Towards adapting metamodelling technique for an online social networks forensic investigation (OSNFI) Domain

• Main Authors: Bade, Aliyu Musa, Othman, Siti Hajar
• Format: Article
• Language: English
• Published: Science and Information Organization 2022
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/100898/1/SitiHajarOthman2022_TowardsAdaptingMetamodellingTechnique.pdf; http://eprints.utm.my/id/eprint/100898/; http://dx.doi.org/10.14569/IJACSA.2022.0130722
• Institution: Universiti Teknologi Malaysia

With the ease of use of smart devices, most data is now kept and exchanged in digital forms such as images, diaries, calendars, movies, and so on. Digital forensic investigation is a new technology that emerged from criminals' who extensively use computers and digital storage devices to commit different types of crimes. To address this issue, a new domain called Online Social Networks Forensic (OSNF) was created to investigate these dynamic crimes perpetrated on social media platforms. OSNFI seeks to obtain, organise, investigate, and visualise user information as direct, objective, and fair evidence. Considering the millions of individuals using social media to share and communicate, they are becoming increasingly relevant for criminal investigations. In forensics investigation of online social network, there are currently major problems such as: lack of structured procedures, the lack of unified automated methods, and the lack of a theoretical context. The use of non-uniform and ad hoc forensic techniques and procedures not only reduces the effectiveness of the process, but also affects the reliability and creditability of the proof in criminal proceedings. As a result, this paper will provide a method derived from the software engineering domain known as metamodelling, which will integrate OSNFI knowledge into an artifact known as a metamodel.