Results 71 to 80 of about 647,604 (320)
Jiàoyù zīliào yǔ túshūguǎn xué, 2023 資訊隱私權是現代人生活中重要權利之一，高等教育階段學生對資訊隱私之個人資料保護法（簡稱個資法）的理解程度，是落實此權利之基礎。本研究設計情境案例問卷，蒐集到745 位高等教育學生對個資法理解之情形，結果顯示：1. 高度理解部分為「通知義務」。2. 中度理解是關於公務機關之定義，以及委託者負擔損害賠償責任。3.
Mei-Lien Hsueh, Chien Chou
doaj +1 more source
Revisiting the Multiple-of Property for SKINNY: The Exact Computation of the Number of Right Pairs
IEEE AccessAt EUROCRYPT 2017, Grassi et al. proposed the multiple-of-8 property for 5-round $\mathtt {AES}$ , where the number $n$ of right pairs is a multiple of 8. At ToSC 2019, Boura et al.
Hanbeom Shin +6 more
doaj +1 more source
On Maximal Correlation, Mutual Information and Data Privacy [PDF]
arXiv, 2015 The rate-privacy function is defined in \cite{Asoodeh} as a tradeoff between privacy and utility in a distributed private data system in which both privacy and utility are measured using mutual information. Here, we use maximal correlation in lieu of mutual information in the privacy constraint.
arxiv
Constructing Privacy Channels from Information Channels [PDF]
arXiv, 2019 Data privacy protection studies how to query a dataset while preserving the privacy of individuals whose sensitive information is contained in the dataset. The information privacy model protects the privacy of an individual by using a noisy channel, called privacy channel, to filter out most information of the individual from the query's output. This
arxiv
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information [PDF]
arXiv, 2023 Privacy-preserving instance encoding aims to encode raw data as feature vectors without revealing their privacy-sensitive information. When designed properly, these encodings can be used for downstream ML applications such as training and inference with limited privacy risk.
arxiv
Frontiers in Psychology, 2018 As the development of the Internet and social media has led to pervasive data collection and usage practices, consumers’ privacy concerns have increasingly grown stronger.
Jasmin Mahmoodi +6 more
doaj +1 more source
Comparing Threshold Selection Methods for Network Anomaly Detection
IEEE AccessThe use of unsupervised machine learning models for anomaly detection is a common thing nowadays. While many research papers focus on improving and testing these models, there is a lack of those that deal with threshold selection, which is an important ...
Adrian Komadina +3 more
doaj +1 more source
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Background This study aims to develop a novel predictive model for determining human papillomavirus (HPV) presence in oropharyngeal cancer using computed tomography (CT). Current image‐based HPV prediction methods are hindered by high computational demands or suboptimal performance.
Junhua Chen +3 more
wiley +1 more source
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Current radiotherapy practices rely on manual contouring of CT scans, which is time‐consuming, prone to variability, and requires highly trained experts. There is a need for more efficient and consistent contouring methods. This study evaluated the performance of the Varian Ethos AI auto‐contouring tool to assess its potential integration into
Robert N. Finnegan +6 more
wiley +1 more source
Privacy-Preserving Policy Synthesis in Markov Decision Processes [PDF]
arXiv, 2020 In decision-making problems, the actions of an agent may reveal sensitive information that drives its decisions. For instance, a corporation's investment decisions may reveal its sensitive knowledge about market dynamics. To prevent this type of information leakage, we introduce a policy synthesis algorithm that protects the privacy of the transition ...
arxiv