Security and Communication Networks

Digital Forensics Approaches and Challenges of Ubiquitous and Emerging Devices

Publishing date
01 May 2022
Submission deadline
17 Dec 2021

1University of Zagreb, Zagreb, Croatia

2Singidunum University, Belgrade, Serbia

3University of Murcia, Murcia, Spain

Digital Forensics Approaches and Challenges of Ubiquitous and Emerging Devices

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Papers are published upon acceptance, regardless of the Special Issue publication date.

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There is a growing number of devices used every day that are able to transmit, store, and process data. Those devices have been developed and deployed due to the strong progress of information and communication technologies and concepts such as the Internet of Things and the Internet of Everything.

Because of their capabilities and broad application possibilities, devices such as cars, cameras, drones, wearables, and medical devices are increasingly becoming a means of criminal activity, and they can also be witnesses or targets of crime. As such, there is an increased need to research new and innovative methods for effective digital forensics of emerging and ubiquitous devices.

This Special Issue aims to provide a platform for researchers and practitioners to exchange and publish the latest research trends and results related to digital forensics of various end devices. The main objective of this Special Issue is to empower researchers to explore the new methods and concepts that can lead to effective, secure, and performance-oriented digital forensics techniques using artificial intelligence (AI), machine learning (ML), deep learning, and similar approaches. Original research and review articles are welcome.

Potential topics include but are not limited to the following:

  • AI in digital forensics
  • AI and ML in future forensics
  • Applied machine learning for digital forensics
  • Deep learning for image/video forensics
  • Deep learning-based anti-forensics
  • Deep learning for multimedia
  • Deep learning for cybersecurity applications
  • Security challenges associated with deep learning
  • Data-driven network security
  • Data-driven defence frameworks
  • Exploitation and defences
  • Fuzzy logic in digital forensics
  • Federated learning approach for digital forensics
  • Big data analytics and digital forensics
  • Anti-forensic techniques and methods
Security and Communication Networks
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