Trust-Oriented Recommender System for Cloud Reputation Services

Trust-Oriented Recommender System for Cloud Reputation Services

Master Thesis

Motivation
The latest trend in computing world is the cloud computing which is Internet-based computing that provides shared computer processing resources and data to computers and other devices on demand. There are numbers of cloud providers that provide different services, e.g. Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), to users. Users need to select the most trustworthy service provider that they can totally rely upon to fulfil their demands. For this purpose, trust calculation plays an important role. Because the limited Web interfaces do not allow users to identify the trustworthiness of service providers like typical face-to-face interaction. Users can find the trustworthiness of a service provider in cloud reputation services, e.g. TaaS4Cloud. The functionality of this web service can be enhanced by users’ ratings and recommendations to make it more user-centric. So that users can select the appropriate provider they need. In this case, trustworthiness of the users should also be considered to get more dependable recommendations. We can fulfil these requirements of users to select the most trustworthy providers by implementing a trust-oriented recommender system for cloud reputation services.

Ziel
The objectives of the thesis are as followings:

  • To derive mechanisms to provide ratings to cloud providers and to share in professional and social media.
  • To compare and evaluate different trust-oriented collaborative filtering algorithms to identify the most efficient trust-oriented collaborative filtering recommender system for TaaS4Cloud web-service.
  • To extract users’ trust from professional or social networks to incorporate it with recommender system.
  • To solve the cold-start problem for the selected recommender system.

To implement a prototype of a trust-aware recommender system for TaaS4Cloud.

Vision
Cloud customers can participate in the decision-making process of selecting trustworthy cloud providers through the recommender system (focus of this thesis) that we plan to intergrate into the TaaS4Cloud web service.

Start: 14.08.2017

Ende: 14.02.2018

Betreuer:

  • Sheikh Mahbub Habib (sheikh(a-t)tk.tu-darmstadt.de)

Forschungsgebiete: CYSEC, privacy-trust, Telecooperation , – SPIN: Smart Protection in Infrastructures and Networks