PPT-AppContext : Differentiating Malicious and Benign Mobile App Behavior Under Contexts

Wei Yang Xusheng Xiao Benjamin Andow Sihan Li Tao Xie and William Enck Mobile apps become increasingly popular 2 Source official Android blog Example 3 The number of mobile malware keeps increasing. Hongyu . Gao. , . Jun Hu. , . Christo . Wilson. , . Zhichun. . Li. , . Yan . Chen. . and . Ben Y. . Zhao. Northwestern University, US. Northwestern / . Huazhong. Univ. . of . Sci. & Tech, China. Possible attack threats to mobile devices. Network exploit. Hackers takes advantage of vulnerability or flaw of user’s web browser on mobile device in . WiFi. communication to attack victims.. Hackers send malicious code/data from malicious logic websites to victim’s browser after user browses the malicious page and the malicious code will take over the control to get all sensitive data on the victim’s device.. : Detecting Malicious Facebook . Applications. Md Sazzadur . Rahman. , Ting-Kai Huang, Harsha . Madhyastha. , Michalis . Faloutsos. University of California, Riverside . . Problem . S. tatement. 2. S. : . The Evolution of Evasive Malware . Giovanni Vigna. Department of Computer Science. University of California Santa Barbara. http://. www.cs.ucsb.edu. /~. vigna. Lastline, Inc.. http://. www.lastline.com. : Differentiating Malicious and Benign Mobile App Behavior Under Contexts. Wei Yang. , . Xusheng. Xiao, Benjamin . Andow. , . Sihan. Li, Tao . Xie. and William . Enck. Mobile apps become increasingly popular. : Detecting Malicious Facebook . Applications. Md Sazzadur . Rahman. , Ting-Kai Huang, Harsha . Madhyastha. , Michalis . Faloutsos. University of California, Riverside . . Problem . S. tatement. 2. S. Tao Xie. Joint Work w/ . David Yang, . Sihan Li (Illinois). Xusheng . Xiao, Benjamin Andow, . Rahul . Pandita, . William Enck (NCSU). Mobile App Markets. Apple App Store. Google Play. Microsoft Windows Phone. By . Amir Javed. Supervisor : Dr. Pete Burnap. Prof. Omer Rana. Problem. Identifies Trending Topics. #Trending topic . lmao this tweet by @user was nuts . Short_URL. User clicks on shortened URL. Mobile Devices vs. Desktops. Physical Theft . – Mobile devices are now more prone to physical theft unlike Desktops they are small and mobile.. More Areas for Error– . In essence mobile devices are seen as mini computers however mobile security must now take into account SMS, MMS, Bluetooth etc. .   . Session 5. : Panel Discussion – Mobile Technology, Mobile Payments and Cyber Threats . September 7-10, 2014 - Lilongwe, Malawi.  . Mobile Financial Servicers threats . and . risks: the . principles and procedures used to address . Detecting and Characterizing Social Spam Campaigns Hongyu Gao , Jun Hu , Christo Wilson , Zhichun Li , Yan Chen and Ben Y. Zhao Northwestern University, US Northwestern / Huazhong Univ. Malware. Vitor M. . Afonso, . Dario S. Fernandes . Filho, . André . R. A. . Grégio1. , PauloL.de Geus, . Mario . Jino. Contents. Introduction. Related work. System Description. Tests. Results. Conclusion And Future Work. Impact Factor: 5.665, ISSN (Online): 2456 - 4664 (www.dvpublicati on.com) Volume 1, Issue 2, 2016 25 A SECURITY SYSTEM TO REMOVE MALICIOUS WEBPAGES ON MOBILE USING KAYO N. Manimozhi*, S . Rame sh** Arpitha G et al , Computer Science and Mobile Computing, Vol.7 Issue.4 , April - 2018 , pg. 76 - 81