Article
Computer Science, Information Systems
Kha Dinh Duy, Hojoon Lee
Summary: Demand for data-intensive workloads and confidential computing is shaping the future of cloud computing. In this article, a novel design called se-pim is presented, which utilizes Processing-In-Memory (PIM) as a data-intensive confidential computing accelerator. By bringing computation closer to memory, se-pim achieves highly efficient large data computation. The evaluation shows that se-pim provides secure computation offloading with negligible performance overhead compared to the baseline PIM model.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Editorial Material
Cardiac & Cardiovascular Systems
Nina S. Stachenfeld, Lacy M. Alexander
Summary: Equity is crucial for improving the quality of scientific professional societies and enhancing leadership diversity. Efforts to improve gender equity contribute to inclusivity and a governance that reflects the membership.
AMERICAN JOURNAL OF PHYSIOLOGY-HEART AND CIRCULATORY PHYSIOLOGY
(2022)
News Item
Physics, Multidisciplinary
David Kramer
Summary: Although quantum computers are still years away, NIST is finalizing new encryption standards to replace current vulnerable protections.
Article
Multidisciplinary Sciences
Samantha S. R. Crossfield, Kieran Zucker, Paul Baxter, Penny Wright, Jon Fistein, Alex F. Markham, Mark Birkin, Adam W. Glaser, Geoff Hall
Summary: The use of healthcare data in research has the potential to contribute significantly to knowledge generation and service improvement. However, there are legal and ethical concerns regarding confidentiality, privacy, and data protection rights. This study aims to define an approach for creating an anonymous research dataset that addresses these concerns and provide a case study for its utilization.
Article
Geriatrics & Gerontology
Ming Zhao, Shuo-Tsung Chen, Tzu-Li Chen, Shu-Yi Tu, Cheng-Ta Yeh, Fang-Yu Lin, Hao-Chun Lu
Summary: With the aging society, healthcare and elderly care have become the focus of medical care, especially for the elderly with dementia. This study proposes an intelligent healthcare system that hides patients' confidential data in electrocardiogram (ECG) signals. By optimizing the quality of the embedded ECG signals and using simulated annealing (SA), the embedded confidential data can satisfy the requirements of physiological diagnostics. Experimental results confirm the effectiveness of this method.
FRONTIERS IN AGING NEUROSCIENCE
(2022)
Article
Computer Science, Theory & Methods
Chenglu Jin, Zheng Yang, Tao Xiang, Sridhar Adepu, Jianying Zhou
Summary: Industrial Internet of Things (IIoT) is a new paradigm for intelligent industrial control systems. Establishing a secure channel for machine-to-machine (M2M) communication in IIoT is crucial to prevent attacks and information leakage. This paper proposes a historical data based multi-factor authenticated and confidential channel establishment (HMACCE) approach, which uses a symmetric secret key, historical data, and secret tags to establish secure communication between client and server. The HMACCE protocols are lightweight, tailored for resource-constrained IIoT devices, and have bounded historical tag leakage resilience.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2023)
Article
Ecology
Christopher M. Free, Camila Vargas Poulsen, Lyall F. Bellquist, Sophia N. Wassermann, Kiva L. Oken
Summary: This article introduces the CALFISH database, a collection of historical datasets on California's fisheries. The curated datasets include information on landings, fishing vessel numbers, and licensed fishers. These datasets provide valuable insights into the historical context of California's fisheries, support original research, and assist in anticipating confidential data characteristics.
ECOLOGICAL INFORMATICS
(2022)
Article
Computer Science, Theory & Methods
Bradley Wakefield, Yan-Xia Lin, Rathin Sarathy, Krishnamurty Muralidhar
Summary: To protect privacy, synthetic micro-data is often used instead of confidential data. Accurately estimating the density function based on sample micro-data is important for the synthetic data to be useful for analysis.
STATISTICS AND COMPUTING
(2023)
Article
Computer Science, Information Systems
Andreou Andreas, Constandinos X. Mavromoustakis, George Mastorakis, Dinh-Thuan Doi, Jordi Mongay Batalla, Evangelos Palliss, Evangelos K. Markakis
Summary: This paper introduces an encryption framework based on data fragmentation and a novel deterministic grey-scale optical encryption scheme to ensure the security of medical data through encryption and fragmentation, and the reconstruction of images using interpolation and personal data from the database management system. It also aims to ensure the secure acquisition of diagnostic images and medical imagery based on probabilistic approaches.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Operations Research & Management Science
Jinwook Lee, Matthew J. Schneider
Summary: Exponential smoothing is a widely used forecasting method for univariate time series data. This study derives theoretical bounds for the absolute change to forecasts generated from additive exponential smoothing models based on the difference between protected and confidential time series data. The study also establishes robust bounds for Delta MAE and MMAE.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Theory & Methods
Hassan Zivarifard, Matthieu R. Bloch, Aria Nosratinia
Summary: This paper analyzes secrecy rates for a channel in which two transmitters simultaneously multicast to two receivers in the presence of an eavesdropper. Achievable rates are calculated and inner and outer bounds are derived, showcasing the minimal randomness necessary to achieve secrecy in different channel scenarios.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2021)
Article
Operations Research & Management Science
Jinwook Lee, Matthew J. Schneider
Summary: Exponential smoothing is a widely used forecasting method for time series data. This study derives theoretical bounds for the absolute change to forecasts generated from additive exponential smoothing models, based on the difference between protected and confidential time series data. It is found that the absolute change to forecasts can be represented as a compact form of geometric series and robust bounds are also identified for the Change in Mean Absolute Error (ΔMAE) and Measured Mean Absolute Error (MMAE).
