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As a new research area, Digital Forensics is a subject in a rapid development society. Cyber security for Big Data in the Cloud is getting attention more than ever. Computing breach requires digital forensics to seize the digital evidence to locate who done it and what has been done maliciously and possible risk/damage assessing what loss could leads to. In particular, for Big Data attack cases, Digital Forensics has been facing even more challenge than original digital breach investigations. Nowadays, Big Data due to its characteristics of three "V"s (Volume, Velocity, and Variety), they are either synchronized with Cloud (Such as smart phone) or stored on the Cloud, in order to sort out the storage capacity etc. problems, which made Digital Forensics investigation even more difficult. The Big Data-Digital Forensics issue for Cloud is difficult due to some issues. One of them is physically identify specific wanted device. Data are distributed in the cloud, customer or the digital forensics practitioner cannot have a fully access control like the traditional investigation does. The Smart City technique is making use of ICT (information communications technology) to collecting, detecting, analysing and integrating the key information data of core systems in running the cities. Meantime, the control is making intelligent responses to different requirements that include daily livelihood, PII (Personally identifiable information) security, environmental protection, public safety, industrial and commercial activities and city services. The Smart City data are Big Data, collected and gathered by the IoT (Internet of Things). This paper has summerised our review on the trends of Digital Forensics served for Big Data. The evidence acquisition challenge is discussed. A case study of a Smart City project with the IoT collected services Big data which are stored at the cloud computing environment is represented. The techniques can be generalised to other Big Data in the Cloud environment.

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Reconfigurable intelligent surface (RIS) has emerged as a promising technique for enhancing the performance of wireless networks. However, the traditional reflecting‐only RIS requires that the transmitter and receiver ought to be on the same side of the RIS, limiting the flexibility of RIS deployment. To overcome this drawback, a new simultaneous transmission and reflection reconfigurable intelligent surface (STAR‐RIS) has been proposed. Different from STAR‐RIS assisted half‐duplex systems in the existing literature, this work investigates a novel STAR‐RIS aided full‐duplex (FD) communication system. An FD base station (BS) communicates with an uplink (UL) user and a downlink user simultaneously over the same time‐frequency dimension assisted by a STAR‐RIS. The authors aim to maximise the energy efficiency by jointly optimising the transmit power of the BS and the UL user and the passive beamforming at the STAR‐RIS. The authors decouple the non‐convex problem into two subproblems and optimise them iteratively. The Dinkelbach's method is used to solve the power optimisation subproblem, whereas the penalty‐based method and successive convex approximation are applied to design the passive beamforming. The convergence and complexity of the proposed algorithm are also analysed. The simulation results demonstrate the superior performance of the proposed scheme compared with other baseline schemes.