Analysis of Tizen Security Model and Ways of Bypassing It on Smart TV Platform

Majchrowicz, Michał; Duch, Piotr

doi:10.3390/app112412031

Cited by 2 publications

(1 citation statement)

References 38 publications

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“…These devices were secure against DDoS or DNS attacks but used unencrypted communication and allowed simple passwords [19,20]. Ethical hacking on smart televisions using Tizen Linux in 2021 resulted in the possibility of root-shell execution, even though Tizen's security mechanisms were active [21].…”

Section: Cybersecurity Measuresmentioning

confidence: 99%

Security Awareness in Smart Homes and Internet of Things Networks through Swarm-Based Cybersecurity Penetration Testing

Schiller,

Caulkins,

et al. 2023

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Internet of Things (IoT) devices are common in today’s computer networks. These devices can be computationally powerful, yet prone to cybersecurity exploitation. To remedy these growing security weaknesses, this work proposes a new artificial intelligence method that makes these IoT networks safer through the use of autonomous, swarm-based cybersecurity penetration testing. In this work, the introduced Particle Swarm Optimization (PSO) penetration testing technique is compared against traditional linear and queue-based approaches to find vulnerabilities in smart homes and IoT networks. To evaluate the effectiveness of the PSO approach, a network simulator is used to simulate smart home networks of two scales: a small, home network and a large, commercial-sized network. These experiments demonstrate that the swarm-based algorithms detect vulnerabilities significantly faster than the linear algorithms. The presented findings support the case that autonomous and swarm-based penetration testing in a network could be used to render more secure IoT networks in the future. This approach can affect private households with smart home networks, settings within the Industrial Internet of Things (IIoT), and military environments.

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Section: Cybersecurity Measuresmentioning

confidence: 99%