Ibrahim Abba (Nigeria)

Motivated by a personal encounter with the devastating impact of Boko Haram’s insurgency in Maiduguri, where Ibrahim’s home was attacked and razed in December 2021, this research addresses the urgent need for enhanced security measures. Leveraging images from the Nigerian Army’s wanted list and other online sources, the proposed Convolutional Neural Network (CNN) employs transfer learning from the ImageNet dataset to discern Boko Haram members from the community.

Emphasizing that many Boko Haram faces are familiar due to recruitment from the local area, the model focuses on precise facial image recognition. Through careful data collection, including images from known Boko Haram individuals, and fine-tuning the VGG16 architecture pretrained on ImageNet, the model achieves a remarkable 95% accuracy. This work not only advances counter-terrorism strategies but also stands as a personal commitment to fortifying security in regions affected by extremist activities, where community-specific knowledge is pivotal for effective identification of the boko haram terrorist group.