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The rise of ad-blockers is viewed as an economic threat by online publishers, especially those who primarily rely on ad- vertising to support their services. To address this threat, publishers have started retaliating by employing ad-block…
Anomaly detection is an important task in network management. However, deploying intelligent alert systems in real-world large-scale networking systems is challenging when we take into account (i) scalability, (ii) data heterogeneity, and…
The simple security property in an information flow policy can be enforced by encrypting data objects and distributing an appropriate secret to each user. A user derives a suitable decryption key from the secret and publicly available…
According to recent studies, the vulnerability of state-of-the-art Neural Networks to adversarial input samples has increased drastically. A neural network is an intermediate path or technique by which a computer learns to perform tasks…
Blockchains have a two-sided reputation: they are praised for disrupting some of our institutions through innovative technology for good, yet notorious for being slow and expensive to use. In this work, we tackle this issue with…
In the era of data-driven economies, incentive systems and loyalty programs, have become ubiquitous in various sectors, including advertising, retail, travel, and financial services. While these systems offer advantages for both users and…
Detecting illicit nodes on blockchain networks is a valuable task for strengthening future regulation. Recent machine learning-based methods proposed to tackle the tasks are using some blockchain transaction datasets with a small portion of…
We propose a scheme to preserve the anonymity of users in proof-of-asset transactions. We assume bitcoin-like cryptocurrency systems in which a user must prove the strength of its assets (i.e., solvency), prior conducting further…
Although the bulk of the research in privacy and statistical disclosure control is designed for static data, more and more data are often collected as continuous streams, and extensions of popular privacy tools and models have been proposed…
Skeleton-based action recognition attracts practitioners and researchers due to the lightweight, compact nature of datasets. Compared with RGB-video-based action recognition, skeleton-based action recognition is a safer way to protect the…
In this work we address the question of efficiency of distributed computing in anonymous, congested and highly dynamic and not-always-connected networks/systems. More precisely, the system consists of an unknown number of anonymous nodes…
Authentication and authorization of a user's identity are generally done by the service providers or identity providers. However, these centralized systems limit the user's control of their own identity and are prone to massive data leaks…
At present, the cloud storage used in searchable symmetric encryption schemes (SSE) is provided in a private way, which cannot be seen as a true cloud. Moreover, the cloud server is thought to be credible, because it always returns the…
Blockchain is a novel technology that is rising a lot of interest in the industrial and re- search sectors because its properties of decentralisation, immutability and data integrity. Initially, the underlying consensus mechanism has been…
Applications of blockchain technologies got a lot of attention in recent years. They exceed beyond exchanging value and being a substitute for fiat money and traditional banking system. Nevertheless, being able to exchange value on a…
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…
Many service systems rely on verifiable identity-related information of their users. Manipulation and unwanted exposure of this privacy-relevant information, however, must at the same time be prevented and avoided. Peer-to-peer…
Operators of online social networks are increasingly sharing potentially sensitive information about users and their relationships with advertisers, application developers, and data-mining researchers. Privacy is typically protected by…
Decentralized unpermissioned peer-to-peer networks are inherently vulnerable to spam when they allow arbitrary participants to submit content to a common public index or registry; preventing this is difficult due to the absence of a central…
Whistleblower laws protect individuals who inform the public or an authority about governmental or corporate misconduct. Despite these laws, whistleblowers frequently risk reprisals and sites such as WikiLeaks emerged to provide a level of…