Push-styled Traffic Adaptive Mobile Botnets

In the recent years, with the rapid development of mobile Internet and the growing popularityof smart phones, pads etc, mobile botnets, evolving from the traditional PC botnets are becomingthe most effective means of attacking. The attackers can not only acquire the user privacyinformation through mobile botnets, but also order high paying services without the notice of theusers, and spread from one single mobile terminal to other users through the mobile network. Thuscause the users’ privacy and financial loss.Sensing and responding to mobile botnets in advance is the key to handling the mobile botnets.So the research on command and control mechanism of mobile botnets is particularly important.The two main characteristics of mobile botnets are timeliness and stealthiness.Because the commands are issued in a certain time, an effective botnets must make timely andeffective treatment to the attacker’s commands, the timeliness response of the bots is veryimportant. If you missed the time, the attack may lose significance. On the other hand, as a malwareprogram, bots must be unknown to the users while implementing attacks. If the channel isapperceived by the user, the mobile botnets will be cut off and result the failure of the mobile botnet.So stealthiness is also very important for the mobile botnets.In order to respond effectively to the mobile botnets, studying the command and controlmechanisms of mobile botnets is particularly important. This thesis studies a push-styled trafficadaptive mobile botnets command and control mechanisms from the aspects of timeliness andstealthiness. Because the security level of3G and WiFi is different, so taking use of the networklinking status, the urgent level of the command, the traffic cost of the attack, the normal traffic costof the user and some other corresponding aspects to make the traffic adaptive process will getperfect stealthiness. Pushing the command information to the bots by the message pushingmechanism can also get the perfect timeliness effect. Experimental results show that the timelinessand stealthiness of this kind of botnets is strong and need to pay attention.