An Epidemic Model of Computer Worms with Time Delay and Variable Infection Rate

Dynamical analysis and control strategies on malware propagation model

Malware software has become a pervasive threat in computer and mobile technology attacks. Attackers use this software to obtain information about users of the digital world to obtain benefits by hijacking their data. Antivirus software has been developed to prevent the propagation of malware, but this problem is not yet under control. To develop this software, we have to check the propagation of malware. In this paper, we explore an advanced malware propagation model with a time-delay factor and a variable infection rate. To better understand this model, we use fractal–fractional theory. We use an exponential decay kernel for this. For theoretical purposes (existence, uniqueness, and stability), we use the results from fixed-point theory, and, for numerical purposes, a Lagrange two-point interpolation polynomial is used to develop an algorithm. Matlab R2016a is used for simulation, and the physical significance is assessed. We examine the impact of different fractal and fractional orders for various parameters. Moreover, we compare four different mathematical models (classical, fractional, fractal, and fractal–fractional). Also, constant and variable fractional and fractal orders are compared using graphs. We investigate the idea that significant perturbation in infected nodes might be due to minor changes. This work may help with developing antivirus strategies in real life.

Bacterial endosymbionts of sap-sucking insects provide their host with a number of beneficial qualities, including the supply of nutrition, defense against parasitoids, and protection from heat stress. Damage to these bacterial associates can therefore have a negative impact on the fitness of their insect host. We evaluated observational and experimental factors regarding the nonnative hemlock woolly adelgid (Adelges tsugae Annand) (Hemiptera: Adelgidae) to help understand the roles of its three recently identified symbionts, including under heat stress conditions. The prevalence of A. tsugae's facultative symbiont (Serratia symbiotica) was examined at different spatial scales to determine how variable infection rates are for this symbiont. There was no significant difference found in infection rates between adelgids on a tree, within a plot, or within a state. However, significantly more adelgids in Georgia (95%) had S. symbiotica compared to those in New York (68%). Microsatellite genotyping of the adelgids found that this difference was most likely not the result of a second introduction of A. tsugae into eastern North America. Comparison of S. symbiotica proportions between first and fourth instars showed that symbiont absence did not affect the ability of A. tsugae to survive aestivation. Evaluations of symbiont densities within each adelgid found that when S. symbiotica was absent, the density of obligate symbionts was significantly higher. Exposure to heat stress (32.5 °C) was not consistently correlated with changes in symbiont densities over a 4-d period. Overall, we have shown that symbiont prevalence and densities vary within the broad population of A. tsugae in eastern North America, with potentially significant effects upon the ecology of this important pest.

Hopf bifurcation in an Internet worm propagation model with time delay in quarantine

Enteroviruses (EV) and parechoviruses A (PeV-A) are commonly circulating viruses able to cause severe disease. Surveillance studies from sub-Saharan Africa are limited and show high but variable infection rates and a high variation in genotypes. This is the first study to describe EV and PeV-A circulation in children in South Sudan. Of the fecal samples collected, 35% and 10% were positive for EV and PeV-A, respectively. A wide range of genotypes were found, including several rarely described EV and PeV-A types. Coxsackie virus A (CVA) EV-C types, particularly CVA13, were the most dominant EV types. The CVA13 types had a high diversity with the majority belonging to four different previously described clusters. PeV-A1 and -A14 were the most common PeV-A genotypes. A lack of representative data from our and other studies from sub-Saharan Africa demonstrates the need for more systematic surveillance of non-polio EV and PeV-A types in this region.

