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Hardened Setup of Personalized Security Indicators to Counter Phishing Attacks in Mobile Banking

Published: 24 October 2016 Publication History

Abstract

Application phishing attacks are rooted in users inability to distinguish legitimate applications from malicious ones. Previous work has shown that personalized security indicators can help users in detecting application phishing attacks in mobile platforms. A personalized security indicator is a visual secret, shared between the user and a security-sensitive application (e.g., mobile banking). The user sets up the indicator when the application is started for the first time. Later on, the application displays the indicator to authenticate itself to the user. Despite their potential, no previous work has addressed the problem of how to securely setup a personalized security indicator -- a procedure that can itself be the target of phishing attacks. In this paper, we propose a setup scheme for personalized security indicators. Our solution allows a user to identify the legitimate application at the time she sets up the indicator, even in the presence of malicious applications. We implement and evaluate a prototype of the proposed solution for the Android platform. We also provide the results of a small-scale user study aimed at evaluating the usability and security of our solution.

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cover image ACM Conferences
SPSM '16: Proceedings of the 6th Workshop on Security and Privacy in Smartphones and Mobile Devices
October 2016
130 pages
ISBN:9781450345644
DOI:10.1145/2994459
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 24 October 2016

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Author Tags

  1. mobile applications
  2. phishing
  3. security indicators

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CCS'16
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SPSM '16 Paper Acceptance Rate 13 of 31 submissions, 42%;
Overall Acceptance Rate 46 of 139 submissions, 33%

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  • (2023)Security and Performance of Knowledge-Based User Authentication for Smart DevicesInformation Security and Privacy in Smart Devices10.4018/978-1-6684-5991-1.ch002(41-70)Online publication date: 31-Mar-2023
  • (2022)DeviceWatch: A Data-Driven Network Analysis Approach to Identifying Compromised Mobile Devices with Graph-InferenceACM Transactions on Privacy and Security10.1145/355876726:1(1-32)Online publication date: 7-Nov-2022
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  • (2019)GUI-Squatting Attack: Automated Generation of Android Phishing AppsIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2019.2956035(1-1)Online publication date: 2019
  • (2019)Mobile anti-phishing: Approaches and challengesInformation Security Journal: A Global Perspective10.1080/19393555.2019.169129328:6(178-193)Online publication date: 12-Nov-2019
  • (2019)Preventing the propagation of a new kind of illegitimate appsFuture Generation Computer Systems10.1016/j.future.2018.11.05194(368-380)Online publication date: May-2019
  • (2019)Anti-phishing Models for Mobile Application Development: A Review PaperIntelligent Technologies and Applications10.1007/978-981-13-6052-7_15(168-181)Online publication date: 12-Mar-2019
  • (2018)VButtonProceedings of the 16th Annual International Conference on Mobile Systems, Applications, and Services10.1145/3210240.3210330(28-40)Online publication date: 10-Jun-2018
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