Related papers: Preventing Malware Pandemics in Mobile Devices by …
We consider the spread of epidemics in technological and social networks. How do people react? Does awareness and cautious behavior help? We analyze these questions and present a dynamic model to describe the movement of individuals and/or…
Malware attacks in today's vast digital ecosystem pose a serious threat. Understanding malware propagation dynamics and designing effective control strategies are therefore essential. In this work, we propose a generic SEIRV model…
The ubiquity of portable wireless-enabled computing and communications devices has stimulated the emergence of malicious codes (wireless worms) that are capable of spreading between spatially proximal devices. The potential exists for worms…
Malicious mobile phone worms spread between devices via short-range Bluetooth contacts, similar to the propagation of human and other biological viruses. Recent work has employed models from epidemiology and complex networks to analyse the…
In our more and more interconnected world, a specific risk is that of a cyber-epidemic (or cyber-pandemic), produced either accidentally or intentionally, where a cyber virus propagates from device to device up to undermining the global…
Epidemics of infectious diseases are among the largest threats to the quality of life and the economic and social well-being of developing countries. The arsenal of measures against such epidemics is well-established, but costly and…
This paper presents a new multi-agent model for simulating malware propagation in device-to-device (D2D) 5G networks. This model allows to understand and analyze mobile malware-spreading dynamics in such highly dynamical networks.…
We present a mobile app solution to help the containment of an epidemic outbreak by keeping track of possible infections in the incubation period. We consider the particular case of an infection which primarily spreads among people through…
Mobile malware and mobile network attacks are becoming a significant threat that accompanies the increasing popularity of smart phones and tablets. Thus in this paper we present our research vision that aims to develop a network-based…
Billions of wireless devices are foreseen to participate in big data aggregation and smart automation in order to interface the cyber and physical worlds. Such large-scale ultra-dense wireless connectivity is vulnerable to malicious…
With the hit of new pandemic threats, scientific frameworks are needed to understand the unfolding of the epidemic. The use of mobile apps that are able to trace contacts is of utmost importance in order to control new infected cases and…
Computer malware and biological pathogens often use similar mechanisms of infections. For this reason, it has been suggested to model malware spread using epidemiological models developed to characterize the spread of biological pathogens.…
Modeling infection spread during pandemics is not new, with models using past data to tune simulation parameters for predictions. These help understand the healthcare burden posed by a pandemic and respond accordingly. However, the problem…
We model the mobility of mobile phone users to study the fundamental spreading patterns characterizing a mobile virus outbreak. We find that while Bluetooth viruses can reach all susceptible handsets with time, they spread slowly due to…
The rapid proliferation of Internet of Things (IoT) devices in recent years has resulted in a significant surge in the number of cyber-attacks targeting these devices. Recent data indicates that the number of such attacks has increased by…
A model of the spread of viruses in selected city and in a network of cities is considered, taking into account the delay caused by the long incubation period of the virus. The effect of delay effects is shown in comparison with pandemics…
We introduce and analyze models for the propagation of malware in pure D2D networks given via stationary Cox-Gilbert graphs. Here, the devices form a Poisson point process with random intensity measure $\lambda\Lambda$, where $\Lambda$ is…
A new model for the spread of mobile malware based on proximity (i.e. Bluetooth, ad-hoc WiFi or NFC) is introduced. The spread of malware is analyzed using a Monte Carlo method and the results of the simulation are compared with those from…
Nowadays, epidemic models provide an appropriate tool for describing the propagation of biological viruses in human or animal populations, or rumours and other kinds of information in social networks and malware in both computer and ad hoc…
Nowadays, mobile handsets combine the functionality of mobile phones and PDAs. Unfortunately, mobile handsets development process has been driven by market demand, focusing on new features and neglecting security. So, it is imperative to…