01764nas a2200205   4500008004100000245007100041210006900112520107300181653001801254653002201272653002701294653002601321653001701347100001801364700001501382700002001397700002301417700002101440856009701461       2022                        eng d00aTowards a Threat Model and Security Analysis for Data Cooperatives0 aTowards a Threat Model and Security Analysis for Data Cooperativ3 a<p>Data cooperative (called “data coop” 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>
10aCybersecurity10aData Cooperatives10aSecure Data Management10aSecurity and Privacy.10aThreat Model1 aSalau, Abiola1 aDantu, Ram1 aMorozov, Kirill1 aUpadhyay, Kritagya1 aBadruddoja, Syed  uhttps://nsl.cse.unt.edu/content/towards-threat-model-and-security-analysis-data-cooperatives01752nas a2200157   4500008004100000245005200041210005200093520126200145100002101407700001501428700001501443700001901458700001801477700002301495856007601518       2022                        eng d00aTrusted AI with Blockchain to Empower Metaverse0 aTrusted AI with Blockchain to Empower Metaverse3 a<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>
1 aBadruddoja, Syed1 aDantu, Ram1 aHe, Yanyan1 aThompson, Mark1 aSalau, Abiola1 aUpadhyay, Kritagya  uhttps://nsl.cse.unt.edu/content/trusted-ai-blockchain-empower-metaverse