unless, these push-based services are properly managed they would overwhelm the user with unnecessary information, thus, it will soon start annoying the user. In this paper, we propose a lightweight context-aware IoT service architecture namely LISA to support IoT push services in an efficient manner. In particular, LISA filter and forward the most important and relevant services to the users by understanding their context. To achieve its goals, LISA formulates a user model to resolve local decision making by using agents and available web services paradigm. The proposed user model describes the user in an abstract way by considering the context and profile information of the user. For evaluation, we simulate LISA by considering an IoT tourist guide system as a use case scenario, and we show the performance of the our user model concerning precision and recall metrics. The results of our preliminary experiments confirm that LISA successfully reduces the information provided to the user by selecting only the most relevant among those. The evaluation shows that LISA can extract services for a user by selecting from 15000 services with precision upto 0.3 and recall upto 0.8, and it can be further optimized by tuning the user-specific design settings. Additionally, our approach shows improvements in query processing time which also includes the query generation time. [ABSTRACT FROM AUTHOR]

While encryption can prevent unauthorized access to a secret message, it does not provide undetectability of covert communications over the public network. Implementing a highly latent data exchange, especially with low eavesdropping/discovery probability, is challenging for practical scenarios, such as social and political movements in authoritarian regimes, military operations, and privacy preservation. Moreover, the current literature suffers from a low embedding capacity and monolingual applicability, limiting the amount of hiding secret data within short text messages using state-of-the-art algorithms, e.g., linguistic-based, structural-based, or coverless-based solutions. In this paper, we present a systematic covert communication technique called CovertSYS that enables a multilingual secure end-to-end conversation via messaging or social network platforms. The CovertSYS functions by encrypting a confidential message using a multi-factor authentication scheme and converting the encoded binary data into hidden Unicode symbols to be transmitted under cover of short text messages. We then conduct extensive experiments to confirm the security and validity of the proposed technique against state-of-the-art approaches. Our experimental results show that the CovertSYS provides a superior mean performance of 91.53% by improving the criteria scores: embedding capacity rate of 100%, imperceptibility rate of 76.4%, and distortion robustness rate of 98.2%. Finally, we discuss the practical implications of the proposed technique compared to the existing text steganography methods. [Display omitted] • Various evaluation criteria based on literature and practical scenario have been discussed. • Possible cyberattacks on covert communication systems have been described. • The CovertSYS has been implemented in an Android prototype software. • Experimental results show superior performance compared to existing related works. [ABSTRACT FROM AUTHOR]