IoT security: Review, blockchain solutions, and open challenges

The blockchain technology has revolutionized the digital currency space with the pioneering cryptocurrency platform named Bitcoin. From an abstract perspective, a blockchain is a distributed ledger capable of maintaining an immutable log of transactions happening in a network. In recent years, this technology has attracted significant scientific interest in research areas beyond the financial sector, one of them being the Internet of Things (IoT). In this context, the blockchain is seen as the missing link toward building a truly decentralized, trustless, and secure environment for the IoT and, in this survey, we aim to shape a coherent and comprehensive picture of the current state-of-the-art efforts in this direction. We start with fundamental working principles of blockchains and how blockchain-based systems achieve the characteristics of decentralization, security, and auditability. From there, we build our narrative on the challenges posed by the current centralized IoT models, followed by recent advances made both in industry and research to solve these challenges and effectively use blockchains to provide a decentralized, secure medium for the IoT.

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Applications of Blockchains in the Internet of Things: A Comprehensive Survey

The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. IoT is one of the fastest developing fields in the history of computing, with an estimated 50 billion devices by the end of 2020. However, the crosscutting nature of IoT systems and the multidisciplinary components involved in the deployment of such systems have introduced new security challenges. Implementing security measures, such as encryption, authentication, access control, network and application security for IoT devices and their inherent vulnerabilities is ineffective. Therefore, existing security methods should be enhanced to effectively secure the IoT ecosystem. Machine learning and deep learning (ML/DL) have advanced considerably over the last few years, and machine intelligence has transitioned from laboratory novelty to practical machinery in several important applications. Consequently, ML/DL methods are important in transforming the security of IoT systems from merely facilitating secure communication between devices to security-based intelligence systems. The goal of this work is to provide a comprehensive survey of ML methods and recent advances in DL methods that can be used to develop enhanced security methods for IoT systems. IoT security threats that are related to inherent or newly introduced threats are presented, and various potential IoT system attack surfaces and the possible threats related to each surface are discussed. We then thoroughly review ML/DL methods for IoT security and present the opportunities, advantages and shortcomings of each method. We discuss the opportunities and challenges involved in applying ML/DL to IoT security. These opportunities and challenges can serve as potential future research directions.

A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security

Current research on Internet of Things (IoT) security: A survey

A Comprehensive Survey on Attacks, Security Issues and Blockchain Solutions for IoT and IIoT

Internet of Things security

Managing big RDF data in clouds: Challenges, opportunities, and solutions

Recently, the Internet of Things and building information modeling (IoT-BIM) has captured attention because of its wide range of applications in multiple domains communicating across different layers. The IoT-BIM consists of three layers, namely physical, network, and application layer. This paper provides and discusses security attacks countermeasure for each IoT-BIM layer. In this paper, we discuss various state-of-the-art IoT-BIM security frameworks and propose a unified security framework for IoT-BIM networks, called “Unified Federated Security Framework”. The proposed framework relies on fuzzy cognitive maps for modeling and evaluating trust relationships between the involved entities in federated identity management systems.

Fadele Ayotunde Alaba

Papers

Internet of Things security

Managing big RDF data in clouds: Challenges, opportunities, and solutions

A Conceptual Framework for Securing IoT-BIM