MAPPING POTENTIAL ATTACKERS AGAINST NETWORK SECURITY USING LOCATION AWARE REACHABILITY QUERIES ON GEO SOCIAL DATA

Abstract

Attacks on network security can happen anywhere. Using Geo-Social Networks (GSN), i.e., a graph that combines social network data and spatial information, we can find the potential attackers based on the given location. In answering the graph-based problems, Reachability Queries are utilized. It verifies the reachability between two nodes in the graph. This paper addresses a problem defined as follows: Given a geo-social graph and a location area as a query point, we map potential attackers against network security using location-aware reachability queries. We employ the concepts of Reachability Minimum Bounding Rectangle (RMBR) and graph traversal algorithm, i.e., Depth-First Search (DFS), to answer the location-aware reachability queries. There are two kinds of the proposed solution, i.e., (1) RMBR-based solution map potential attackers by looking for intersecting RMBR values, and (2) Graph traversal-based solution map potential attackers by traversing the graph. We evaluate the performance of both proposed solutions using synthetic datasets. Based on the experimental result, the RMBR-based solution has much lower execution time and memory usage than the graph traversal-based solution.