Please use this identifier to cite or link to this item: https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4260
Title: LOCATION BASED AUTHENTICATION USING WI-FI SIGNAL STRENGTH
Authors: CHANDRATHILAKA, J.A.R.N.
Issue Date: 28-Jul-2021
Abstract: Authentication is the process of identifying the user as genuine for the system which is a key functionality, when considering the security of all systems. The most conventional way of authentication depends on the user name and password. Even though the three(03)acceptable concepts which are used to authenticate users: something user knows(password), something user has (tokens, cards) and something user is (bio-metrics) or the combination of them are used, the systems are still vulnerable of being attacked by the hackers which results huge impact on cost, reputation of the organization and privacy of the users/ customers. Even though, additional security layers together with traditional authentication methods have already been introduced, still there is a need of a solution which is capable of providing secure authentication mechanism which is compatible with existing infrastructure without requesting special equipments. Wi-Fi access points are available in most of the places which provide connectivity to the systems in a particular area and most of the authorized professionals who are responsible for most critical functionalities of the systems widely use Wi-Fi access point to gain access to the servers, so as the hackers by spoofing their actual identity by pretending as a genuine user to misuse data. To address this problem, the research project LOCATION BASED AUTHENTICATION USING WI-FI SIGNAL STRENGTH tries to introduce an additional security layer to the Wi-Fi access point without requesting special equipments and it additionally checks the location where user tries to access the system with respect to Wi-Fi signal strength together with the combination of user name and password to enforce the security policy.
URI: http://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4260
Appears in Collections:2018

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