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Revisiting Defenses against Large-Scale Online Password Guessing Attacks

Title:

Revisiting Defenses against Large-Scale Online Password Guessing Attacks

Alsaleh, M., Mannan, Mohammad and van Oorschot, P. C. (2012) Revisiting Defenses against Large-Scale Online Password Guessing Attacks. IEEE Transactions on Dependable and Secure Computing, 9 (1). pp. 128-141. ISSN 1545-5971

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Official URL: http://dx.doi.org/10.1109/TDSC.2011.24

Abstract

Brute force and dictionary attacks on password-only remote login services are now widespread and ever increasing. Enabling convenient login for legitimate users while preventing such attacks is a difficult problem. Automated Turing Tests (ATTs) continue to be an effective, easy-to-deploy approach to identify automated malicious login attempts with reasonable cost of inconvenience to users. In this paper, we discuss the inadequacy of existing and proposed login protocols designed to address largescale online dictionary attacks (e.g., from a botnet of hundreds f thousands of nodes). We propose a new Password Guessing Resistant Protocol (PGRP), derived upon revisiting prior proposals designed to restrict such attacks. While PGRP limits the total number of login attempts from unknown remote hosts to as low as a single attempt per username, legitimate users in most cases (e.g., when attempts are made from known, frequently-used machines) can make several failed login attempts before being challenged with an ATT. We analyze the performance of PGRP with two real-world data sets and find it more promising than existing proposals.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Concordia Institute for Information Systems Engineering
Item Type:Article
Refereed:Yes
Authors:Alsaleh, M. and Mannan, Mohammad and van Oorschot, P. C.
Journal or Publication:IEEE Transactions on Dependable and Secure Computing
Date:2012
Digital Object Identifier (DOI):10.1109/TDSC.2011.24
Keywords:Online password guessing attacks, brute force attacks, password dictionary, ATTs
ID Code:976807
Deposited By: Danielle Dennie
Deposited On:28 Jan 2013 14:02
Last Modified:18 Jan 2018 17:43

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