相关论文: Privacy-preserving targeted mobile advertising: A …
Privacy-preservation policies are guidelines formulated to protect data providers private data. Previous privacy-preservation methodologies have addressed privacy in which data are permanently stored in repositories and disconnected from…
Targeted advertising has transformed the marketing landscape for a wide variety of businesses, by creating new opportunities for advertisers to reach prospective customers by delivering personalised ads, using an infrastructure of a number…
Modern distributed applications in healthcare, supply chain, and the Internet of Things handle a large amount of data in a diverse application setting with multiple stakeholders. Such applications leverage advanced artificial intelligence…
Privacy preservation is a big concern for various sectors. To protect individual user data, one emerging technology is differential privacy. However, it still has limitations for datasets with frequent queries, such as the fast accumulation…
Cross-institutional healthcare predictive modeling can accelerate research and facilitate quality improvement initiatives, and thus is important for national healthcare delivery priorities. For example, a model that predicts risk of…
Recommender systems have been widely used in different application domains including energy-preservation, e-commerce, healthcare, social media, etc. Such applications require the analysis and mining of massive amounts of various types of…
Blockchain has received a widespread attention because of its decentralized, tamper-proof, and transparent nature. Blockchain works over the principle of distributed, secured, and shared ledger, which is used to record, and track data…
An increasing amount of users' sensitive information is now being collected for analytics purposes. To protect users' privacy, differential privacy has been widely studied in the literature. Specifically, a differentially private algorithm…
In the current connected world - Websites, Mobile Apps, IoT Devices collect a large volume of users' personally identifiable activity data. These collected data is used for varied purposes of analytics, marketing, personalization of…
Electronic government (e-government) uses information and communication technologies to deliver public services to individuals and organisations effectively, efficiently and transparently. E-government is one of the most complex systems…
Online mobile advertising ecosystems provide advertising and analytics services that collect, aggregate, process, and trade a rich amount of consumers' personal data and carry out interest-based ad targeting, which raised serious privacy…
Searching for available parking spaces is a major problem for drivers especially in big crowded cities, causing traffic congestion and air pollution, and wasting drivers' time. Smart parking systems are a novel solution to enable drivers to…
Free content and services on the Web are often supported by ads. However, with the proliferation of intrusive and privacy-invasive ads, a significant proportion of users have started to use ad blockers. As existing ad blockers are radical…
Retail energy markets are increasingly consumer-oriented, thanks to a growing number of energy plans offered by a plethora of energy suppliers, retailers and intermediaries. To maximize the benefits of competitive retail energy markets,…
The popularity and applicability of mobile crowdsensing applications are continuously increasing due to the widespread of mobile devices and their sensing and processing capabilities. However, we need to offer appropriate incentives to the…
This paper explores how ad platforms can utilize Bayesian persuasion within blockchain-based auction systems to strategically influence advertiser behavior despite increased transparency. By integrating game-theoretic models with machine…
For the modern world where data is becoming one of the most valuable assets, robust data privacy policies rooted in the fundamental infrastructure of networks and applications are becoming an even bigger necessity to secure sensitive user…
Blockchain is a linearly linked, distributed, and very robust data structure. Originally proposed as part of the Bitcoin distributed stack, it found a number of applications in a number of fields, most notably in smart contracts, social…
Federated learning is a distributed mechanism that trained large-scale neural network models with the participation of multiple clients and data remains on their devices, only sharing the local model updates. With this feature, federated…
Recommendation systems form the center piece of a rapidly growing trillion dollar online advertisement industry. Even with numerous optimizations and approximations, collaborative filtering (CF) based approaches require real-time…