{"id":26761,"date":"2025-06-28T16:09:47","date_gmt":"2025-06-28T10:24:47","guid":{"rendered":"https:\/\/www.revoscience.com\/en\/?p=26761"},"modified":"2025-06-28T16:09:52","modified_gmt":"2025-06-28T10:24:52","slug":"hide-and-seek-uncovering-new-ways-to-detect-hidden-apps-on-smartphones","status":"publish","type":"post","link":"https:\/\/www.revoscience.com\/en\/hide-and-seek-uncovering-new-ways-to-detect-hidden-apps-on-smartphones\/","title":{"rendered":"Hide and seek: Uncovering new ways to detect hidden apps on smartphones"},"content":{"rendered":"\n
\"\"<\/figure>\n\n\n\n

Researchers have discovered a modern solution to detect vault applications<\/a> (apps) on smartphones, which could be a game-changer for law enforcement.<\/p>\n\n\n\n

The analysis, led by researchers from Edith Cowan University (ECU) and the University of Southern Queensland, demonstrates that machine learning (ML) can be used to effectively identify vault apps.<\/p>\n\n\n\n

Smartphones are an integral part of daily life, used by an estimated 5 billion people around the world.<\/p>\n\n\n\n

With the growing concern for digital privacy, vault apps are becoming increasingly popular, providing users with secure storage by encrypting files and hiding their presence in the smartphone system.<\/p>\n\n\n\n

ECU Associate Professor and cybersecurity expert\u00a0Mike Johnstone<\/a>\u00a0said while these apps can be used for legitimate purposes, they are regularly associated with illegal activity.<\/p>\n\n\n\n

\u201cContent hiding\u2014or vault apps\u2014allows users to hide files, messages, and even entire apps behind additional layers of encryption,\u201d Associate Professor Johnstone said.<\/p>\n\n\n\n

\u201cThis could be for very good reasons, such as securing personal photos, files, or sensitive information.<\/p>\n\n\n\n

\u201cHowever, they may also facilitate espionage, enable unauthorized spying, and support a wide range of malicious activities that compromise user privacy and security.\u201d<\/p>\n\n\n\n

Associate Professor Johnstone said vault apps are not easily identified by existing detection systems.<\/p>\n\n\n\n

\u201cThese apps can look and behave like their normal equivalents, which can make them hard to identify,\u201d he said.<\/p>\n\n\n\n

\u201cConventional methods of detection also require prior knowledge of which apps are classified as improper, so it makes things difficult if you don\u2019t already know which apps to look for.<\/p>\n\n\n\n

\u201cThis is a key challenge for smartphone forensics, making it difficult for police to investigate crimes.\u201d<\/p>\n\n\n\n

Researchers found that they could effectively identify vault apps by using ML, with significant accuracy on Android phones.<\/p>\n\n\n\n

\u201cThis research shows a better way, by using machine learning to spot vault apps without the need for a fixed list or database that must be constantly updated,\u201d Associate Professor Johnstone said.<\/p>\n\n\n\n

\u201cOur findings reveal that it is entirely possible to detect an Android vault app with 98 percent accuracy.\u201d<\/p>\n\n\n\n

With this level of accuracy, Associate Professor Johnstone said this method could be extremely valuable for law enforcement agencies.<\/p>\n\n\n\n

\u201cThis approach could be instrumental for law enforcement in their efforts to address this critical issue,\u201d he said.<\/p>\n\n\n\n

\u201cGiven the popularity of phones, any approach that is non-invasive and accurate would be of use.\u201d<\/p>\n\n\n\n

Associate Professor Johnstone said the next phase of research will involve additional algorithms, a larger sample size, investigating whether it will work for non-Android devices, as well as the use of vault apps by cybercriminals.<\/p>\n","protected":false},"excerpt":{"rendered":"

Researchers have discovered a modern solution to\u00a0detect vault applications\u00a0(apps) on smartphones, which could be a game-changer for law enforcement.<\/p>\n","protected":false},"author":2,"featured_media":26762,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[47,17],"tags":[],"class_list":["post-26761","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-it","category-research"],"featured_image_urls":{"full":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app.webp",1920,1080,false],"thumbnail":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app-200x200.webp",200,200,true],"medium":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app-675x380.webp",675,380,true],"medium_large":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app-768x432.webp",750,422,true],"large":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app-1100x619.webp",750,422,true],"1536x1536":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app-1536x864.webp",1536,864,true],"2048x2048":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app.webp",1920,1080,false],"ultp_layout_landscape_large":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app-1200x800.webp",1200,800,true],"ultp_layout_landscape":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app-870x570.webp",870,570,true],"ultp_layout_portrait":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app-600x900.webp",600,900,true],"ultp_layout_square":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app-600x600.webp",600,600,true],"newspaper-x-single-post":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app-760x490.webp",760,490,true],"newspaper-x-recent-post-big":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app-550x360.webp",550,360,true],"newspaper-x-recent-post-list-image":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app-95x65.webp",95,65,true],"web-stories-poster-portrait":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app-640x853.webp",640,853,true],"web-stories-publisher-logo":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app-96x96.webp",96,96,true],"web-stories-thumbnail":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/06\/mob-app-150x84.webp",150,84,true]},"author_info":{"info":["RevoScience"]},"category_info":"IT<\/a> Research<\/a>","tag_info":"Research","comment_count":"0","_links":{"self":[{"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/posts\/26761","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/comments?post=26761"}],"version-history":[{"count":1,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/posts\/26761\/revisions"}],"predecessor-version":[{"id":26763,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/posts\/26761\/revisions\/26763"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/media\/26762"}],"wp:attachment":[{"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/media?parent=26761"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/categories?post=26761"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/tags?post=26761"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}