@conference {503,
	title = {Towards a Threat Model and Security Analysis for Data Cooperatives},
	booktitle = {19th International Conference on Security and Cryptography (SECRYPT 2022)},
	year = {2022},
	abstract = {<p>Data cooperative (called {\textquotedblleft}data coop{\textquotedblright} for short) is an emerging approach in the area of secure data management. It promises its users a better protection and control of their data, as compared to the traditional way of their handling by the data collectors (such as governments, big data companies, and others). However, for the success of data coops, existing challenges with respect to data management systems need to be adequately addressed. Especially, they concern terms of security and privacy, as well as the power imbalance between providers/owners and collectors of data. Designing a security and privacy model for a data coop requires a systematic threat modeling approach that identifies the security landscape, attack vectors, threats, and vulnerabilities, as well as the respective mitigation strategies. In this paper, we analyze the security of data cooperatives, identify potential security risks and threats, and suggest adequate countermeasures. We also discuss existing challenges that hinder the widespread adoption of data coops.\&nbsp;</p>
},
	keywords = {Cybersecurity, Data Cooperatives, Secure Data Management, Security and Privacy., Threat Model},
	doi = {10.5220/0011328700003283},
	author = {Salau, Abiola and Dantu, Ram and Morozov, Kirill and Upadhyay, Kritagya and Badruddoja, Syed}
}
@conference {565,
	title = {Trusted AI with Blockchain to Empower Metaverse},
	booktitle = {2022 Fourth International Conference on Blockchain Computing and Applications (BCCA)},
	year = {2022},
	abstract = {<p>The digital experience emerging in the virtual world is a reality with the advent of the metaverse. Augmented reality(AR), virtual reality(VR), extended reality(XR), and artificial intelligence(AI) algorithms would pave the way for an immersive experience for the users in the virtual space. However, the explosion of these technologies broaches new challenges to threaten the success of metaverse due to security risks. The blockchain technology augmented with AI promises to deliver a trusted metaverse for everyone. Nevertheless, smart contracts fail to produce a cognitive prediction, dissuading users from confiding in the metaverse. We arm smart contracts with intelligence to predict using AI algorithms. Moreover, we deploy the smart contracts on the Ethereum blockchain platform and produce a prediction accuracy of 95\% compared to Python scikit-learn-based predictions. Our results show that the prediction delay can obstruct the growth of metaverse applications to accept blockchain technologies. Furthermore, the limitation of blockchain technology can make integration unreasonable. Therefore, we discuss possible scalability solutions that can be part of our future work to help more metaverse applications adopt blockchain solutions.</p>
},
	doi = {10.1109/BCCA55292.2022.9922027},
	author = {Badruddoja, Syed and Dantu, Ram and He, Yanyan and Thompson, Mark and Salau, Abiola and Upadhyay, Kritagya}
}
