Oblivious k-Nearest Neighbors for Secure Map Applications

Abstract

Cloud storage enables users to access and store large amounts of data on servers anytime and anywhere at little to no cost. Map applications are specific examples of cloud storage servers that allow users to query for nearby points of interest. Despite the many benefits offered by map applications, users are susceptible to data leakage through their access patterns, which is a significant security risk for these applications since the users location and other sensitive data can be leaked. In order to mitigate access pattern leakage and implement security in map applications, we have developed a novel remotely-stored network data structure, the ORAM-backed Hilbert B-tree. The novel data structure combines existing features such as the B-tree data structure, k-Nearest Neighbor (k-NN) search algorithms, Hilbert Curves, and Oblivious Random Access Memory (ORAM) algorithms, but ultimately allows users to make oblivious queries in map applications, a function that has not yet been conceived for such applications. This provides a significant improvement in security for map applications without compromising performance, preventing sensitive information such as the users physical location from being leaked.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jul 06, 2020
Accession Number
AD1136693

Entities

People

  • Jamie W. Lee

Organizations

  • United States Naval Academy

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Cloud Computing
  • Cloud Storage
  • Computer Networks
  • Computer Science
  • Computers
  • Data Centers
  • Data Leakages
  • Department Of Defense
  • Electronic Mail
  • Hilbert Curve
  • Hilbert Space
  • Information Operations
  • Social Media
  • Trees (Data Structures)
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Cybersecurity.
  • Neural Network Machine Learning.
  • Parallel and Distributed Computing.