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Theory & Methods
Federico Magnanini, Luca Ferretti, Michele Colajanni
Summary: In this study, we propose a software update framework based on a distributed infrastructure to ensure the high availability, integrity, and security of software even in the presence of cyber attacks. This framework utilizes a multi-authority attribute-based encryption scheme to avoid single-point vulnerabilities and guarantees both survivability and confidentiality of software updates.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2022)
Article
Multidisciplinary Sciences
Stefanie Warnat-Herresthal, Hartmut Schultze, Krishnaprasad Lingadahalli Shastry, Sathyanarayanan Manamohan, Saikat Mukherjee, Vishesh Garg, Ravi Sarveswara, Kristian Haendler, Peter Pickkers, N. Ahmad Aziz, Sofia Ktena, Florian Tran, Michael Bitzer, Stephan Ossowski, Nicolas Casadei, Christian Herr, Daniel Petersheim, Uta Behrends, Fabian Kern, Tobias Fehlmann, Philipp Schommers, Clara Lehmann, Max Augustin, Jan Rybniker, Janine Altmueller, Neha Mishra, Joana P. Bernardes, Benjamin Kraemer, Lorenzo Bonaguro, Jonas Schulte-Schrepping, Elena De Domenico, Christian Siever, Michael Kraut, Milind Desai, Bruno Monnet, Maria Saridaki, Charles Martin Siegel, Anna Drews, Melanie Nuesch-Germano, Heidi Theis, Jan Heyckendorf, Stefan Schreiber, Sarah Kim-Hellmuth, Jacob Nattermann, Dirk Skowasch, Ingo Kurth, Andreas Keller, Robert Bals, Peter Nuernberg, Olaf Riess, Philip Rosenstiel, Mihai G. Netea, Fabian Theis, Sach Mukherjee, Michael Backes, Anna C. Aschenbrenner, Thomas Ulas, Monique M. B. Breteler, Evangelos J. Giamarellos-Bourboulis, Matthijs Kox, Matthias Becker, Sorin Cheran, Michael S. Woodacre, Eng Lim Goh, Joachim L. Schultze
Summary: The study introduces Swarm Learning, a decentralized machine-learning approach that integrates medical data globally while complying with local privacy regulations. Using over 16,400 blood transcriptomes and more than 95,000 chest X-ray images, the research shows that Swarm Learning classifiers outperform those developed at individual sites.
Article
Biophysics
Lito Kriara, Mattia Zanon, Florian Lipsmeier, Michael Lindemann
Summary: This paper presents a deep learning framework for sensor signal cleaning, which can effectively remove measurement noise and accurately classify clean and noisy signals. The proposed models outperform existing feature-based approaches and have advantages in reducing false positive/negative rates.
PHYSIOLOGICAL MEASUREMENT
(2023)
Article
Computer Science, Cybernetics
Hugo Placido Da Silva, Stephen Fairclough, Andreas Holzinger, Robert Jacob, Desney Tan
ACM TRANSACTIONS ON COMPUTER-HUMAN INTERACTION
(2015)
Article
Computer Science, Cybernetics
Alexander J. Karran, Stephen H. Fairclough, Kiel Gilleade
ACM TRANSACTIONS ON COMPUTER-HUMAN INTERACTION
(2015)
Editorial Material
Computer Science, Cybernetics
Stephen Fairclough, Hugo Placido da Silva, Hugo Gamboa, Kiel Gilleade, Sergi Bermudez i Badia
INTERACTING WITH COMPUTERS
(2015)
Article
Computer Science, Cybernetics
Christopher G. Burns, Stephen H. Fairclough
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2015)
Article
Psychology, Biological
Carl A. Roberts, Stephen H. Fairclough, Francis P. McGlone, John E. Fisk, Catharine Montgomery
EXPERIMENTAL AND CLINICAL PSYCHOPHARMACOLOGY
(2013)
Article
Neurosciences
Ute Kreplin, Stephen H. Fairclough
FRONTIERS IN HUMAN NEUROSCIENCE
(2013)
Article
Psychology, Biological
Stephen H. Fairclough, Elena Spiridon
INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY
(2012)
Article
Clinical Neurology
C. A. Roberts, S. Fairclough, J. E. Fisk, F. T. Tames, C. Montgomery
JOURNAL OF PSYCHOPHARMACOLOGY
(2013)
Article
Psychology, Biological
Stephen H. Fairclough, Marjolein van der Zwaag, Elena Spiridon, Joyce Westerink
PHYSIOLOGY & BEHAVIOR
(2014)
Article
Neurosciences
C. A. Roberts, S. H. Fairclough, J. E. Fisk, F. Tames, C. Montgomery
PSYCHOPHARMACOLOGY
(2013)
Proceedings Paper
Computer Science, Cybernetics
Stephen H. Fairclough, Alexander J. Karran, Kiel Gilleade
CHI 2015: PROCEEDINGS OF THE 33RD ANNUAL CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS
(2015)
Article
Psychology, Social
Andreas Kastenmueller, Tobias Greitemeyer, Stephen Fairclough, Daniel Waite, Peter Fischer
Article
Psychology, Clinical
Laura Goodwin, Stephen H. Fairclough, Helen M. Poole
JOURNAL OF HEALTH PSYCHOLOGY
(2013)
Proceedings Paper
Computer Science, Artificial Intelligence
Mannes Poel, Femke Nijboer, Egon L. van den Broek, Stephen Fairclough, Anton Nijholt
ICMI '12: PROCEEDINGS OF THE ACM INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION
(2012)
