Efficient anonymous knowledge distribution

Master Thesis

Motivation
In a pub/sub system, each node has a specific role, publishers produce information, subscribers consume the information and broker forwards the information generated by the producer to the consumer. Broker nodes have the information cor- responding to the identity of the publisher and the subscriber nodes. An attacker needs to attack only these broker nodes and can get information about publisher-subscriber relationship. In order to establish the relationship between publisher and subscribers, a routing table needs to be maintained and distributed. This process should preserve confidentiality and anonymity of receivers /senders while minimizing message overhead.

Ziel
Research question which this thesis is going to answer:

  1. How to distribute advertisement and subscription messages efficiently over the network.
  2. How to balance attribute localization between publisher and subscriber in terms of message overhead.
  3. Considering the above two questions, How to achieve the anonymity in pub/sub while minimizing message over- head.

Vision
In current pub/sub systems, an advertiser floods the network with its advertisement messages which puts a lot of extra overhead on the network. This is referred to as message overhead. To reduce this message overhead a user can use some different approaches like probabilistic forwarding. Using probabilistic forwarding a publisher instead of flooding it will forward some neighbors. But probabilistic forwarding algorithms are not designed for anonymity. To use these algorithms to achieve anonymity and minimize the message overhead, we have to find out some parameters.

Start: 01.05.2015

Ende: 30.09.2015

Betreuer:

  • Jörg Daubert
  • Tim Grube

Forschungsgebiete: CASED, Telecooperation , – SSI – Area Secure Smart Infrastructures