
doi: 10.4018/ijdcf.403438
Despite growing development of digital forensic tools for detection of child sexual exploitative and abuse material (CSEAM), victims and offenders remain a challenge to investigators and forensic experts. To understand developments and shortcomings of digital forensic approaches, a systematic literature review was carried out in IEEE Xplore, EBSCOHost Academic Search complete, and Science Direct between 2010 to 2025. A total of 41 articles out of 4,148 were selected through various filtering criteria. The review revealed seven themes covering the dark web, detection tools, crime patterns, applications based on artificial intelligence (AI) and machine learning (ML), biometric analysis, social media network analysis, and analysis of online behaviour. Despite the growing popularity of AI and ML, their application towards addressing CSEAM is scanty. Text analysis is the least commonly used feature, though text accompanies all media. Ethical implications are discussed. This research will help relevant stakeholders to strengthen the fight against CSEAM.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
