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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig3 Teixeira FutureInternet2018 10-8.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Huang iScience2022 25-8.jpg|240px]]</div>
'''"[[Journal:SCADA system testbed for cybersecurity research using machine learning approach|SCADA system testbed for cybersecurity research using machine learning approach]]"'''
'''"[[Journal:Elegancy: Digitizing the wisdom from laboratories to the cloud with free no-code platform|Elegancy: Digitizing the wisdom from laboratories to the cloud with free no-code platform]]"'''


This paper presents the development of a [[supervisory control and data acquisition]] (SCADA) system testbed used for [[cybersecurity]] research. The testbed consists of a water storage tank’s control system, which is a stage in the process of water treatment and distribution. Sophisticated cyber-attacks were conducted against the testbed. During the attacks, the network traffic was captured, and features were extracted from the traffic to build a dataset for training and testing different machine learning algorithms. Five traditional machine learning algorithms were trained to detect the attacks: Random Forest, Decision Tree, Logistic Regression, Naïve Bayes, and KNN. Then, the trained machine learning models were built and deployed in the network, where new tests were made using online network traffic. The performance obtained during the training and testing of the machine learning models was compared to the performance obtained during the online deployment of these models in the network. The results show the efficiency of the machine learning models in detecting the attacks in real time. The testbed provides a good understanding of the effects and consequences of attacks on real SCADA environments. ('''[[Journal:Semantics for an integrative and immersive pipeline combining visualization and analysis of molecular data|Full article...]]''')<br />
One of the top priorities in any [[laboratory]] is [[Archival informatics|archiving]] experimental data in the most secure, efficient, and errorless way. It is especially important to those in chemical and biological research, for it is more likely to damage experiment records. In addition, the transmission of experiment results from paper to electronic devices is time-consuming and redundant. Therefore, we introduce an [[Open-source software|open-source]] no-code [[electronic laboratory notebook]] (ELN), Elegancy, a [[Cloud computing|cloud-based]]/standalone web service distributed as a Docker image. Elegancy fits all laboratories but is specially equipped with several features benefitting biochemical laboratories. It can be accessed via various web browsers, allowing researchers to upload photos or audio recordings directly from their mobile devices. Elegancy also contains a meeting arrangement module, audit/revision control, and laboratory supply management system. We believe Elegancy could help the scientific research community gather evidence, share information, reorganize knowledge, and digitize laboratory works with greater ease and security ... ('''[[Journal:Elegancy: Digitizing the wisdom from laboratories to the cloud with free no-code platform|Full article...]]''')<br />
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Latest revision as of 17:08, 10 April 2023

Fig1 Huang iScience2022 25-8.jpg

"Elegancy: Digitizing the wisdom from laboratories to the cloud with free no-code platform"

One of the top priorities in any laboratory is archiving experimental data in the most secure, efficient, and errorless way. It is especially important to those in chemical and biological research, for it is more likely to damage experiment records. In addition, the transmission of experiment results from paper to electronic devices is time-consuming and redundant. Therefore, we introduce an open-source no-code electronic laboratory notebook (ELN), Elegancy, a cloud-based/standalone web service distributed as a Docker image. Elegancy fits all laboratories but is specially equipped with several features benefitting biochemical laboratories. It can be accessed via various web browsers, allowing researchers to upload photos or audio recordings directly from their mobile devices. Elegancy also contains a meeting arrangement module, audit/revision control, and laboratory supply management system. We believe Elegancy could help the scientific research community gather evidence, share information, reorganize knowledge, and digitize laboratory works with greater ease and security ... (Full article...)

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