Threat Analysis of Fake Virus Alerts Using WebView Monitor

Imamura, Yuta; Orito, Rintaro; Chaikaew, Kritsana; Manardo, Celia; Leelaprute, Pattara; Sato, Mitsuru; Yamauchi, Toshihiro

doi:10.1109/candar.2019.00012

Cited by 1 publication

(6 citation statements)

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“…On mobile devices, attacks redirect the users to unwanted websites by unwanted page transition. Figure 1, adapted from [12], shows the flow diagram of an attack that redirects a user to unwanted websites. The steps of the attack are described as follows:…”

Section: Attacks Of Redirecting a User To Unwanted Websitesmentioning

confidence: 99%

“…According to this flow diagram, an attack that redirects a user to an unwanted website uses multiple malicious websites such as the landing site, intermediate site, and unwanted website. In addition, the URL of intermediate site 2 is generated by executing the JavaScript code of intermediate site 1 by either of the following two operations [12].…”

Section: Attacks Of Redirecting a User To Unwanted Websitesmentioning

confidence: 99%

“…In some cases, redirection to unwanted websites does not occur. On the landing site, attackers set one of the following three conditions to make the redirection occur when the user taps anywhere on the landing site [12].…”

Section: Attacks Of Redirecting a User To Unwanted Websitesmentioning

confidence: 99%

“…From the communication data, the FQDN is extracted as a keyword from the URLs of the intermediate site and the unwanted website because the landing site may redirect the user to the intermediate site and the unwanted website. The URL of the intermediate site is sometimes created from the specified URL and a randomly created character string [12]. Furthermore, the URL of the unwanted website sometimes includes the user's device information [12].…”

Section: Extraction Of Abstractmentioning

confidence: 99%

“…-The URL of an unknown malicious website posted by an attacker can be discovered in a timely fashion by collecting the URLs from Twitter's Streaming API. Most Flow of an attack that redirects a user to unwanted websites [12] malicious websites discovered by the proposed method were not detected by Google Safe Browsing. -The proposed method analyzes the collected malicious websites using an Android device and generates a blacklist for mobile devices.…”

Section: Introductionmentioning

confidence: 99%

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Method of Generating a Blacklist for Mobile Devices by Searching Malicious Websites

Ishihara

Sato

Yamauchi

2020

2020 Eighth International Symposium on Computing and Networking Workshops (CANDARW)

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As mobile devices have become more popular, malware and attacks directed at them have significantly increased. One of the methods to attack mobile devices is redirecting a user to unwanted websites by unwanted page transition. One of the countermeasures against such attacks is to generate a blacklist of URLs and hostnames, which can prevent access to malicious websites. To generate a blacklist, first, malicious websites are collected in the web space. Then, URLs and hostnames of the malicious websites are added to the blacklist. However, URLs of the malicious websites are typically changed frequently; thus, it is necessary to keep track of the malicious websites and update the blacklist in a timely manner. In this study, we proposed a method to generate blacklists for mobile devices by searching malicious websites. The method collects many HTML files from the web space using a crawler and searches for HTML files that are highly likely to be malicious using keywords extracted from the known malicious websites to discover the new ones. Thus, new malicious websites can be added to the blacklist in a timely manner. Using the proposed method, we discovered malicious websites that were not detected by Google Safe Browsing. Moreover, the blacklist generated using the method had a high detection rate for certain malicious websites. This paper reports the design process and the results of the evaluation of the new method.

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Section: Attacks Of Redirecting a User To Unwanted Websitesmentioning

confidence: 99%

Section: Attacks Of Redirecting a User To Unwanted Websitesmentioning

confidence: 99%

Section: Attacks Of Redirecting a User To Unwanted Websitesmentioning

confidence: 99%

Section: Extraction Of Abstractmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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