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Malware Propagation in Large-Scale Networks

ABSTRACT:-

            Malware is spreading in networks, and poses a critical threat to network security. However, we have very limited understanding of malware behavior in networks to date. In this paper, we investigate how malware propagates in networks from a global. We formulate the problem, and establish a rigorous two layer epidemic model for malware propagation from network to network. Based on the proposed model, our analysis indicates that the distribution of a given malware follows exponential distribution, power law distribution with a short exponential tail, and power law distribution at its early, late and final stages, respectively. Extensive experiments have been performed through two real-world global scale malware data sets, and the results confirm our theoretical findings.

EXISTING SYSTEM	PROPOSED SYSTEM
EXISTING CONCEPT:- Existing process Single layer epidemic model: This layer focuses on the hosts of a given network. It have separate detection method use in malware detection.	PROPOSED CONCEPT: - We propose a two layer epidemic model: the upper layer focuses on networks of a large scale networks. The lower layer focuses on the hosts of a given network. This two layer model improves the accuracy compared with the available single layer epidemic models in malware modeling. Moreover, the proposed two layer model offers us the distribution of malware in terms of the low layer networks.
EXISTING TECHNIQUE:- DNS Redirection.	PROPOSED TECHNIQUE:- Malware Propagation.
TECHNIQUE DEFINITION:- The control system theory based models try to detect and contain the spread of malware. Detect malware in network level and redirect other host.	TECHNIQUE DEFINITION:- Malware means only a small percentage of vulnerable hosts have been compromised, and the propagation follows exponential distributions. Propagation of a malware means that all vulnerable hosts of a given network have been compromised.
DRAWBACKS:- In this process malware detect only host level. Malware detection is not perfect.	ADVANTAGES:- It detects malware in two level, Network level and Host level. Malware detection is perfect compare than existing technique.