Title page for ETD etd-07082011-113804


Type of Document Master's Thesis
Author Penubaku, Lohit
Author's Email Address lprasa5@tigers.lsu.edu
URN etd-07082011-113804
Title Smart Access Control System with Behavioral Profiling and Dynamic PIN Concept
Degree Master of Science in Electrical Engineering (M.S.E.E.)
Department Electrical & Computer Engineering
Advisory Committee
Advisor Name Title
Li, Xin Committee Chair
Iyengar, S.S. Committee Member
Wu, Hsiao-Chun Committee Member
Keywords
  • SAC system
  • security
  • access point
Date of Defense 2011-06-10
Availability unrestricted
Abstract
Since ancient time, an access control device has been used for securing valuable properties as well as lives from threatening peoples. The most representative security device is Lock/Key. Recently, those security device technologies have been improved tremendously and provided various types of security methods. Nevertheless, these methods are not individually perfect to provide optimal security so that in recent years many such methods have been combined and used together to provide the required level of security. However, such combination can enhance security for limited number of users only but very difficult to provide scalable security with the number of users increases. They, most of the time, are not convenient for wide range of users (i.e., the innocent users who do not pose any threat) due to access time delay and different layers of authentication.

We believe that the system should exhibit capabilities that support adaptive security procedures for different range of users so most innocent users require minimum layer of identity authentication and verification while suspicious users may require passing through maximum along with some additional layers of security authentication and verification. These capabilities enable the system providing enhanced security as well as convenience to the users. A natural question in providing enhanced security is how to categorize certain individual users who require additional layers of authentication. We address this question by proposing a novel smart access control (SAC) system which can identify and categorize suspicious users from the analysis of their behavioral activities and bio-information.

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