The Internet of Things (IoT) aims to transform everyday physical objects into an interconnected ecosystem with digital data accessible anywhere and anytime. “Things” in IoT are embedded with sensing, processing, and actuating capabilities and cooperate in providing smart and innovative services autonomously. The rapid spread of IoT services arises different security vulnerabilities that need to be carefully addressed. Several emerging and promising technologies and techniques are introduced to improve the security of IoT. This paper aims to provide an up-to-date vision of the current research topics related to IoT security. Initially, we introduce common elements and protocols of IoT to demystify the origins of threats in IoT. Then, we propose a taxonomy of IoT attacks and analyze the security vulnerabilities of IoT at different layers. Subsequently, we provide a comparison of recent security schemes based on emerging solutions including fog computing, edge computing, software-defined networking (SDN), blockchain, lightweight cryptography, homomorphic and searchable encryption, and machine learning. Finally, security challenges are discussed and future directions are highlighted for future interested researchers.

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Recent Security Trends in Internet of Things: A Comprehensive Survey

Lightweight cryptography in IoT networks: A survey

The Internet of Things (IoT) has continued gaining in popularity and importance in everyday life in recent years. However, this development does not only present advantages. Indeed, due to the number of sensitive and private data produced by IoT systems, they have become the new privileged targets for cyberattackers. At the same time, Machine Learning (ML) has gained a phenomenal success in various fields like telecommunications, transport or cybersecurity. Nonetheless, the application of ML can cause significant damage when put in the hands of an attacker. Contrary to many previous works, we do not focus on the potential contributions of ML in the IoT security systems. Indeed, this survey aims to provide a comprehensive overview of ML approaches to enable more effective and less detectable attacks. Thereby, the purpose of this article is to identify and discuss the advantages of the elaboration of ML attacks and the possible solutions already evoked in the literature. Firstly, we provide an identification of the main threats and potential attacks on IoT networks. Then, we investigate on cyberattacks integrating machine learning algorithms during the last few years and we provide future research directions, especially for jamming, side channel, false data injection and adversarial machine learning attacks. 

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How Machine Learning Changes the Nature of Cyberattacks on IoT Networks: A Survey

Internet of Things (IoT) have opened the door to a world of unlimited possibilities for implementations in varied sectors in society, but it also has many challenges. One of those challenges is security and privacy. IoT devices are more susceptible to security threats and attacks. Due to constraints of the IoT devices such as area, power, memory, etc., there is a lack of security solutions that are compatible with IoT devices and applications, which is leading this world of securely connected things to the “internet of insecure things.” A promising solution to this problem is going beyond the standard or classical techniques to implementing the security solutions in the hardware of the IoT device. The integration of emerging technologies in IoT networks, such as machine learning, blockchain, fog/edge/cloud computing, and quantum computing have added more vulnerable points in the network. This paper introduces a comprehensive study on IoT security threats and solutions. Additionally, this survey outlines how emerging technologies such as machine learning and blockchain are integrated in IoT, challenges resulted from this integration, and potential solutions to these challenges. The paper utilizes the 4-layer IoT architecture as a reference to identify security issues with corresponding solutions. 

A survey on security in internet of things with a focus on the impact of emerging technologies

IoT is becoming more common and popular due to its wide range of applications in various domains. They collect data from the real environment and transfer it over the networks. There are many challenges while deploying IoT in a real-world, varying from tiny sensors to servers. Security is considered as the number one challenge in IoT deployments, as most of the IoT devices are physically accessible in the real world and many of them are limited in resources (such as energy, memory, processing power and even physical space). In this paper, we are focusing on these resource-constrained IoT devices (such as RFID tags, sensors, smart cards, etc.) as securing them in such circumstances is a challenging task. The communication from such devices can be secured by a mean of lightweight cryptography, a lighter version of cryptography. More than fifty lightweight cryptography (plain encryption) algorithms are available in the market with a focus on a specific application(s), and another 57 algorithms have been submitted by the researchers to the NIST competition recently. To provide a holistic view of the area, in this paper, we have compared the existing algorithms in terms of implementation cost, hardware and software performances and attack resistance properties. Also, we have discussed the demand and a direction for new research in the area of lightweight cryptography to optimize balance amongst cost, performance and security.

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Lightweight Cryptography Algorithms for Resource-Constrained IoT Devices: A Review, Comparison and Research Opportunities

With the emergence of 5G, Internet of Things (IoT) has become a center of attraction for almost all industries due to its wide range of applications from various domains The explosive growth of industrial control processes and the industrial IoT, imposes unprecedented vulnerability to cyber threats in critical infrastructure through the interconnected systems This new security threats could be minimized by lightweight cryptography, a sub-branch of cryptography, especially derived for resource-constrained devices such as RFID tags, smart cards, wireless sensors, etc More than four dozens of lightweight cryptography algorithms have been proposed, designed for specific application(s) These algorithms exhibit diverse hardware and software performances in different circumstances This paper presents the performance comparison along with their reported cryptanalysis, mainly for lightweight block ciphers, and further shows new research directions to develop novel algorithms with right balance of cost, performance and security characteristics

Vishal A. Thakor

Papers

Lightweight Cryptography Algorithms for Resource-Constrained IoT Devices: A Review, Comparison and Research Opportunities

Lightweight Cryptography for IoT: A State-of-the-Art