A Review of Several Privacy Violation Measures for Large Networks under Active Attacks

Bayesian graphical models for modern biological applications

Statistical Methods & Applications ◽

10.1007/s10260-021-00572-8 ◽

2021 ◽

Author(s):

Yang Ni ◽

Veerabhadran Baladandayuthapani ◽

Marina Vannucci ◽

Francesco C. Stingo

Keyword(s):

Graphical Models ◽

Cancer Genomics ◽

Graph Structure ◽

Biological Processes ◽

Limited Sample ◽

Large Networks ◽

Bayesian Approaches ◽

Complex Sampling ◽

Complex Dependence ◽

Bayesian Graphical Models

AbstractGraphical models are powerful tools that are regularly used to investigate complex dependence structures in high-throughput biomedical datasets. They allow for holistic, systems-level view of the various biological processes, for intuitive and rigorous understanding and interpretations. In the context of large networks, Bayesian approaches are particularly suitable because it encourages sparsity of the graphs, incorporate prior information, and most importantly account for uncertainty in the graph structure. These features are particularly important in applications with limited sample size, including genomics and imaging studies. In this paper, we review several recently developed techniques for the analysis of large networks under non-standard settings, including but not limited to, multiple graphs for data observed from multiple related subgroups, graphical regression approaches used for the analysis of networks that change with covariates, and other complex sampling and structural settings. We also illustrate the practical utility of some of these methods using examples in cancer genomics and neuroimaging.

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Simultaneous detection of communities and roles from large networks

Proceedings of the second edition of the ACM conference on Online social networks - COSN '14 ◽

10.1145/2660460.2660482 ◽

2014 ◽

Cited By ~ 10

Author(s):

Yiye Ruan ◽

Srinivasan Parthasarathy

Keyword(s):

Simultaneous Detection ◽

Large Networks

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A review on Queue Management Algorithms in Large Networks

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/1076/1/012034 ◽

2021 ◽

Vol 1076 (1) ◽

pp. 012034

Author(s):

Mustafa Maad Hamdi ◽

Hussain Falih Mahdi ◽

Mohammed Salah Abood ◽

Ruaa Qahtan Mohammed ◽

Abdulkareem Dawah Abbas ◽

...

Keyword(s):

Queue Management ◽

Large Networks ◽

Management Algorithms

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A Survey on Security and Privacy Issues in Modern Healthcare Systems

ACM Transactions on Computing for Healthcare ◽

10.1145/3453176 ◽

2021 ◽

Vol 2 (3) ◽

pp. 1-44

Author(s):

Akm Iqtidar Newaz ◽

Amit Kumar Sikder ◽

Mohammad Ashiqur Rahman ◽

A. Selcuk Uluagac

Keyword(s):

Healthcare Systems ◽

Security And Privacy ◽

Health Conditions ◽

Future Research ◽

Security Measures ◽

Implantable Medical Devices ◽

Manual Intervention ◽

Security Challenges ◽

Future Research Directions ◽

Privacy Violation

Recent advancements in computing systems and wireless communications have made healthcare systems more efficient than before. Modern healthcare devices can monitor and manage different health conditions of patients automatically without any manual intervention from medical professionals. Additionally, the use of implantable medical devices, body area networks, and Internet of Things technologies in healthcare systems improve the overall patient monitoring and treatment process. However, these systems are complex in software and hardware, and optimizing between security, privacy, and treatment is crucial for healthcare systems because any security or privacy violation can lead to severe effects on patients’ treatments and overall health conditions. Indeed, the healthcare domain is increasingly facing security challenges and threats due to numerous design flaws and the lack of proper security measures in healthcare devices and applications. In this article, we explore various security and privacy threats to healthcare systems and discuss the consequences of these threats. We present a detailed survey of different potential attacks and discuss their impacts. Furthermore, we review the existing security measures proposed for healthcare systems and discuss their limitations. Finally, we conclude the article with future research directions toward securing healthcare systems against common vulnerabilities.

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