Detecting Mobile Spam Botnets Using Artificial immune Systems - Working Groups
Conference Papers Year : 2011

Detecting Mobile Spam Botnets Using Artificial immune Systems

Abstract

Malicious software infects large numbers of computers around the world. Once compromised, the computers become part of a botnet and take part in many forms of criminal activity, including the sending of unsolicited commercial email or spam. As mobile devices become tightly integrated with the Internet, associated threats such as botnets have begun to migrate onto the devices. This paper describes a technique based on artificial immune systems to detect botnet spamming programs on Android phones. Experimental results demonstrate that the botnet detection technique accurately identifies spam. The implementation of this technique could reduce the attractiveness of mobile phones as a platform for spammers.
Fichier principal
Vignette du fichier
978-3-642-24212-0_14_Chapter.pdf (334.86 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-01569560 , version 1 (27-07-2017)

Licence

Identifiers

Cite

Ickin Vural, Hein Venter. Detecting Mobile Spam Botnets Using Artificial immune Systems. 7th Digital Forensics (DF), Jan 2011, Orlando, FL, United States. pp.183-192, ⟨10.1007/978-3-642-24212-0_14⟩. ⟨hal-01569560⟩
93 View
98 Download

Altmetric

Share

More