首页    期刊浏览 2024年09月20日 星期五
登录注册

文章基本信息

  • 标题:Drone Forensics and Machine Learning: Sustaining the Investigation Process
  • 本地全文:下载
  • 作者:Zubair Baig ; Majid Ali Khan ; Nazeeruddin Mohammad
  • 期刊名称:Sustainability
  • 印刷版ISSN:2071-1050
  • 出版年度:2022
  • 卷号:14
  • 期号:8
  • 页码:4861
  • DOI:10.3390/su14084861
  • 语种:English
  • 出版社:MDPI, Open Access Journal
  • 摘要:Drones have been increasingly adopted to address several critical challenges faced by humanity to provide support and convenience . The technological advances in the broader domains of artificial intelligence and the Internet of Things (IoT) as well as the affordability of off-the-shelf devices, have facilitated modern-day drone use. Drones are readily available for deployment in hard to access locations for delivery of critical medical supplies, for surveillance, for weather data collection and for home delivery of purchased goods. Whilst drones are increasingly beneficial to civilians, they have also been used to carry out crimes. We present a survey of artificial intelligence techniques that exist in the literature in the context of processing drone data to reveal criminal activity. Our contribution also comprises the proposal of a novel model to adopt the concepts of machine learning for classification of drone data as part of a digital forensic investigation. Our main conclusions include that properly trained machine-learning models hold promise to enable an accurate assessment of drone data obtained from drones confiscated from a crime scene. Our research work opens the door for academics and industry practitioners to adopt machine learning to enable the use of drone data in forensic investigations.
国家哲学社会科学文献中心版权所有