Two Quarantine Models on the Attack of Malicious Objects in Computer Network

Abstract

SEIQR (Susceptible, Exposed, Infectious, Quarantined, and Recovered) models for the transmission of malicious objects with simple mass action incidence and standard incidence rate in computer network are formulated. Threshold, equilibrium, and their stability are discussed for the simple mass action incidence and standard incidence rate. Global stability and asymptotic stability of endemic equilibrium for simple mass action incidence have been shown. With the help of Poincare Bendixson Property, asymptotic stability of endemic equilibrium for standard incidence rate has been shown. Numerical methods have been used to solve and simulate the system of differential equations. The effect of quarantine on recovered nodes is analyzed. We have also analyzed the behavior of the susceptible, exposed, infected, quarantine, and recovered nodes in the computer network.

Defending against Malicious Threats in Wireless Sensor Network: A Mathematical Model

“…The SIS (Susceptible-Infected-Susceptible) and SIR (Susceptible-Infected-Recovered) models are highly applicable and suggested model, SIR model assumes that once a host recovers from the disease, it becomes immune forever while the SIS model has been used for diseases where repeat infections are common. Richard and Mark [14] have proposed an improved SEI [10] and modification of SIR models generated guides for infections prevention by using the concept of epidemiological threshold [6][7][8] [16,17]. To overcome the limitation, Mishra and Saini [6] present a SEIRS model with latent and immune periods, which can reveal common worm propagation.…”

Cascading Failures in Weighted Complex Networks of Transit Systems Based on Coupled Map Lattices

“…For the case of intentional attack, with the same parameter set as the above, a perturbation = 5 > and is added to the node with the largest degree or strength, respectively. The simulations (shown in Figure 10) show that whether the stop with the largest degree or strength is intentionally attacked, the spreading processes of failures are almost synchronized for different 2 ; that is, the peak times all occur in a small range ≈ ∈ [12,16], and their failure proportions are ∈ [0.07, 0.08] and ∈ [0.06, 0.07], respectively, which reflects that although the topological network is small-world and the flow distribution is scalefree, the flow dynamic behaviors may nearly eliminate the cascading difference between these two structures. The time step that all of nodes are failed is ( ) = 74 when the largest degree stop is attacked, which is later than that of the largest strength one; that is, ( ) = 69, but they are both earlier than that in the mode of random fault ( ) = 82, revealing that the spreading process is the most intense when the largest strength node is intentionally attacked.…”

“…The scale-free networks become "robust yet fragile" [9,10]; that is, these networks are very sensitive to the intentional removal of central nodes but become robust to the random removal of some other nodes. There have been a few recent empirical studies on the structural robustness of many real complex networks, for example, the protein network [11], the food webs [12], the email network [13], the internet network [14,15], the computer network [16], the cyber-physical network [17], and the uncertain system [18,19].…”

Two Time Delay Quarantine Model for the Transmission of Worms in Wireless Network

“…By sending out copies of itself as a .sis file over cellular networks, it can affect users who are outside the 10 m range of Bluetooth. As quarantine is one of the important remedial processes for malware attack in network, several researchers developed model taking quarantine as one of the compartment in the epidemic models [3][4][5][6][7]. The effect of time delay on wireless network with worm propagation helps us to better understand the time lag of attack from one compartment to another [8,9].In this paper, we try to develop a compartment susceptible -infectious-quarantine-recover-susceptible(SIQRS) model with emphasis on Two Time Delays : latent and immune period.…”