There is no denying that communication networks, in particular the Internet, have changed our lives in many ways. Many organizations and businesses in general benefit, but at the same time their communication networks face many challenges such as cyber-attacks, which can result in disruptions of services and huge financial losses. Therefore, resilience of these networks against cyber-attacks is a growing interest in the cyber security community. In this paper, we propose a framework for attack pattern recognition by collecting and correlating cyber situational information vertically across protocol-levels, and horizontally along the end-to-end network path. This will help to analyze cyber challenges from different viewpoints and to develop effective countermeasures.