Data analytics of crowdsourced resources for cybersecurity intelligence

Cybersecurity incidents are always enduring hazards to organizations and enterprises. The increasing number of high exposure makes cybersecurity-related data a valuable asset, offering chances to identify trends, to make decisions and address challenges for cybersecurity end-users. While facing a considerable amount of data, it is challenging to seek out an agile approach that directly points out the most severe risks and provides security recommendations. In this paper, we propose a novel methodology that begins with data collection, follows by representing information on the knowledge graph and finishes with offering security recommendations based on the systematic data analysis. It demonstrates the power of collective intelligence of social media community and cybersecurity experts and even hackers to monitor vulnerabilities, threats and security trends to further facilitate decision-making and future planning. Also, we develop a prototype to prove the effectiveness and deployability of the methodology. We applied Tweets containing the unique vulnerability identifiers to examine our tool. The analysis results indicate the tool enabling to point out the vulnerabilities with high priority and reflect the historical experiences on weaknesses. With the facilitation of public cybersecurity reports and databases, our tool can offer security recommendations for risk mitigation from various aspects that satisfy end-users’ requirement within cybersecurity.