Paper Title
The Development of a Semantically Enabled Methodology for Exchanging Cyber Threat Intelligence

Abstract
The global technology landscape is being transformed by Big Data, which is raising the level of online information access required for tackling everyday difficulties, such as monitoring the spread of illnesses in real-time within areas of interest. Among other factors, the amount of data being generated and stored in cyberspace is alarming. As a result, organizations are confronted with the complex challenge of sifting through this data in order to detect and respond to security threats relevant to their operating domain on a timely basis. Traditional businesses and government organizations typically rely on inefficient and discrete solutions that rely on restricted sources of information and signature-based and anomaly-based approaches to detect known cyber threats and assaults. On the other hand, threat agents continue to create cutting-edge tools for cyber espionage, reconnaissance missions, and, ultimately, deadly cyber-attacks. Furthermore, new cybersecurity intelligence systems lack the semantic understanding required for the automated sharing of timely and context-aware information inside a specified operating domain. Furthermore, conventional cybersecurity information sharing solutions lack the visualization and intelligence required to deal with the vast volume of unstructured data from diverse sources across several industries. This paper will tackle some issues, and the paper proposes a semantic-enabled sharing model for communicating timely and appropriate cybersecurity intelligence with trusted partners. Based on past research and open-source sharing platforms such as CRITS, this paradigm is anchored by common information exchange standards such as STIX and TAXII. The suggested cross-platform sharing model is assessed by exploring a vast stream of cybersecurity-related tweets and semantic knowledge available from several data sources. Preliminary findings indicate that semantic knowledge is critical for facilitating the collaborative and automated exchange of timely and actionable cybersecurity intelligence. Keywords - Cyber-Attacks, Cyber Threat Intelligence, Cybersecurity, Big Data.