Experimental large-scale review of attractors for detection of potentially unwanted applications

Vlasta Stavova, Lenka Dedkova, Vashek Matyas, Mike Just, David Smahel, Martin Ukrop

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)
69 Downloads (Pure)

Abstract

While malicious software (malware) is designed to disrupt or damage computer systems, potentially unwanted applications (PUAs) combine useful features with less desirable ones, such as adware or spyware. Unlike anti-malware solutions, removing PUAs can be controversial, for both the PUA owners and also the users who might wish to accept the PUA features. Thus, solutions for removing PUAs require users to make their removal decisions. In this paper we investigate the effectiveness of 15 screen variants that use different "security warning attractors" designed to encourage users to enable PUA detection when they are installing a security software solution from the online security software company ESET. Our live field study with close to 750,000 software installations by end users in 222 countries shows that a small change of switching the order of the options presented using radio buttons and offering the "enable detection" option first was the most effective (and was later set as the option of choice by ESET). The chosen approach led to a significant reduction of non-consenting users from 17.9% to 11.1%. Other features, such as the use of colours and
pictorials, which have previously demonstrated their effectiveness with more traditional SSL security warnings, did not yield significant improvements for enabling PUA detection.
Original languageEnglish
Pages (from-to)92-100
Number of pages9
JournalComputers and Security
Volume76
Early online date12 Mar 2018
DOIs
Publication statusPublished - Jul 2018

Fingerprint

Dive into the research topics of 'Experimental large-scale review of attractors for detection of potentially unwanted applications'. Together they form a unique fingerprint.

Cite this