Trajectory Based Behavior Analysis for User Verification

Many of our activities on computer need a verification step for authorized access. The goal of verification is to tell apart the true account owner from intruders. We propose a general approach for user verification based on user trajectory inputs. The approach is labor-free for users and is likely to avoid the possible copy or simulation from other non-authorized users or even automatic programs like bots. Our study focuses on finding the hidden pattern on the trajectories produced by account users. We employ a Markov chain model with Gaussian distribution in its transitions to describe the behavior on the trajectory. To distinguish between two trajectories, we propose a novel dissimilarity measure combined with a manifold learnt tuning for catching the pairwise relationship. Based on the pairwise relationship, we plug-in any effective classification or clustering methods for the detection of unauthorized access. The result shows that the proposed method can accurately verify the user...

• Type: Journal
• Year: 2010
• Where: IDEAL
• Authors: Hsing-Kuo Pao, Hong-Yi Lin, Kuan-Ta Chen, Junaidillah Fadlil
• Keywords: IDEAL 2010, Intelligent Agents, Pairwise Relationship, Trajectory, True Account Owner