MODELING AND RESTRAINING MOBILE VIRUS PROPAGATION

MODELING AND RESTRAINING MOBILE VIRUS PROPAGATION

ABSTRACT:

Viruses and malwares can spread from computer networks into mobile networks with the rapid growth of smart cellphone users. In a mobile network, viruses and malwares can cause privacy data leakage, extra charges, and remote listening. Furthermore, they can jam wireless servers by sending thousands of spam messages or track user positions through GPS. Because of the potential damages of mobile viruses, it is important for us to gain a deep understanding of the propagation mechanisms of mobile viruses. In this paper, we propose a two-layer network model for simulating virus propagation through both Bluetooth and SMS. Different from previous work, our work addresses the impacts of human behaviors, i.e., operational behavior and mobile behavior, on virus propagation. Our simulation results provide further insights into the determining factors of virus propagation in mobile networks. Moreover, we examine two strategies for restraining mobile virus propagation, i.e., preimmunization and adaptive dissemination strategies drawing on the methodology of autonomy-oriented computing (AOC). The experimental results show that our strategies can effectively protect large-scale and/or highly dynamic mobile networks.

EXISTING SYSTEM:

The Viruses and malwares can spread from computer networks into mobile networks with the rapid growth of smart cell phone users. In a mobile network, viruses and malwares can cause privacy data leakage, extra charges, and remote listening.

DISADVANTGES:

·         Attackers can jam wireless servers by sending thousands of spam messages.

·         Affect the mobile OS and cause damage to the mobile. This leds unable to use the mobiles due to virus.

·         Wastage of amount to clear the virus.

PROPOSED SYSTEM:

In the System we are implementing, we are modeling the Virus and Propagating through Bluetooth technology and SMS. Thus the Virus will be send to the other Users mobile via Bluetooth or SMS. So that when the Users opens the SMS the virus will be spread to their Mobile Phones. To protect our Mobile Phones from such virus, we are creating an android application from which we can get the Patches to clear those viruses from the Mobile Phones. So that we can protect our system from Virus. 

ADVANTAGES:

·         Detect the virus very effectively.

·         Apply the patches and remove the virus. 

SYSTEM REQUIREMENTS:

SOFTWARE REQUIREMENTS:

§  Platform                :Windows Xp,

§  Front End             : Java JDK1.5.

§  Back End              : MYSQL

HARDWARE REQUIREMENTS:

§  Processor                           :           Pentium IV

§  RAM                                :            512 MB

§  HDD                                :            80 GB

CONCLUSION:

In this paper, we have presented a two-layer network model for simulating and analyzing the propagation dynamics of SMS-based and BT-based viruses. Our model characterizes two types of human behavior, i.e., operational behavior and mobile behavior, in order to observe and uncover the propagation mechanisms of mobile viruses. Our simulation-based studies have contributed to the understanding of interactions between human behaviors and the propagation dynamics of mobile viruses. As has been shown in our experimental results, it would be helpful

to send security notifications to as many users as possible in order to improve their security awareness, which can in turn play a key role in restraining virus propagation. Meanwhile, our simulation results have shed light on the effects of human mobility on BT-based virus spreading, in terms of infection dynamics and spatially localized spreading patterns.

Based on our proposed two-layer network model, we have examined two strategies for controlling SMS-based virus propagation that are based on the methodology of AOC. As revealed in our experimental results, the AOC based preimmunization strategy is capable of restraining mobile virus propagation by protecting some highly connected phones, whereas the AOC-based dissemination strategy can forward security notifications or patches to as many phones as possible with a low communication cost in order to help them recover or avoid the potential damages of mobile viruses. Our experimental results have also indicated that our strategies can restrain virus propagation in a large-scale, dynamically evolving, and/or  community based network.