Implicit Continuous User Authentication for Mobile Devices based on Deep Reinforcement Learning  

作　　者：Christy James Jose M.S.Rajasree 

机构地区：[1]Government Engineering College,Idukki,685603,India [2]APJ Abdul Kalam Technological University,Thiruvananthapuram,695016,India

出　　处：《Computer Systems Science & Engineering》2023年第2期1357-1372,共16页计算机系统科学与工程（英文）

摘　　要：The predominant method for smart phone accessing is confined to methods directing the authentication by means of Point-of-Entry that heavily depend on physiological biometrics like,fingerprint or face.Implicit continuous authentication initiating to be loftier to conventional authentication mechanisms by continuously confirming users’identities on continuing basis and mark the instant at which an illegitimate hacker grasps dominance of the session.However,divergent issues remain unaddressed.This research aims to investigate the power of Deep Reinforcement Learning technique to implicit continuous authentication for mobile devices using a method called,Gaussian Weighted Cauchy Kriging-based Continuous Czekanowski’s(GWCK-CC).First,a Gaussian Weighted Non-local Mean Filter Preprocessing model is applied for reducing the noise pre-sent in the raw input face images.Cauchy Kriging Regression function is employed to reduce the dimensionality.Finally,Continuous Czekanowski’s Clas-sification is utilized for proficient classification between the genuine user and attacker.By this way,the proposed GWCK-CC method achieves accurate authen-tication with minimum error rate and time.Experimental assessment of the pro-posed GWCK-CC method and existing methods are carried out with different factors by using UMDAA-02 Face Dataset.The results confirm that the proposed GWCK-CC method enhances authentication accuracy,by 9%,reduces the authen-tication time,and error rate by 44%,and 43%as compared to the existing methods.

关 键 词：Deep reinforcement learning gaussian weighted non-local meanfilter cauchy kriging regression continuous czekanowski’s implicit continuous authentication mobile devices 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]