Related papers: A Privacy-preserving Community-based P2P OSNs Usin…
We study the ON-OFF privacy problem. At each time, the user is interested in the latest message of one of $N$ sources. Moreover, the user is assumed to be incentivized to turn privacy ON or OFF whether he/she needs it or not. When privacy…
There has been work that exploits polynomial approximation to solve distributed nonconvex optimization problems involving univariate objectives. This idea facilitates arbitrarily precise global optimization without requiring local…
Reliable neural networks (NNs) provide important inference-time reliability guarantees such as fairness and robustness. Complementarily, privacy-preserving NN inference protects the privacy of client data. So far these two emerging areas…
Distributed broadcast encryption (DBE) is a variant of broadcast encryption (BE) that can efficiently transmit a message to a subset of users, in which users independently generate user private keys and user public keys instead of a central…
Privacy preservation is an important issue in today's context of extreme penetration of internet and mobile technologies. It is more important in the case of Wireless Sensor Networks (WSNs) where collected data often requires in-network…
In recent years, several studies proposed privacy-preserving algorithms for solving Distributed Constraint Optimization Problems (DCOPs). All of those studies assumed that agents do not collude. In this study we propose the first…
Data concerning the users and usage of Online Social Networks (OSNs) has become available externally, from public resources (e.g., user profiles), participation in OSNs (e.g., establishing relationships and recording transactions such as…
Cooperative spectrum sensing, despite its effectiveness in enabling dynamic spectrum access, suffers from location privacy threats, merely because secondary users (SUs)' sensing reports that need to be shared with a fusion center to make…
User reporting is an essential component of content moderation on many online platforms -- in particular, on end-to-end encrypted (E2EE) messaging platforms where platform operators cannot proactively inspect message contents. However,…
Recommender systems are a vital tool that helps us to overcome the information overload problem. They are being used by most e-commerce web sites and attract the interest of a broad scientific community. A recommender system uses data on…
In the era of social media and messaging applications, people are becoming increasingly aware of data privacy issues associated with such apps. Major messaging applications are moving towards end-to-end encryption (E2EE) to give their users…
Recommender systems have become a pervasive part of our daily online experience, and are one of the most widely used applications of artificial intelligence and machine learning. Therefore, regulations and requirements for trustworthy…
The proliferation of online biometric authentication has necessitated security requirements of biometric templates. The existing secure biometric authentication schemes feature a server-centric model, where a service provider maintains a…
In this paper we propose a data dissemination platform that supports data security and different privacy levels even when the platform and the data are hosted by untrusted infrastructures. The proposed system aims at enabling an application…
Transfer learning is an effective technique to improve a target recommender system with the knowledge from a source domain. Existing research focuses on the recommendation performance of the target domain while ignores the privacy leakage…
Since the advent of software defined networks ({SDN}), there have been many attempts to outsource the complex and costly local network functionality, i.e. the middlebox, to the cloud in the same way as outsourcing computation and storage.…
In the intricate dance of multi-agent systems, achieving average consensus is not just vital--it is the backbone of their functionality. In conventional average consensus algorithms, all agents reach an agreement by individual calculations…
Most previous works in privacy of Online Social Networks (OSN) focus on a restricted scenario of using one type of information to infer another type of information or using only static profile data such as username, profile picture or home…
Social networks, instant messages and file sharing systems are common communication means among friends, families, coworkers, etc. Due to concerns of personal privacy, identify thefts, data misuse, freedom of speech and government…
Privacy leaks are an unfortunate and an integral part of the current Internet domain name resolution. Each DNS query generated by a user reveals -- to one or more DNS servers -- the origin and target of that query. Over time, a user's…