IoT is a network of interconnected devices over the internet. The emerging trends and challenges in IoT security research are discussed below.
Here are emerging trends in IoT security research
1. AI and Edge Computing
The idea of edge computing is processing data close to the data source, at the edge of the network, as opposed to in the cloud. This can improve security and privacy while lowering latency, bandwidth, and consumption of energy. AI enhances the effectiveness, productivity, and performance of IoT systems. But edge computing and Artificial Intelligence (AI) also bring new hazards and security issues for the Internet of Things devices. For instance, edge equipment could be more vulnerable to physical assaults or have fewer resources and ability to deploy security measures. AI algorithms might provide biassed or inaccurate results, or they could be subject to adversarial assaults such as data evasion or poisoning. In addition to developing strategies and instruments to safeguard and validate edge devices and AI models, IoT security research must address the dangers and security concerns associated with edge computing and AI in IoT systems.
2. DLT and Blockchain
Blockchain and DLTs enable the creation and maintenance of a decentralized, distributed, and unchangeable record of transactions or data. IoT systems may benefit from trust, transparency, accountability, and security thanks to blockchain and DLT. For instance, smart contracts, identity management, access control, and safe and verifiable data exchange between IoT devices and stakeholders may all be made possible by blockchain and DLT. Blockchain and distributed ledger technology (DLT), however, also provide obstacles and constraints for IoT security research. For instance, blockchain and DLT could need a lot of energy and resources, or they might have problems with scalability, performance, and interoperability. Blockchain and DLT may give rise to ethical issues. Research on IoT security must tackle the difficulties and constraints posed by blockchain and DLT in IoT systems, as well as investigate the best ways to develop and apply these technologies to improve IoT security.
Here are emerging challenges in IoT security research
1. Attack Surface and the Degree of Complexity
IoT devices, characterized by their hardware, software, functionality, and communication protocols, can communicate intricately and dynamically with users, cloud services, and other devices. Because of this, it is challenging to locate and guard against all potential points of entry and weaknesses that an attacker may exploit. To build and implement security mechanisms that can handle the heterogeneity and scalability of IoT settings, IoT security research must create techniques and tools for analyzing and modelling the attack surface and complexity of IoT systems.
2. Protection of Data and Privacy
Sensitive and private data, including location, preferences, behaviour, and health records, can be found in IoT data. This data may be vulnerable to hostile assaults, shoddy encryption, or unapproved access, alteration, or disclosure. Issues with IoT data privacy and protection need to be addressed, and security research needs to make sure that user preferences, consent, and legal and ethical requirements are all followed. To allow consumers transparency and control over their data, IoT security research must also take into account the trade-offs between privacy and functionality.
Here are the neglected but equally important factors of Internet of Things (IoT) security research
1. Human Involvement and User Experience
The adoption, acceptability, and behaviour of IoT users and stakeholders are influenced by human factors and user experience, making them essential components of IoT security research. Users may exchange security for convenience or utility, and they may have varying degrees of awareness, expertise, motivation, and expectations surrounding IoT security. Consequently, user-centric, user-friendly, and user-empowering IoT security solutions should be designed and evaluated by IoT security research taking these characteristics into account.
