Results 1 to 10 of about 190,686 (266)
A privacy-preserving federated meta-learning framework for cross-project defect prediction in software systems [PDF]
Scientific ReportsSoftware defect prediction (SDP) is a critical task in software engineering, aiming to identify fault-prone modules before deployment. This paper introduces the Efficient Communication Federated Meta-Learning (ECFML) framework for cross-project defect ...
Jhansi Lakshmi Potharlanka +2 more
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Privacy concerns and protection behavior during the Covid-19 pandemic [PDF]
Problems and Perspectives in Management, 2022 This paper aims to analyze the protection behavior of employees while working remotely during the Covid-19 pandemic using online video chat software.
Ranjany Sundaram, Snehal Shetty
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Transactions on Cryptographic Hardware and Embedded Systems, 2023 In this paper we present the first formally verified implementations of Kyber and, to the best of our knowledge, the first such implementations of any post-quantum cryptosystem.
José Bacelar Almeida +11 more
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Scaling Exponents of Time Series Data: A Machine Learning Approach
Entropy, 2023 In this study, we present a novel approach to estimating the Hurst exponent of time series data using a variety of machine learning algorithms. The Hurst exponent is a crucial parameter in characterizing long-range dependence in time series, and ...
Sebastian Raubitzek +3 more
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Listening to bluetooth beacons for epidemic risk mitigation
Scientific Reports, 2022 The ongoing COVID-19 pandemic let to efforts to develop and deploy digital contact tracing systems to expedite contact tracing and risk notification. Unfortunately, the success of these systems has been limited, partly owing to poor interoperability with
Gilles Barthe +10 more
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Privacy Profiles and Amplification by Subsampling
The Journal of Privacy and Confidentiality, 2020 Differential privacy provides a robust quantifiable methodology to measure and control the privacy leakage of data analysis algorithms. A fundamental insight is that by forcing algorithms to be randomized, their privacy leakage can be characterized by ...
Borja Balle +2 more
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IEEE Access, 2020 The recent success of deep neural networks is attributed in part to large-scale well-labeled training data. However, with the ever-increasing size of modern datasets, combined with the difficulty of obtaining label information, semi-supervised learning ...
Xiaotao Wei +4 more
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Comprehensive quantitative analysis on privacy leak behavior. [PDF]
PLoS ONE, 2013 Privacy information is prone to be leaked by illegal software providers with various motivations. Privacy leak behavior has thus become an important research issue of cyber security.
Lejun Fan +5 more
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Perceptions of ICT Practitioners Regarding Software Privacy
Entropy, 2020 During software development activities, it is important for Information and Communication Technology (ICT) practitioners to know and understand practices and guidelines regarding information privacy, as software requirements must comply with data privacy
Edna Dias Canedo +4 more
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IET Software, 2021 This study argues the difference between security and privacy and outlines the concept of Privacy Debt as a new Technical Debt. Privacy is gaining momentum in any software system due to mandatory compliance with respect to laws and regulations. There are
Xabier Larrucea +2 more
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