@article {831,
	title = {Blockchain meets Internet of Things (IoT) forensics: A unified framework for IoT ecosystems},
	journal = {Internet of Things},
	year = {2023},
	month = {oct},
	pages = {100968},
	abstract = {<p>With the continuously increasing number of security incidents targeting sensors, embedded devices, and other electronics appliances and systems that comprise the so-called Internet of things (IoT), the field of IoT forensics emerged as a branch of digital forensics focusing on the investigation of attacks in the IoT ecosystem. Digital evidence authenticity, integrity, confidentiality, and privacy are among the factors affecting the investigation process in IoT forensics, which can be addressed by employing the blockchain as the means not only for the preservation of digital evidence, but also for other steps of a digital forensics investigation process. The high-level goal of the paper is three-fold: to establish a holistic IoT forensics process as a reference point against which blockchain integration patterns and best practices will be identified in order to yield a robust, widely accepted and scalable architecture of the blockchain-enabled solution; to integrate the blockchain with the proposed IoT forensics process for addressing the above challenges; and to evaluate the overall solution highlighting improvements and potential performance bottlenecks. The proposed blockchain-enabled platform leverages multi-access edge computing and has been implemented with Hyperledger Fabric on an extensive virtualized testbed providing a realistic smart home environment. A thorough evaluation was conducted with real cyber-attacks generating digital evidence at high rates for testing the platform{\textquoteright}s behavior at high load. The experimental results showed that the proposed platform achieved high throughput, excessively low latency, and zero error rate in the operation of the blockchain network.</p>
},
	keywords = {blockchain, cyber-security, Digital forensics, Edge computing, Internet of Things},
	doi = {10.1016/j.iot.2023.100968},
	url = {https://www.sciencedirect.com/science/article/pii/S2542660523002913},
	author = {Sotirios Brotsis and Konstantinos P. Grammatikakis and Dimitrios Kavallieros and Antonio I. Mazilu and Nicholas Kolokotronis and Konstantinos Limniotis and Costas Vassilakis}
}
@article {798,
	title = {On the Design of IoT Security: Analysis of Software Vulnerabilities for Smart Grids},
	journal = {Energies},
	volume = {14},
	year = {2021},
	month = {may},
	pages = {2818},
	abstract = {<p>The 5G communication network will underpin a vast number of new and emerging services, paving the way for unprecedented performance and capabilities in mobile networks. In this setting, the Internet of Things (IoT) will proliferate, and IoT devices will be included in many 5G application contexts, including the Smart Grid. Even though 5G technology has been designed by taking security into account, design provisions may be undermined by software-rooted vulnerabilities in IoT devices that allow threat actors to compromise the devices, demote confidentiality, integrity and availability, and even pose risks for the operation of the power grid critical infrastructures. In this paper, we assess the current state of the vulnerabilities in IoT software utilized in smart grid applications from a source code point of view. To that end, we identified and analyzed open-source software that is used in the power grid and the IoT domain that varies in characteristics and functionality, ranging from operating systems to communication protocols, allowing us to obtain a more complete view of the vulnerability landscape. The results of this study can be used in the domain of software development, to enhance the security of produced software, as well as in the domain of automated software testing, targeting improvements to vulnerability detection mechanisms, especially with a focus on the reduction of false positives.</p>
},
	keywords = {Internet of Things, robustness, security, software vulnerabilities},
	doi = {10.3390/en14102818},
	author = {Christos-Minas Mathas and Costas Vassilakis and Nicholas Kolokotronis and Charilaos C. Zarakovitis and Michail-Alexandros Kourtis}
}
