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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Casey ForensicSciInt2020 316.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig5 Jebali JofInfoTelec2020 5-1.jpg|240px]]</div>
'''"[[Journal:Digital transformation risk management in forensic science laboratories|Digital transformation risk management in forensic science laboratories]]"'''
'''"[[Journal:Secure data outsourcing in presence of the inference problem: Issues and directions|Secure data outsourcing in presence of the inference problem: Issues and directions]]"'''


Technological advances are changing how [[Forensic laboratory|forensic laboratories]] operate in all [[Forensic science|forensic disciplines]], not only digital. Computers support [[workflow]] management and enable evidence analysis (physical and digital), while new technology enables previously unavailable forensic capabilities. Used properly, the integration of digital systems supports greater efficiency and reproducibility, and drives digital transformation of forensic laboratories. However, without the necessary preparations, these digital transformations can undermine the core principles and processes of forensic laboratories. Forensic preparedness concentrating on digital data reduces the cost and operational disruption of responding to various kinds of problems, including misplaced exhibits, allegations of employee misconduct, disclosure requirements, and information security breaches ... ('''[[Journal:Digital transformation risk management in forensic science laboratories|Full article...]]''')<br />
With the emergence of the [[cloud computing]] paradigms, secure data outsourcing—moving some or most data to a third-party provider of secure data management services—has become one of the crucial challenges of modern computing. Data owners place their data among cloud service providers (CSPs) in order to increase flexibility, optimize storage, enhance data manipulation, and decrease processing time. Nevertheless, from a [[Cybersecurity|security]] point of view, access control proves to be a major concern in this situation seeing that the security policy of the data owner must be preserved when data is moved to the cloud. The lack of a comprehensive and systematic review on this topic in the available literature motivated us to review this research problem. Here, we discuss current and emerging research on privacy and confidentiality concerns in cloud-based data outsourcing and pinpoint potential issues that are still unresolved. ('''[[Journal:Secure data outsourcing in presence of the inference problem: Issues and directions|Full article...]]''')<br />
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Revision as of 17:39, 25 January 2022

Fig5 Jebali JofInfoTelec2020 5-1.jpg

"Secure data outsourcing in presence of the inference problem: Issues and directions"

With the emergence of the cloud computing paradigms, secure data outsourcing—moving some or most data to a third-party provider of secure data management services—has become one of the crucial challenges of modern computing. Data owners place their data among cloud service providers (CSPs) in order to increase flexibility, optimize storage, enhance data manipulation, and decrease processing time. Nevertheless, from a security point of view, access control proves to be a major concern in this situation seeing that the security policy of the data owner must be preserved when data is moved to the cloud. The lack of a comprehensive and systematic review on this topic in the available literature motivated us to review this research problem. Here, we discuss current and emerging research on privacy and confidentiality concerns in cloud-based data outsourcing and pinpoint potential issues that are still unresolved. (Full article...)

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