The modern bug bounty landscape presents a dual challenge: the volume of attack surface across large programs is vast and continuously evolving, while the depth of expertise required to identify sophisticated vulnerabilities demands specialized knowledge across multiple security domains. Traditional approaches — manual penetration testing, monolithic vulnerability scanners, and single-model machine learning systems — struggle to simultaneously achieve breadth of coverage and depth of analysis.
This repository contains the supplementary materials associated with the article: “Beyond Grades: Multi-Target Deep Learning for Early Academic Risk Detection” The materials support the transparency, reproducibility, interpretability, and pedagogical analysis of the leakage-free…
# Land Subsidence Susceptibility Mapping and Screening-Level Relative Sea Level Change Scenarios for the Nigerian Coastal Zone Analysis code and derived data layers for the manuscript: > Ugwu, O. J., Njoku, R. E., Ahuchaogu, E. U., \& Uzoeshi, S. M. (2026).> \*Land Subsidence Sus…
Abstract: Deepfake technology, driven by generative models such as GANs and diffusion architectures, has enabled the creation of highly realistic manipulated media capable of deceiving both visual and auditory perception. Such forgeries pose significant risks to identity verifica…
Large language models (LLMs) are increasingly deployed in user-facing applications, which exposes them to prompt injection and jailbreak attacks that override system instructions, exfiltrate data, or elicit disallowed behaviour. Existing defences are largely single-mechanism: a r…