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Register a new userWhats in Your Wallet? Privacy and Security Issues in Web 3.0
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Added by
Philipp Winter
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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Much of the recent excitement around decentralized finance (DeFi) comes from hopes that DeFi can be a secure, private, less centralized alternative to traditional finance systems but the accuracy of these hopes has to date been understudied; people moving to DeFi sites to improve their privacy and security may actually end up with less of both. In this work, we improve the state of DeFi by conducting the first measurement of the privacy and security properties of popular DeFi applications. We find that DeFi applications suffer from the same kinds of privacy and security risks that frequent other parts of the Web. For example, we find that one common tracker has the ability to record Ethereum addresses on over 56% of websites analyzed. Further, we find that many trackers on DeFi sites can trivially link a users Ethereum address with PII (e.g., name or demographic information) or phish users. This work also proposes remedies to the vulnerabilities we identify, in the form of improvements to the most common cryptocurrency wallet. Our wallet modification replaces the users real Ethereum address with site-specific addresses, making it harder for DeFi sites and third parties to (i) learn the users real address and (ii) track them across sites.
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The synergy between the cloud and the IoT has emerged largely due to the cloud having attributes which directly benefit the IoT and enable its continued growth. IoT adopting Cloud services has brought new security challenges. In this book chapter, we pursue two main goals: 1) to analyse the different components of Cloud computing and the IoT and 2) to present security and privacy problems that these systems face. We thoroughly investigate current security and privacy preservation solutions that exist in this area, with an eye on the Industrial Internet of Things, discuss open issues and propose future directions
This paper is a general survey of all the security issues existing in the Internet of Things (IoT) along with an analysis of the privacy issues that an end-user may face as a consequence of the spread of IoT. The majority of the survey is focused on the security loopholes arising out of the information exchange technologies used in Internet of Things. No countermeasure to the security drawbacks has been analyzed in the paper.
Additive manufacturing (AM) is growing as fast as anyone can imagine, and it is now a multi-billion-dollar industry. AM becomes popular in a variety of sectors, such as automotive, aerospace, biomedical, and pharmaceutical, for producing parts/ components/ subsystems. However, current AM technologies can face vast risks of security issues and privacy loss. For the security of AM process, many researchers are working on the defense mechanism to countermeasure such security concerns and finding efficient ways to eliminate those risks. Researchers have also been conducting experiments to establish a secure framework for the users privacy and security components. This survey consists of four sections. In the first section, we will explore the relevant limitations of additive manufacturing in terms of printing capability, security, and possible solutions. The second section will present different kinds of attacks on AM and their effects. The next part will analyze and discuss the mechanisms and frameworks for access control and authentication for AM devices. The final section examines the security issues in various industrial sectors and provides the observations on the security of the additive manufacturing process.
This paper embodies the usage of Big Data in Healthcare. It is important to note that big data in terms of Architecture and implementation might be or has already or will continue to assist the continuous growth in the field of healthcare. The main important aspects of this study are the general importance of big data in healthcare, the positives big data will help tackle and enhance in this field and not to also forget to mention the tremendous downside big data has on healthcare that is still needed to improve or putting extensive research on. We believe there is still a long way in which institutions and individuals understand the hidden truth about big data. We have highlighted the various ways one could be confidently relied on big data and on the other hand highlighted the weighted importance of big problem big data and expected solutions.
Voice assistants have become quite popular lately while in parallel they are an important part of smarthome systems. Through their voice assistants, users can perform various tasks, control other devices and enjoy third party services. The assistants are part of a wider ecosystem. Their function relies on the users voice commands, received through original voice assistant devices or companion applications for smartphones and tablets, which are then sent through the internet to the vendor cloud services and are translated into commands. These commands are then transferred to other applications and services. As this huge volume of data, and mainly personal data of the user, moves around the voice assistant ecosystem, there are several places where personal data is temporarily or permanently stored and thus it is easy for a cyber attacker to tamper with this data, bringing forward major privacy issues. In our work we present the types and location of such personal data artifacts within the ecosystems of three popular voice assistants, after having set up our own testbed, and using IoT forensic procedures. Our privacy evaluation includes the companion apps of the assistants, as we also compare the permissions they require before their installation on an Android device.
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