Optimal Distributed Malware Defense in Mobile Networks
with Heterogeneous Devices
ABSTRACT:
As malware
attacks become more frequently in mobile networks, deploying an efficient
defense system to protect against infection and to help the infected nodes to
recover is important to prevent serious spreading and outbreaks. The technical
challenges are that mobile devices are heterogeneous in terms of operating
systems, the malware infects the targeted system in any opportunistic fashion
via local and global connectivity, while the to-be-deployed defense system on
the other hand would be usually resource limited. In this paper, we investigate
the problem of how to optimally distribute the content-based signatures of
malware, which helps to detect the corresponding malware and disable further
propagation, to minimize the number of infected nodes. We model the defense
system with realistic assumptions addressing all the above challenges that have
not been addressed in previous analytical work. Based on the framework of
optimizing the system welfare utility, which is the weighted summation of
individual utility depending on the final number of infected nodes through the
signature allocation, we propose an encounter-based distributed algorithm based
on Metropolis sampler. Through theoretical analysis and simulations with both
synthetic and realistic mobility traces, we show that the distributed algorithm
achieves the optimal solution, and performs efficiently in realistic
environments.
EXISTING SYSTEM:
Mobile malware can
propagate through two different dominant approaches. Via MMS, a malware may
send a copy of itself to all devices whose numbers are found in the address
book of the infected handset. This kind of malware propagates in the social
graph formed by the address books, and can spread very quickly without
geographical limitations.
The other
approach is to use the short-range wireless media such as Bluetooth to infect
the devices in proximity as “proximity malware.”
Recent work of
Wang et al. has investigated the proximity malware propagation features, and
finds that it spreads slowly because of the human mobility, which offers ample
opportunities to deploy the defense system. However, the approach for
efficiently deploying such a system is still an ongoing research problem.
DISADVANTAGES
OF EXISTING SYSTEM:
Ø There is a problem for optimal signature distribution
to defend mobile networks against the propagation of both proximity and
MMS-based malware.
PROPOSED SYSTEM:
Ø To Design a defense system for both MMS and proximity
malware. Our research problem is to deploy an efficient defense system to help
infected nodes to recover and prevent healthy nodes from further infection.
Ø We formulate the optimal signature distribution
problem with the consideration of the heterogeneity of mobile devices and
malware, and the limited resources of the defense system. Moreover, our
formulated model is suitable for both the MMS and proximity malware
propagation.
Ø We give a centralized greedy algorithm for the
signature distribution problem. We prove that the proposed greedy algorithm
obtains the optimal solution for the system, which provides the benchmark
solution for our distributed algorithm design.
Ø We propose an
encounter-based distributed algorithm to disseminate the malware signatures
using Metropolis sampler. It only relies on local information and opportunistic
contacts.
ADVANTAGES
OF PROPOSED SYSTEM:
Ø The system provides optimal signature distribution to
defend mobile networks against the propagation of both proximity and MMS-based
malware.
Ø The proposed system offers protection against both MMS
based attack and Bluetooth based attack at the same time.
SYSTEM
REQUIREMENTS:
HARDWARE REQUIREMENTS:
Ø
System : Pentium IV 2.4 GHz.
Ø
Hard Disk :
40 GB.
Ø
Floppy Drive : 1.44
Mb.
Ø
Monitor : 15
VGA Colour.
Ø
Mouse :
Logitech.
Ø Ram : 512 Mb.
SOFTWARE
REQUIREMENTS:
Ø Operating system : Windows
XP/7.
Ø Coding Language : JAVA/J2EE
Ø IDE : Netbeans 7.4
Ø Database : MYSQL
REFERENCE:
Ong Li, Member,
IEEE, Pan Hui, Member, IEEE, Depeng Jin, Member, IEEE, Li Su, and Lieguang
Zeng, Member, IEEE. ”Optimal Distributed Malware Defense in Mobile Networks
with Heterogeneous Devices”. IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL.
13, NO. 2, FEBRUARY 2014
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