Affiliation:
1. Liverpool John Moores University, Merseyside, UK
2. Zayed University, Abu Dhabi, UAE
Abstract
The Internet of Things (IoT) represents the seamless merging of the real and digital world, with new devices created that store and pass around data. Processing large quantities of IoT data will proportionately increase workloads of data centres, leaving providers with new security, capacity, and analytics challenges. Handling this data conveniently is a critical challenge, as the overall application performance is highly dependent on the properties of the data management service. This article explores the challenges posed by cybercrime investigations and digital forensics concerning the shifting landscape of crime – the IoT and the evident investigative complexity – moving to the Internet of Anything (IoA)/Internet of Everything (IoE) era. IoT forensics requires a multi-faceted approach where evidence may be collected from a variety of sources such as sensor devices, communication devices, fridges, cars and drones, to smart swarms and intelligent buildings.
Reference32 articles.
1. ACPO. (2012). ACPO Good Practice Guide for Digital Evidence. Association of Chief Police Officers of England, Wales & Northern Ireland, 5(March), 41.
2. Adams, R. B. (2012). The Advanced Data Acquisition Model (ADAM): A Process Model for Digital Forensic Practice. Journal of Digital Forensics, Security and Law, 8(4). Retrieved from http://researchrepository.murdoch.edu.au/14422/2/02Whole.pdf
3. Adams, R. B. (2013). The Advanced Data Acquisition Model (ADAM): A process model for digital forensic practice. Murdoch University. Retrieved from http://researchrepository.murdoch.edu.au/14422/2/02Whole.pdf
4. Challenges to digital forensics: A survey of researchers & practitioners attitudes and opinions
5. An energy-aware service composition algorithm for multiple cloud-based IoT applications
Cited by
15 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献