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The world is resorting to the Internet of Things (IoT) for ease of control and monitoring of smart devices. The ubiquitous use of IoT ranges from Industrial Control Systems (ICS) to e-Health, e-Commerce, smart cities, supply chain management, smart cars, Cyber Physical Systems (CPS) and a lot more. Such reliance on IoT is resulting in a significant amount of data to be generated, collected, processed and analyzed. The big data analytics is no doubt beneficial for business development. However, at the same time, numerous threats to the availability and privacy of the user data, message and device integrity, the vulnerability of IoT devices to malware attacks and the risk of physical compromise of devices pose a significant danger to the sustenance of IoT. This paper thus endeavors to highlight most of the known threats at various layers of the IoT architecture with a focus on the anatomy of malware attacks. We present a detailed attack methodology adopted by some of the most successful malware attacks on IoT including ICS and CPS. We also deduce an attack strategy of a Distributed Denial of Service attack through IoT botnet followed by requisite security measures. In the end, we propose a composite guideline for the development of an IoT security framework based on industry best practices and also highlight lessons learned, pitfalls and the open research challenges. Index Terms-Threats to the IoT, Internet of Things, malware attacks on the Internet of Things, attack methodology, security and privacy, IoT security framework, security guidelines.

Future 5th generation (5G) networks are expected to enable three key services -enhanced mobile broadband (eMBB), massive machine type communications (mMTC) and ultra-reliable and low latency communications (URLLC). As per the 3rd generation partnership project (3GPP) URLLC requirements, it is expected that the reliability of one transmission of a 32 byte packet will be at least 99.999% and the latency will be at most 1 ms. This unprecedented level of reliability and latency will yield various new applications such as smart grids, industrial automation and intelligent transport systems. In this survey we present potential future URLLC applications, and summarize the corresponding reliability and latency requirements. We provide a comprehensive discussion on physical (PHY) and medium access control (MAC) layer techniques that enable URLLC, addressing both licensed and unlicensed bands. The paper evaluates the relevant PHY and MAC techniques for their ability to improve the reliability and reduce the latency. We identify that enabling long-term evolution (LTE) to coexist in the unlicensed spectrum is also a potential enabler of URLLC in the unlicensed band, and provide numerical evaluations. Lastly, the paper discusses the potential future research directions and challenges in achieving the URLLC requirements.

The ubiquitous use of Internet of Things (IoT) ranges from industrial control systems to e-Health, e-commerce, smart cities, agriculture, supply chain management, smart cars, cyber-physical systems and a lot more. However, the data collected and processed by IoT systems especially the ones with centralized control are vulnerable to availability, integrity, and privacy threats. Hence, we present "PrivySharing," a blockchainbased innovative framework for privacy-preserving and secure IoT data sharing in a smart city environment. The proposed scheme is distinct from existing strategies on many aspects. The data privacy is preserved by dividing the blockchain network into various channels, where every channel comprises a finite number of authorized organizations and processes a specific type of data such as health, smart car, smart energy or financial details. Moreover, access to users' data within a channel is controlled by embedding access control rules in the smart contracts. In addition, data within a channel is further isolated and secured by using private data collection and encryption respectively. Likewise, the REST API that enables clients to interact with the blockchain network has dual security in the form of an API Key and OAuth 2.0. The proposed solution conforms to some of the significant requirements outlined in the European Union General Data Protection Regulation. We also present a system of reward in the form of a digital token named "PrivyCoin" for users sharing their data with stakeholders/third parties. Lastly, the experimental outcomes advocate that a multi-channel blockchain scales well as compared to a single-channel blockchain system.

Task admission is critical to delay-sensitive applications in mobile edge computing, but technically challenging due to its combinatorial mixed nature and consequently limited scalability. We propose an asymptotically optimal task admission approach which is able to guarantee task delays and achieve (1 −)-approximation of the computationally prohibitive maximum energy saving at a time-complexity linearly scaling with devices. is linear to the quantization interval of energy. The key idea is to transform the mixed integer programming of task admission to an integer programming (IP) problem with the optimal substructure by pre-admitting resource-restrained devices. Another important aspect is a new quantized dynamic programming algorithm which we develop to exploit the optimal substructure and solve the IP. The quantization interval of energy is optimized to achieve an [O(), O(1/)]-tradeoff between the optimality loss and time-complexity of the algorithm. Simulations show that our approach is able to dramatically enhance the scalability of task admission at a marginal cost of extra energy, as compared to the optimal branch and bound method, and can be efficiently implemented for online programming.

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