IoT Security Techniques Based on Machine Learning: How Do IoT Devices Use AI to Enhance Security?

Xiao, Liang; Wan, Xiaoyue; Lu, Xiaozhen; Zhang, Yanyong; Wu, Di

doi:10.1109/msp.2018.2825478

Cited by 540 publications

(273 citation statements)

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“…[30][31][32][33] Several well-known attacks have been described in the literature. A more extensive discussion of attacks on IoT devices is beyond the scope of this paper but can be found in the recent literature.…”

Section: Common Attacks On Iot Devicesmentioning

confidence: 99%

“…[30][31][32][33] Several well-known attacks have been described in the literature. 30,35 For example, an attacker may use a remote execution service's vulnerability on an IoT device in order to install a trojan that will provide him or her access to the device. 34 The first approach aims to overwhelm the lightweight communication channel that is utilized.…”

Section: Common Attacks On Iot Devicesmentioning

confidence: 99%

“…Recently, several research efforts 30,[36][37][38][39] have started to apply machine learning techniques to detect malicious traffic data and behaviors of devices running in IoT environments. Consequently, we need efficient security controls that can be automated and quickly analyse and differentiate between benign and malicious IoT data.…”

Section: Machine Learning: An Opportunity For Improving Iot Securitymentioning

confidence: 99%

“…30,52,53 Thus, adapting such methods for improving IoT security at the network level is possible. The algorithms in this category enable the execution of multiple scenarios on the basis of action and state permutations that lead to variable outcomes.…”

Section: Reinforcement Learningmentioning

confidence: 99%

“…30 Give the seamless and ubiquitous connectivity of the IoT devices with physical space solutions against eavesdropping are likely to be effective if machine learning approaches are implemented. The more passive the actions of an attacker are, the more difficult it becomes to detect them.…”

Section: Eavesdropping Detectionmentioning

confidence: 99%

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Securing Internet of Things (IoT) with machine learning

Zeadally

Tsikerdekis

2019

Int J Communication

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Advances in hardware, software, communication, embedding computing technologies along with their decreasing costs and increasing performance have led to the emergence of the Internet of Things (IoT) paradigm. Today, several billions of Internet-connected devices are part of the IoT ecosystem.IoT devices have become an integral part of the information and communication technology (ICT) infrastructure that supports many of our daily activities. The security of these IoT devices has been receiving a lot of attention in recent years. Another major recent trend is the amount of data that is being produced every day which has reignited interest in technologies such as machine learning and artificial intelligence. We investigate the potential of machine learning techniques in enhancing the security of IoT devices. We focus on the deployment of supervised, unsupervised learning techniques, and reinforcement learning for both host-based and network-based security solutions in the IoT environment. Finally, we discuss some of the challenges of machine learning techniques that need to be addressed in order to effectively implement and deploy them so that they can better protect IoT devices. KEYWORDSattack, internet of things, machine learning, security

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Section: Common Attacks On Iot Devicesmentioning

confidence: 99%