A High Abstract Digital Forensic Readiness Metamodel for Securing Smart Cities

Abstract

The rapid pace of technological development in recent years necessitates the protection of smart cities' infrastructure from various cyber threats. In the near future, cyber threats targeting smart cities are expected to increase in volume, number, nature, sophistication, and diversity. A literature review, on the other hand, indicates that smart cities do not have a comprehensive digital forensic readiness metamodel to address both predicted and unanticipated attacks. As a solution to this challenge, the present study developed a high abstract digital forensic readiness metamodel (HADFRM) for securing smart cities using a model-driven engineering approach. A major contribution of this study is to facilitate cybercrime investigation in such smart environments by integrating common processes and forensic readiness concepts embedded in HADFRM. The proposed HADFRM is bound to be an excellent source of practical assistance to forensic practitioners when a tool such as its structure can be used to help develop effective solutions to their problems. The HADFRM consists of five meta-processes: incident response process, data acquisition process, data preservation process, data analysis process, and reporting and presentation process. The HADFRM was evaluated with a realistic cybercrime scenario in a smart home. In this scenario, HADFRM was tested to determine its applicability and usefulness. By developing smart city security solutions, we have the opportunity to improve cybersecurity and stimulate sustainable economic growth, which ultimately contributes to improving citizens' welfare.