TY - GEN
T1 - Extracting Cyber Threat Intelligence from Social Media with Case Studies in Twitter/X and Reddit
AU - Jakstaite, Dainora
AU - Czekster, Ricardo M.
PY - 2025/4/15
Y1 - 2025/4/15
N2 - A substantial amount of Internet traffic pertains to social media. This virtual way of interacting among peers, friends and audiences has contributed to help users test arguments and advertise statuses whilst helping organisations reaching out prospective clients. Given its global outreach, social media users produce a massive amount of daily data that are publicly available (depending on T&C). This brings interesting challenges in Cyber Threat Intelligence (CTI) as it can employ social media datasets to investigate impending cyber-attacks or latest malicious incursions on victims. Our contributions are two-fold, firstly, it outlines how to extract CTI in a timely fashion as well as the considerations and trade-offs for cyber security officers with case studies in Twitter/X and Reddit. Secondly, it proposes a trustability metric for determining reputable accounts to prioritise subsequent analysis efforts.
AB - A substantial amount of Internet traffic pertains to social media. This virtual way of interacting among peers, friends and audiences has contributed to help users test arguments and advertise statuses whilst helping organisations reaching out prospective clients. Given its global outreach, social media users produce a massive amount of daily data that are publicly available (depending on T&C). This brings interesting challenges in Cyber Threat Intelligence (CTI) as it can employ social media datasets to investigate impending cyber-attacks or latest malicious incursions on victims. Our contributions are two-fold, firstly, it outlines how to extract CTI in a timely fashion as well as the considerations and trade-offs for cyber security officers with case studies in Twitter/X and Reddit. Secondly, it proposes a trustability metric for determining reputable accounts to prioritise subsequent analysis efforts.
UR - https://link.springer.com/chapter/10.1007/978-3-031-87217-4_3
UR - http://www.scopus.com/inward/record.url?scp=105003859284&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-87217-4_3
DO - 10.1007/978-3-031-87217-4_3
M3 - Conference publication
SN - 9783031872167
T3 - Lecture Notes in Computer Science (LNCS)
SP - 46
EP - 65
BT - From Data to Models and Back
A2 - Broccia, Giovanna
A2 - Cerone, Antonio
ER -