The Evolving Threat Landscape: How Cyber Threat Intelligence Empowers Proactive Defenses against WannaCry Ransomware
Jumoke Eluwa,
Patrick Omorovan,
Dipo Adewumi and
Oluwafunmilayo Ogbeide
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024, vol. 10, issue 2, 403-411
Abstract:
Cyber threat intelligence (CTI) is a rapidly growing field that plays an essential role in ensuring the security of online systems. CTI refers to the intelligence that is gathered, analyzed, and disseminated to help organizations understand and respond to cyber threats. This information can be used to identify vulnerabilities, detect potential attacks, and develop strategies to mitigate risks. The field of CTI is constantly evolving, as cyber threats become more sophisticated and complex. Legacy security measures like firewalls and anti-virus software are no longer enough to protect organizations from the many threats they face. CTI provides a proactive approach to cybersecurity, by enabling organizations to anticipate and prepare for threats before they occur. CTI relies on the collection and analysis of data from multiple sources, such as open-source intelligence (OSINT), dark web forums, social media, and other threat intelligence streams. The data is analyzed using a wide range of tools and techniques, including machine learning and artificial intelligence, to identify patterns and trends that may indicate a potential threat. One of the key benefits of CTI is its ability to help organizations understand the tactics, techniques, and procedures of attackers. By analyzing the behaviors, strategies, tactics, and actions of threat actors, organizations can develop a more comprehensive understanding of the threats they face and can better prepare for potential attacks.
Keywords: Cyber Threat Intelligence; Threat Landscape; Ransomware (search for similar items in EconPapers)
Date: 2024
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT243648
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v10:y2024:i2:id:59
DOI: 10.32628/CSEIT243648
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