SECURE AND EFFICIENT INFORMATION MANAGEMENT IN DELAY(DISRUPTION) TOLERANT NETWORK
type: CreativeWork
description: "In environments like international military coalitions on the battlefield or multi-party relief work in a disaster zone, multiple teams are deployed to serve different mission goals by the command-and-control center (CC). They may need to survey damages and send information to the CC for situational awareness and also transfer messages to each other for mission purposes. However, due to the damaged network infrastructure in the emergency, nodes need to relay messages using the store and forward paradigm, also called Delay-tolerant Networks (DTNs). In DTN, the limited bandwidth, energy, and contacts among the nodes, and their interdependency impose several challenges such as sensitive data leakage to malicious nodes, redundant data generation, limited and delayed important message delivery, non-interested messages in storage, etc. We aim to focus on solving these challenges. We propose message fragmentation for secure message transfer because existing public-private-key cryptographic approaches may not work due to the unavailability of Public Key Infrastructure (PKI). Besides, to ensure more message delivery, redundant fragments are generated. However, too much redundancy may consume the energy and bandwidth of the nodes while transferring similar messages. Hence, we propose to send diverse content and limit the redundancy. Again, the dynamic environment we consider is prone to many adverse and sudden events. We aim to respond to these events by sending the event-related message to the CC fast with the help of intermediate nodes. The nodes are interested in certain types of content defined by their mission and interest. Therefore, we target to learn nodes' interests using Reinforcement Learning so that the nodes can populate themselves with the messages according to their mission requirements and increase the collaboration among them. Our future work will include machine learning techniques for predicting important places where node encounters the most and to cache …
abstract: "In environments like international military coalitions on the battlefield or multi-party relief work in a disaster zone, multiple teams are deployed to serve different mission goals by the command-and-control center (CC). They may need to survey damages and send information to the CC for situational awareness and also transfer messages to each other for mission purposes. However, due to the damaged network infrastructure in the emergency, nodes need to relay messages using the store and forward paradigm, also called Delay-tolerant Networks (DTNs). In DTN, the limited bandwidth, energy, and contacts among the nodes, and their interdependency impose several challenges such as sensitive data leakage to malicious nodes, redundant data generation, limited and delayed important message delivery, non-interested messages in storage, etc. We aim to focus on solving these challenges. We propose message fragmentation for secure message transfer because existing public-private-key cryptographic approaches may not work due to the unavailability of Public Key Infrastructure (PKI). Besides, to ensure more message delivery, redundant fragments are generated. However, too much redundancy may consume the energy and bandwidth of the nodes while transferring similar messages. Hence, we propose to send diverse content and limit the redundancy. Again, the dynamic environment we consider is prone to many adverse and sudden events. We aim to respond to these events by sending the event-related message to the CC fast with the help of intermediate nodes. The nodes are interested in certain types of content defined by their mission and interest. Therefore, we target to learn nodes' interests using Reinforcement Learning so that the nodes can populate themselves with the messages according to their mission requirements and increase the collaboration among them. Our future work will include machine learning techniques for predicting important places where node encounters the most and to cache …
author: Datta, Shudip
keywords: Computer Sciences, Physical Sciences and Mathematics
date modified: 2026-07-24T03:18:18Z
provider: Missouri University of Science and Technology
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Missouri University of Science and Technology