
With the increasing demand for advanced digital security, efficient and scalable real-time monitoring has become essential. Traditional security evaluation methods often rely on manual oversight or delayed reporting, which lacks the immediate and personalized feedback necessary to thwart modern attacks. This project presents an Intelligent System for Real-Time Cyberthreat Information that leverages automated data streaming to evaluate the digital landscape for threats. The proposed system analyzes network logs and global threat feeds for syntax, logic, and patterns of malicious activity, providing instant alerts along with clear threat explanations and suggested mitigation strategies.
| 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 |
