Essays about: "Information privacy"
Showing result 21 - 25 of 446 essays containing the words Information privacy.
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21. Privacy-preserving Authentication in Participatory Sensing Systems : An attribute based authentication solution with sensor requirement enforcement.
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Participatory Sensing Systems (PSS) are a type of Mobile Crowdsensing System where users voluntarily participate in contributing information. Task initiators create tasks, targeting specific data that needs to be gathered by the users’ device sensors. READ MORE
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22. Towards Building Privacy-Preserving Language Models: Challenges and Insights in Adapting PrivGAN for Generation of Synthetic Clinical Text
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : The growing development of artificial intelligence (AI), particularly neural networks, is transforming applications of AI in healthcare, yet it raises significant privacy concerns due to potential data leakage. As neural networks memorise training data, they may inadvertently expose sensitive clinical data to privacy breaches, which can engender serious repercussions like identity theft, fraud, and harmful medical errors. READ MORE
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23. A SYSTEMATIC REVIEW OF ATTRIBUTE-BASED ENCRYPTION FOR SECURE DATA SHARING IN IoT ENVIRONMENT.
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Internet of Things (IoT) refers to a network of global and interrelated computing devices that connects humans and machines. It connects anything that has access to the internet and creates an avenue for data and information exchange. READ MORE
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24. Development guidelines for increased consumer privacy - Privacy in Home Assistants
University essay from Blekinge Tekniska Högskola/Institutionen för programvaruteknikAbstract : Research has shown that people are generally unaware of what information manufacturers gather and store about them via their IoT-devices. All they know is that there may be some collection of information. READ MORE
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25. Confidential Federated Learning with Homomorphic Encryption
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Federated Learning (FL), one variant of Machine Learning (ML) technology, has emerged as a prevalent method for multiple parties to collaboratively train ML models in a distributed manner with the help of a central server normally supplied by a Cloud Service Provider (CSP). Nevertheless, many existing vulnerabilities pose a threat to the advantages of FL and cause potential risks to data security and privacy, such as data leakage, misuse of the central server, or the threat of eavesdroppers illicitly seeking sensitive information. READ MORE
