Biblio

This paper describes the achievements of project EUBra-BIGSEA, which has delivered programming models and data analytics tools for the development of distributed Big Data applications. As framework components, multiple data models are supported (e.g. data streams, multidimensional data, etc.) and efficient mechanisms to ensure privacy and security, on top of a QoS-aware layer for the smart and rapid provisioning of resources in a cloud-based environment.

Cloud computing paradigm continues to revolutionize the way business processes are being conducted through the provision of massive resources, reliability across networks and ability to offer parallel processing. However, miniaturization, proliferation and nanotechnology within devices has enabled digitization of almost every object which eventually has seen the rise of a new technological marvel dubbed Internet of Things (IoT). IoT enables self-configurable/smart devices to connect intelligently through Radio Frequency Identification (RFID), WI-FI, LAN, GPRS and other methods by further enabling timeously processing of information. Based on these developments, the integration of the cloud and IoT infrastructures has led to an explosion of the amount of data being exchanged between devices which have in turn enabled malicious actors to use this as a platform to launch various cybercrime activities. Consequently, digital forensics provides a significant approach that can be used to provide an effective post-event response mechanism to these malicious attacks in cloud-based IoT infrastructures. Therefore, the problem being addressed is that, at the time of writing this paper, there still exist no accepted standards or frameworks for conducting digital forensic investigation on cloud-based IoT infrastructures. As a result, the authors have proposed a cloud-centric framework that is able to isolate Big data as forensic evidence from IoT (CFIBD-IoT) infrastructures for proper analysis and examination. It is the authors' opinion that if the CFIBD-IoT framework is implemented fully it will support cloud-based IoT tool creation as well as support future investigative techniques in the cloud with a degree of certainty.