A Survey of Security Challenges, Attacks Taxonomy and Advanced Countermeasures in the Internet of Things

Abstract

Internet of Things (IoT) facilitates the integration between objects and different sensors to provide communication among them without human intervention. However, the extensive demand for IoT and its various applications has continued to grow, coupled with the need to achieve foolproof security requirements. IoT produces a vast amount of data under several constraints such as low processor, power, and memory. These constraints, along with the invaluable data produced by IoT devices, make IoT vulnerable to various security attacks. This paper presents an overview of IoT, its well-known system architecture, enabling technologies, and discusses security challenges and goals. Furthermore, we analyze security vulnerabilities and provide state-of-the-art security taxonomy. The taxonomy of the most relevant and current IoT security attacks is presented for application, network, and physical layers. While most other surveys studied one of the areas of security measures, this study considers and reports on the most advanced security countermeasures within the areas of autonomic, encryption, and learning-based approaches. Additionally, we uncover security challenges that may be met by the research community regarding security implementation in heterogeneous IoT environment. Finally, we provide different visions about possible security solutions and future research directions.

Keywords

• Attacks
• countermeasures
• encryption
• Internet of Things
• IoT architecture
• learning-based algorithm