Collaborative Fake Media Detection in a Trust-Aware Real-Time Distribution Network
نویسندگان
چکیده
Due to the increased incorporation of external sources media agencies face the challenge of providing high-trust media to their customers. Automatic image processing approaches still do not bridge the semantic gap to identify fakes. Complementary community-based approaches lack real-time media distribution for improved awareness and base trust on subjective opinions instead of objective actions. In this paper we propose a collaborative fake media detection approach addressing these challenges in form of a federated, trust-aware media distribution network. Starting from a realistic use case scenario we elicit requirements and present an XMPP-based and Web service-enhanced multimedia distribution network as solution. Finally, we sketch a Web-based fake media detection application powered by our network and its services.
منابع مشابه
Merging Similarity and Trust Based Social Networks to Enhance the Accuracy of Trust-Aware Recommender Systems
In recent years, collaborative filtering (CF) methods are important and widely accepted techniques are available for recommender systems. One of these techniques is user based that produces useful recommendations based on the similarity by the ratings of likeminded users. However, these systems suffer from several inherent shortcomings such as data sparsity and cold start problems. With the dev...
متن کاملDisTriB: Distributed Trust Management Model Based on Gossip Learning and Bayesian Networks in Collaborative Computing Systems
The interactions among peers in Peer-to-Peer systems as a distributed collaborative system are based on asynchronous and unreliable communications. Trust is an essential and facilitating component in these interactions specially in such uncertain environments. Various attacks are possible due to large-scale nature and openness of these systems that affects the trust. Peers has not enough inform...
متن کاملDisTriB: Distributed Trust Management Model Based on Gossip Learning and Bayesian Networks in Collaborative Computing Systems
The interactions among peers in Peer-to-Peer systems as a distributed collaborative system are based on asynchronous and unreliable communications. Trust is an essential and facilitating component in these interactions specially in such uncertain environments. Various attacks are possible due to large-scale nature and openness of these systems that affects the trust. Peers has not enough inform...
متن کاملA Collaborative Blood Distribution System in a Network of Hospitals based on their Normal and Emergency Requests: a Mathematical Model and Solution
Background and Objectives: A blood distribution network orchestrates distribution of safe blood products to hospitals. Blood shortage and blood wastage are two important factors which may affect efficiency of blood distribution network. Service delivery time is another factor that refers to the time interval between blood request by a hospital and transfusing it to the patient....
متن کاملDetection of Fake Accounts in Social Networks Based on One Class Classification
Detection of fake accounts on social networks is a challenging process. The previous methods in identification of fake accounts have not considered the strength of the users’ communications, hence reducing their efficiency. In this work, we are going to present a detection method based on the users’ similarities considering the network communications of the users. In the first step, similarity ...
متن کامل