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|
Identifier |
000457006 |
Title |
RED : a Reputation Dashboard that displays the geolocation of bots and malicious computers, utilizing OSINT data |
Alternative Title |
RED (Reputation Dashboard): ένας πίνακας ελέγχου αξιοπιστίας που εμφανίζει τη γεωτοποθεσία των ρομπότ και κακόβουλων υπολογιστών, χρησιμοποιώντας δεδομένα από πηγές ανοιχτού λογισμικού |
Author
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Σπυριδάκης, Κωνσταντίνος Ν.
|
Thesis advisor
|
Μαρκάτος, Ευάγγελος
|
Reviewer
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Μαγκούτης, Κωνσταντίνος
Τζίτζικας, Ιωάννης
|
Abstract |
OSINT community’s active involvement and innovative approaches have played a
pivotal role in the evolution of modern systems. Leveraging freely available online
sources, developing tools and techniques, have a significant influence on information access, cost-effective solutions and collaboration between individuals and
organizations. This work, focused on developing a tool that effectively utilizes OSINT data to extract IP addresses of computers engaged in shady or cybercriminal
activities. Adapting to the difficulties of visualizing such content, we introduce
an IP Reputation Dashboard (RED) that displays the geolocation of bots and
malicious computers across the world. Throughout this research, we explored
and implemented methodologies for information acquisition, content analysis, and
adept utilization of these approaches to effectively visualize the gathered data
on the dashboard. RED’s user interface offers interactive visualizations, including world maps, charts, graphs presenting geospatial data pertaining to poor IP
address credibility, facilitating quick understanding and interpretation of fetched
OSINT information. Furthermore, the design of the tool aligns with the needs of
developers seeking to expand or integrate acquisition and visualization techniques
into their development environment, providing them with streamlined processes
and abstract implementation models. RED empowers users to make data-driven
decisions, identify emerging attack trends, track entities, enabling organizations to
gain actionable intelligence from the wealth of publicly available information.
|
Language |
English |
Subject |
IP address |
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Malicious activity |
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Threat intelligence |
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Διεύθυνση IP |
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Παράνομη δραστηριότητα στο διαδίκτυο |
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Πηγές ανοιχτού λογισμικού |
Issue date |
2023-07-21 |
Collection
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School/Department--School of Sciences and Engineering--Department of Computer Science--Post-graduate theses
|
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Type of Work--Post-graduate theses
|
Permanent Link |
https://elocus.lib.uoc.gr//dlib/b/9/1/metadata-dlib-1688715059-581949-7975.tkl
|
Views |
622 |