Privacy-preserving incremental data dissemination
نویسندگان
چکیده
منابع مشابه
Privacy-preserving incremental data dissemination
Although the k-anonymity and `-diversity models have led to a number of valuable privacy-protecting techniques and algorithms, the existing solutions are currently limited to static data release. That is, it is assumed that a complete dataset is available at the time of data release. This assumption implies a significant shortcoming, as in many applications data collection is rather a continual...
متن کاملA Scheme for Privacy - preserving Data Dissemination
Low-cost and reliable mutual anonymity protocols in peer-to-peer networks, " IEEE Trans. Freenet: A distributed anonymous information storage and retrieval system, " in Proc. Work-[21] J. Kong and X. Hong, " ANODR: Anonymous on demand routing with untraceable routes for mobile ad-hoc networks, " in Proc. 4th ACM Int. Cooperation of nodes, " extended abstract in L. Buttyàn and Hubaux (eds.), " R...
متن کاملTowards Privacy-Preserving Data Dissemination in Crowd-Sensing Middleware Platform
Crowd-sensing, also known as mobile crowdsourcing, is a growing research topic, which consists in engaging end users in the process of gathering physical measurements in the field. While the democratization of such middleware platforms opens the venue for the observation of phenomenon at scale, it may also raise key issues about the privacy of end users involved in the gathering process. In thi...
متن کاملPrivacy-Preserving Incremental Bayesian Network Learning
Bayesian Networks (BNs) have received significant attention in various academic and industrial applications, such as modeling knowledge in image processing, engineering, medicine and bio-informatics. Preserving the privacy of sensitive data, owned by different parties, is often a critical issue. However, in many practical applications, BNs must train from data that gradually becomes available a...
متن کاملIncremental learning of privacy-preserving Bayesian networks
Bayesian Networks (BNs) have received significant attention in various academic and industrial applications, such as modeling knowledge in image processing, engineering, medicine and bio-informatics. Preserving the privacy of sensitive data, owned by different parties, is often a critical issue. However, in many practical applications, BNs must train from data that gradually becomes available a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Computer Security
سال: 2009
ISSN: 1875-8924,0926-227X
DOI: 10.3233/jcs-2009-0316