A risk assessment model for a smart home Internet of Things (IoT) network is implemented using a Bayesian network. The directed acyclic graph of the Bayesian network is constructed from an attack graph that details the paths through which different attacks can occur in the IoT network. The parameters of the Bayesian network are estimated with the maximum likelihood method applied to a data set obtained from the simulation of attacks, in five simulation scenarios. For the risk assessment, inferences in the Bayesian network and the impact of the attacks are considered, focusing on DoS attacks, MitM attacks and both at the same time to the devices that allow the automation of the smart home and that are generally the ones that individually have lower levels of security.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140821 | PMC |
| http://dx.doi.org/10.3390/e24050668 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Effectiveness and Safety of Dose-Specific DOACs in Patients With Atrial Fibrillation: A Systematic Review and Network Meta-Analysis.
Cardiovasc Ther
January 2025
College of Pharmacy and Institute of Pharmaceutical Science and Technology, Hanyang University, Ansan-si, Gyeonggi-do, Republic of Korea.
Dose adjustments of direct-acting oral anticoagulants (DOACs) for atrial fibrillation are based on pivotal clinical trials assessing their effectiveness and safety in controlled settings. However, the appropriateness of these dosing strategies in real-world practice is uncertain. The purpose of this study is to compare the effectiveness and safety of dose-specific DOACs with those of warfarin.
View Article and Find Full Text PDFSeeking optimal non-pharmacological interventions for sarcopenia: a systematic review and network meta-analysis.
Aging Clin Exp Res
January 2025
Department of General Internal Medicine, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Background: With the acceleration of aging, sarcopenia has become a reality of concern today. This study aimed to evaluate the efficacy of various non-pharmacologic interventions and find the optimal interventions for sarcopenia.
Methods: PubMed, Medline OVID, EMBASE, Scopus, and Cochrane were searched from 1 January 2000 to 25 October 2023, with language restrictions to English.
Enhancing prosthetic hand control: A synergistic multi-channel electroencephalogram.
Wearable Technol
November 2024
Embedded Systems and Robotics Lab, Tezpur University, Tezpur, Assam, India.
Electromyogram (EMG) has been a fundamental approach for prosthetic hand control. However it is limited by the functionality of residual muscles and muscle fatigue. Currently, exploring temporal shifts in brain networks and accurately classifying noninvasive electroencephalogram (EEG) for prosthetic hand control remains challenging.
View Article and Find Full Text PDFMasking in Active Comparator Designs in Pharmacovigilance: A Retrospective Bias Analysis on the Spontaneous Reporting of Thiazolidinediones and Cardiovascular Events.
Pharmacoepidemiol Drug Saf
January 2025
School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada.
Introduction: Masking is a reporting bias where drug safety signals are muffled by elevated reporting of other medications in spontaneous reporting databases. While the impact of masking is often limited, its effect when using restricted designs, such as active comparators, can be consequential.
Methods: We used data from the US Food and Drugs Administration Adverse Event Reporting System (1999Q3-2013Q3) to study masking in a real-world example.
Deep neural networks have an inbuilt Occam's razor.
Nat Commun
January 2025
Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford, UK.
The remarkable performance of overparameterized deep neural networks (DNNs) must arise from an interplay between network architecture, training algorithms, and structure in the data. To disentangle these three components for supervised learning, we apply a Bayesian picture based on the functions expressed by a DNN. The prior over functions is determined by the network architecture, which we vary by exploiting a transition between ordered and chaotic regimes.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!