Epstein-Barr virus (EBV) infection has been postulated to be an early event involved in the pathogenesis of NPC. The lack of representative premalignant nasopharyngeal epithelial cell system for EBV infection has hampered research investigation into the regulation and involvement of EBV infection in NPC pathogenesis. We have compared the efficiency of EBV infection in nasopharyngeal epithelial cells with different biological properties including immortalized, primary and cancerous nasopharyngeal epithelial cells. EBV infection could be achieved in all the nasopharyngeal epithelial cells examined with variable infection rate. TGF-β effectively enhanced EBV infection into nasopharyngeal epithelial cells both in the immortalized and primary nasopharyngeal epithelial cells. Stable infection of EBV was achieved in a telomerase-immortalized nasopharyngeal epithelial cell line, NP460hTert. The expression pattern of EBV-encoded genes and biological properties of this EBV infected cell line upon long term propagation were monitored. The EBV-infected nasopharyngeal epithelial cells acquired anchorage independent growth in soft-agar and exhibited invasive growth properties upon prolonged propagation. A distinguish feature of this EBV-infected nasopharyngeal epithelial cell model was its enhanced ability to survive under growth factor and nutrient starvation. This was evidenced by the suppressed activation of apoptotic markers and sustained activation of pAkt of EBV-infected cells compared to control cells under nutrient starvation. Examination of cytokine profiles of EBV-infected NP460hTert cells to nutrient and growth factor deprivation revealed upregulation expression of MCP-1 and GRO-α. The establishment of a stable EBV infection model of premalignant nasopharyngeal epithelial cells will facilitate research investigation into the pathogenic role of EBV in NPC development. Acknowlegement: The authors wish to acknowlege the funding support from the Research Grant Council (Hong Kong) and the Area of Excellence on Nasopharyangeal Carcinoma Research Center (Hong Kong). Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2460.

HepaRG cells are liver bipotent progenitors acquiring hepatocytes features when differentiated in the presence of dimethylsulfoxide (DMSO). Differentiated HepaRG (dHepaRG) are considered the best surrogate model to primary human hepatocytes (PHH) and are susceptible to several hepatotropic viruses, including Hepatitis B Virus (HBV) and Hepatitis Delta Virus (HDV) infection. Despite these advantages, HepaRG cells are not widely used for the study of these two viruses because of their long differentiation process and their rather low and variable infection rates. Here, we tested the use of a cocktail of five chemicals (5C) combined or not with DMSO to accelerate the cells’ differentiation process. We found that NTCP-mediated HDV entry and replication are similar in HepaRG cells cultivated for only 1 week with 5C and DMSO or differentiated with the regular 4-week protocol. However, even though the NTCP-mediated HBV entry process seemed similar, cccDNA and subsequent HBV replication markers were lower in HepaRG cells cultivated for 1 week with 5C and DMSO compared to the regular differentiation protocol. In conclusion, we set up a new procedure allowing fast differentiation and efficient HDV-infection of HepaRG cells and identified differential culture conditions that may allow to decipher the mechanism behind the establishment of the HBV minichromosome.

Modeling and analysis of Internet worm propagation

This paper proposes a method to estimate the time delay and delay rate when forecast data is inaccurate, in the Very Long Baseline Interferometry (VLBI) signal processing for the radio science receiver (RSR). Firstly, we find out rough time delay and rough Doppler shift through cross-correlation chart by using multiple-correlation method to enhance the SNR, which is suitable for the low SNR situation. Secondly, the data is compensated to get linear phase-frequency curve of the cross-power spectrum and calculate the precise time delay and delay rate by iteration. The method is tested with both simulation data and real received data. Result shows the signal detection limitation is at SNR = −23 dB. The standard deviation fit error for the curve can be under 0.05 rad. The method effectively increases the data processing probability.

Tracking control for multiple-integrator systems is regarded as a fundamental problem associated with nonlinear dynamic systems in the physical and mathematical sciences, with many applications in engineering fields. In this paper, we adopt the Zhang neural network method to solve this nonlinear dynamic problem. In addition, in order to adapt to the requirements of real-world hardware implementations with higher-order precision for this problem, the multiple-order derivatives in the Zhang neural network method are estimated using backward finite-divided difference formulas with quadratic-order precision, thus producing time delays. As such, we name the proposed method the Zhang neural network method with time delay. Moreover, we present five theorems to describe the convergence property of the Zhang neural network method without time delay and the quadratic-order error pattern of the Zhang neural network method with time delay derived from the backward finite-divided difference formulas with quadratic-order precision, which specifically demonstrate the effect of the time delay. Finally, tracking controllers with quadratic-order precision for multiple-integrator systems are constructed using the Zhang neural network method with time delay, and two numerical experiments are presented to substantiate the theoretical results for the Zhang neural network methods with and without time delay.

