Prof. Isabella Rossi
1
,
Dr. Luis Fernando Páez
1
,
4
Laboratory of Network Intelligence and Geospatial Systems, Sapienza University of Rome, Rome, Italy
4
Department of Electrical and Computer Engineering, Universidad de los Andes, Bogotá, Colombia
Abstract
Delay-Tolerant Networks (DTNs) are designed to operate effectively in environments characterized by frequent disconnections, long delays, and intermittent connectivity. While their store-carry-forward paradigm enables communication in challenged environments, it also introduces unique security vulnerabilities, particularly concerning attacks that exploit spatial and temporal patterns of node mobility and contact. This article proposes and explores the feasibility of a geospatial anomaly detection framework to identify and monitor potential attack locations within a specific area of a DTN. By leveraging location information alongside network performance metrics, this approach aims to proactively detect malicious activities, such as black hole attacks or resource exhaustion, confined to geographical regions. The methodology encompasses data collection, feature engineering combining network and spatial data, and the application of anomaly detection algorithms. The hypothetical results suggest that such a system could significantly enhance DTN security by enabling targeted intervention and improving overall network resilience in challenged communication scenarios.
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