• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.3
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• pp.43-53
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• 2007

Internet becomes more and more popular, and most companies and institutes use web services for e-business and many other purposes. With the explosion of Internet, the occurrence of cyber terrorism has grown very rapidly. Simulation is one of the most widely used method to study internet worms. But, it is quite challenging to simulate very large-scale worm attacks because of various reasons. In this paper, we propose a hybrid modeling method for RCS(Random Constant Spreading) worm simulation. The proposed hybrid model simulates worm attacks by synchronizing modeling network and packet network. So, this model will be both detailed enough to generate realistic packet traffic, and efficient enough to model a worm spreading through the Internet. Moreover, our model have the capability of dynamic updates of the modeling parameters. Finally, we simulate the hybrid model with the CodeRed worm to show validity of our proposed model for RCS worm simulation.

• Journal of Information Processing Systems
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• v.5 no.1
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• pp.33-40
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• 2009

Ever since the network-based malicious code commonly known as a 'worm' surfaced in the early part of the 1980's, its prevalence has grown more and more. The RCS (Random Constant Spreading) worm has become a dominant, malicious virus in recent computer networking circles. The worm retards the availability of an overall network by exhausting resources such as CPU capacity, network peripherals and transfer bandwidth, causing damage to an uninfected system as well as an infected system. The generation and spreading cycle of these worms progress rapidly. The existing studies to counter malicious code have studied the Microscopic Model for detecting worm generation based on some specific pattern or sign of attack, thus preventing its spread by countering the worm directly on detection. However, due to zero-day threat actualization, rapid spreading of the RCS worm and reduction of survival time, securing a security model to ensure the survivability of the network became an urgent problem that the existing solution-oriented security measures did not address. This paper analyzes the recently studied efficient dynamic network. Essentially, this paper suggests a model that dynamically controls the RCS worm using the characteristics of Power-Law and depth distribution of the delivery node, which is commonly seen in preferential growth networks. Moreover, we suggest a model that dynamically controls the spread of the worm using information about the depth distribution of delivery. We also verified via simulation that the load for each node was minimized at an optimal depth to effectively restrain the spread of the worm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.2
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• pp.191-204
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• 2010

There is a well-defined propagation model, named the random constant spread (RCS) model, which explains worms that spread their clones with a random scanning strategy. This model uses the number of infected hosts in a domain as a factor in the worms' propagation. However, there are difficulties in explaining the characteristics of new Internet worms because they have several considerable new features: the denial of service by network saturation, the utilization of a faster scanning strategy, a smaller size in the worm's propagation packet, and to cause maximum damage before human-mediated responses are possible. Therefore, more effective factors are required instead of the number of infected hosts. In this paper, the network bandwidth usage rate is found to be an effective factor that explains the propagations of the new Internet worms with the random scanning strategy. The analysis and simulation results are presented using this factor. The simulation results show that the scan rate is more sensitive than the propagation packet for detecting worms' propagations.