Related papers: Machine Learning-Enabled IoT Security: Open Issues…
The number of connected smart devices has been increasing exponentially for different Internet-of-Things (IoT) applications. Security has been a long run challenge in the IoT systems which has many attack vectors, security flaws and…
The Internet of Medical Things (IoMT) has revolutionized the healthcare industry by enabling physiological data collection using sensors, which are transmitted to remote servers for continuous analysis by physicians and healthcare…
As the number of cyber-attacks is increasing, cybersecurity is evolving to a key concern for any business. Artificial Intelligence (AI) and Machine Learning (ML) (in particular Deep Learning - DL) can be leveraged as key enabling…
The growing deployment of Internet of Things (IoT) devices in smart cities and industrial environments increases vulnerability to stealthy, multi-stage advanced persistent threats (APTs) that exploit wireless communication. Detection is…
Machine learning (ML) technologies are emerging in the Internet of Things (IoT) to provision intelligent services. This survey moves beyond existing ML algorithms and cloud-driven design to investigate the less-explored systems, scaling and…
The rapid proliferation of the Internet of Things has intensified demand for robust privacy-preserving machine learning mechanisms to safeguard sensitive data generated by large-scale, heterogeneous, and resource-constrained devices. Unlike…
Threat modeling and risk assessments are common ways to identify, estimate, and prioritize risk to national, organizational, and individual operations and assets. Several threat modeling and risk assessment approaches have been proposed…
The Internet of Things (IoT) has evolved from a novel technology to an integral part of our everyday lives. It encompasses a multitude of heterogeneous devices that collect valuable data through various sensors. The sheer volume of these…
Internet of Things (IoT) is the interconnection of heterogeneous smart devices through the Internet with diverse application areas. The huge number of smart devices and the complexity of networks has made it impossible to secure the data…
This work explores the use of machine learning techniques on an Internet-of-Things firmware dataset to detect malicious attempts to infect edge devices or subsequently corrupt an entire network. Firmware updates are uncommon in IoT devices;…
Consumer Internet of Things (IoT) devices are increasingly common, from smart speakers to security cameras, in homes. Along with their benefits come potential privacy and security threats. To limit these threats a number of commercial…
Malware intrusion is problematic for Internet of Things (IoT) and Artificial Intelligence of Things (AIoT) devices as they often reside in an ecosystem of connected devices, such as a smart home. If any devices are infected, the whole…
The security pitfalls of IoT devices make it easy for the attackers to exploit the IoT devices and make them a part of a botnet. Once hundreds of thousands of IoT devices are compromised and become the part of a botnet, the attackers use…
The integration of Internet of Things (IoT) technology in various domains has led to operational advancements, but it has also introduced new vulnerabilities to cybersecurity threats, as evidenced by recent widespread cyberattacks on IoT…
Machine Learning (ML) techniques have been rapidly adopted by smart Cyber-Physical Systems (CPS) and Internet-of-Things (IoT) due to their powerful decision-making capabilities. However, they are vulnerable to various security and…
In the landscape of the Internet of Things (IoT), transforming various industries, our research addresses the growing connectivity and security challenges, including interoperability and standardized protocols. Despite the anticipated…
The use of Machine Learning (ML) models in cybersecurity solutions requires high-quality data that is stripped of redundant, missing, and noisy information. By selecting the most relevant features, data integrity and model efficiency can be…
The rapid expansion of Internet of Things (IoT) devices has increased the risk of cyber-attacks, making effective detection essential for securing IoT networks. This work introduces a novel approach combining Self-Organizing Maps (SOMs),…
The Internet of Things (IoT) envisions pervasive, connected, and smart nodes interacting autonomously while offering all sorts of services. Wide distribution, openness and relatively high processing power of IoT objects made them an ideal…
Many IoT devices are vulnerable to attacks due to flawed security designs and lacking mechanisms for firmware updates or patches to eliminate the security vulnerabilities. Device-type identification combined with data from vulnerability…