article · 2024
EmAc: An authentication method using Email and user activity
Tahsinur Rahman, Abhijit Bhowmik
Cited by 0Open access
Abstract
With the massive increase in the usage of user accounts, it is very important to build a strong defence mechanism for protecting the user from malicious attackers.Modern systems use different types of defence mechanisms such as password protection, two-step verification, secret question answering etc. to protect the users however these systems have their flaws which requires addressing and further work.Email verification is a very common and useful method for doing user authentication.Email can be used as a master key for all other systems.Because of that if the email address gets compromised, an attacker can compromise all other systems that are connected to the affected email address.This paper addresses this issue and proposes EmAc, an authentication system that uses traditional email verification for making the first step of the authentication, however, it will do further authentication using user activity of each individual system as well.
Cite this paper
Rahman, T., & Bhowmik, A. (2024). EmAc: An authentication method using Email and user activity. https://doi.org/10.1145/3723178.3723322
Rahman, Tahsinur, and Abhijit Bhowmik. “EmAc: An authentication method using Email and user activity.” 2024, pp. 1089–94, https://doi.org/10.1145/3723178.3723322.
Rahman, Tahsinur, and Abhijit Bhowmik. 2024. “EmAc: An authentication method using Email and user activity.” https://doi.org/10.1145/3723178.3723322.
Rahman, T. and Bhowmik, A. (2024) ‘EmAc: An authentication method using Email and user activity’. Available at: https://doi.org/10.1145/3723178.3723322.
@article{rahman2024emac,
title = {{EmAc: An authentication method using Email and user activity}},
author = {Rahman, Tahsinur and Bhowmik, Abhijit},
pages = {1089--1094},
year = {2024},
doi = {10.1145/3723178.3723322}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.