Advancements in our understanding of cardiac conduction abnormalities and pathophysiology of congestive heart failure coupled with innovations in device manufacturing and programming have helped to create a demand for a plethora of newer cardiovascular devices over the past 3 decades. Appropriate use of cardiovascular implantable electronic devices (CIEDs) in carefully selected patients is associated with better survival and significant improvements in quality of life.1 Cardiac resynchronization therapy devices are the newest “breed” to join an existing and growing family of permanent pacemakers (PPMs) and implantable cardioverter-defibrillators (ICDs). The number of cardiac devices implanted each year continues to grow exponentially. Unfortunately, because of the invasive nature of the implantation procedures required for placement of these devices and multiple comorbid conditions in device recipients, the benefits of these devices can be eclipsed by infectious complications. Infection is a very serious and dreadful complication requiring complete removal of the infected device and systemic antimicrobial therapy.2–4 Moreover, the financial cost of managing device infections is enormous. In this article, we review the latest developments pertaining to CIED infections, with a special emphasis on pathogenesis and microbiology. Since their first conceptualization and use in the late 1950s,5 CIEDs have undergone significant enhancements in design and function, and their use continues to rise, with a growing number of indications for placement, improvements in implantation techniques, and enhancements in device programming and monitoring.1 Earlier investigations reported a highly variable CIED infection rate, ranging from 0.13% to 19.9%.6,7 However, a more recent review of case records from the Massachusetts General Hospital reported 21 (1.2%) ICD-related infections among 1700 patients who underwent device implantation procedures.8 In a study by Mela et al,8 CIED infection occurred in 1.8% of 1170 patients who underwent a primary implant, a generator change, …

Temperature control load (TCL) usually participates in load frequency control of microgrid (MGLFC) through open communication network, which inevitably introduces time delays. Time delays will degrade the performance of MG and even lead to instability. In this article, the delay-dependent stability for MGLFC with TCL participation is evaluated. First, a model of TCL participating in MGLFC is constructed with time delay induced by open communication network and transformed into a time-delay system. Then, the delay-dependent stability for MGLFC with TCL participation is evaluated by the Lyapunov stability theory. The stability evaluation criterion obtained is less conservative and can provide a larger stability margin of time-varying delay for MGLFC with TCL participation. Finally, the effectiveness of the model and the advantages of the proposed method are verified by numerical calculation, simulation tests, and experiments. The results indicate that, compared with the existing methods, the proposed criterion can obtain a larger delay margin without increasing the computational complexity under the same controller gains. In addition, with the participation of TCL, MGLFC performs a larger time-delay tolerance and can well resist the negative effects of time delays.

Due to the active defense of benign worms against the damage imposed by worms, benign worms have been paid enough attention by network security researchers. This paper presents patching structured benign worms, and we designed their deployment and work mechanism. Furthermore, the process of patching structured benign worms countering against worms is modeled based on the infectious model. Finally, the model was simulated. From the simulation, two factors (detection rate of the sensor and delay time), which affect the process of patching structured benign worms countering against worms, were summarized. The model of patching structured benign worms leads to a better understanding and prediction of the scale and speed of benign worms countering against the propagation of worms.

This study focuses on the mean square couple-group consensus of a heterogeneous multi-agent system with time delay and Markov switching. Based on heterogeneity, time delay, competitive-cooperative relations, and stochastic switching, new protocols have been developed to achieve the mean square couple-group consensus of this system. Sufficient conditions have been achieved for the mean square couple-group consensus of this system by using the properties of stochastic indecomposable and aperiodic matrices, stochastic delta operator, graph theory, and linear matrix inequality techniques. These findings demonstrate that some strict demands for the topology, such as strong connectivity or a spanning tree, can be relaxed. The reliability of our findings has been evaluated by several numerical experiments.

The parameter identification of a nonlinear Hammerstein-type process is likely to be complex and challenging due to the existence of significant nonlinearity at the input side. In this paper, a new parameter identification strategy for a block-oriented Hammerstein process is proposed using the Haar wavelet operational matrix (HWOM). To determine all the parameters in the Hammerstein model, a special input excitation is utilized to separate the identification problem of the linear subsystem from the complete nonlinear process. During the first test period, a simple step response data is utilized to estimate the linear subsystem dynamics. Then, the overall system response to sinusoidal input is used to estimate nonlinearity in the process. A single-pole fractional order transfer function with time delay is used to model the linear subsystem. In order to reduce the mathematical complexity resulting from the fractional derivatives of signals, a HWOM based algebraic approach is developed. The proposed method is proven to be simple and robust in the presence of measurement noises. The numerical study illustrates the efficiency of the proposed modeling technique through four different nonlinear processes and results are compared with existing methods.