相关论文: FakeSafe: Human Level Data Protection by Disinform…

In this digital era, our lives highly depend on the internet and worldwide technology. Wide usage of technology and platforms of communication makes our lives better and easier. But on the other side it carries out some security issues and…

The wide spread of false information online including misinformation and disinformation has become a major problem for our highly digitised and globalised society. A lot of research has been done to better understand different aspects of…

Scientific collaborations benefit from collaborative learning of distributed sources, but remain difficult to achieve when data are sensitive. In recent years, privacy preserving techniques have been widely studied to analyze distributed…

Security monitoring via ubiquitous cameras and their more extended in intelligent buildings stand to gain from advances in signal processing and machine learning. While these innovative and ground-breaking applications can be considered as…

Data mining is also being useful to give solutions for invasion finding and auditing. While data mining has several applications in protection, there are also serious privacy fears. Because of email mining, even inexperienced users can…

Deep Neural Networks (DNNs) are susceptible to model stealing attacks, which allows a data-limited adversary with no knowledge of the training dataset to clone the functionality of a target model, just by using black-box query access. Such…

Power consumption data is very useful as it allows to optimize power grids, detect anomalies and prevent failures, on top of being useful for diverse research purposes. However, the use of power consumption data raises significant privacy…

Privacy Shielding against Mass Surveillance provides a step by step tactical approach to protecting the privacy of all the users of the internet from mass surveillance programs by the governments and other state agencies. Protection of…

Smart environments integrate Information and Communication Technologies (ICT) into devices, vehicles, buildings and cities to offer an increased quality of life, energy efficiency and economical sustainability. In this perspective, the…

Cyberattacks on both databases and critical infrastructure have threatened public and private sectors. Ubiquitous tracking and wearable computing have infringed upon privacy. Advocates and engineers have recently proposed using defensive…

In the fight against tax evaders and other cheats, governments seek to gather more information about their citizens. In this paper we claim that this increased transparency, combined with ineptitude, or corruption, can lead to widespread…

Data is used widely by service providers as input to inference systems to perform decision making for authorized tasks. The raw data however allows a service provider to infer other sensitive information it has not been authorized for. We…

In distributed networks, calculating the maximum element is a fundamental task in data analysis, known as the distributed maximum consensus problem. However, the sensitive nature of the data involved makes privacy protection essential.…

With the rise of cameras and smart sensors, humanity generates an exponential amount of data. This valuable information, including underrepresented cases like AI in medical settings, can fuel new deep-learning tools. However, data…

Credit risk modeling has permeated our everyday life. Most banks and financial companies use this technique to model their clients' trustworthiness. While machine learning is increasingly used in this field, the resulting large-scale…

While becoming more and more present in our every day lives, services that operate on users' locations or location trajectories suffer from general fear of misappropriation of the transmitted location data. Several works have investigated…

Local Differential Privacy (LDP) protocols enable an untrusted data collector to perform privacy-preserving data analytics. In particular, each user locally perturbs its data to preserve privacy before sending it to the data collector, who…

Federated Learning (FL) systems are gaining popularity as a solution to training Machine Learning (ML) models from large-scale user data collected on personal devices (e.g., smartphones) without their raw data leaving the device. At the…

The widespread adoption of face recognition has led to increasing privacy concerns, as unauthorized access to face images can expose sensitive personal information. This paper explores face image protection against viewing and recovery…

In today's highly connected society, we are constantly asked to provide personal information to retailers, voter surveys, medical professionals, and other data collection efforts. The collected data is stored in large data warehouses.…