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1. Data Privacy for Big Automotive Data
Sammanfattning : In an age where data is becoming increasingly more valuable as itallows for data analysis and machine learning, big data has become ahot topic. With big data processing, analyses can be carried out onhuge amounts of user data. LÄS MER
2. Differential Privacy - A Balancing Act
Sammanfattning : Data privacy is an ever important aspect of data analyses. Historically, a plethora of privacy techniques have been introduced to protect data, but few have stood the test of time. LÄS MER
3. Towards Privacy Preserving Micro-data Analysis : A machine learning based perspective under prevailing privacy regulations
Sammanfattning : Machine learning (ML) has been employed in a wide variety of domains where micro-data (i.e., personal data) are used in the training process. LÄS MER
4. Secure and Privacy-Preserving Cloud-Assisted Computing
Sammanfattning : Smart devices such as smartphones, wearables, and smart appliances collect significant amounts of data and transmit them over the network forming the Internet of Things (IoT). Many applications in our daily lives (e.g., health, smart grid, traffic monitoring) involve IoT devices that often have low computational capabilities. LÄS MER
5. Measuring Apps' Privacy-Friendliness : Introducing transparency to apps' data access behavior
Sammanfattning : Mobile apps brought unprecedented convenience to everyday life, and nowadays, hardly any interactive service exists without having an interface through an app. The rich functionalities of apps rely on the pervasive capabilities of the mobile device, such as its cameras and other types of sensors. LÄS MER