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Jia, P., Liu, J., Fang, Y., Liu, L. and Liu, L. (2018) Modeling and Analyzing Malware Propagation in Social Networks with Heterogeneous Infection Rates. Physica A: Statistical Mechanics and Its Applications, 507, 240-254.
https://doi.org/10.1016/j.physa.2018.05.047

has been cited by the following article:

• TITLE: A New Model for Spreading Malware over SMS Using Network Automata

  AUTHORS: Erick Iván Medina-Salas, Ana Lilia Laureano-Cruces, Ma. Elena Lárraga-Ramírez

  KEYWORDS: Cellular Automaton, Malware Spread, Complex Systems, Network Automaton

  JOURNAL NAME: Communications and Network, Vol.15 No.4, November 24, 2023

  ABSTRACT: By the year 2026, it is estimated that the number of smartphone users in Mexico will be approximately 118.1 million. Each smartphone has the functionality of sending and receiving SMS (Short Message Service) messages, which pose a significant threat to all users, as it makes any device vulnerable to a malware attack. In particular, worm-type malware takes advantage of this means of communication in order to spread. Studying the dynamics of malware propagation can help understand and prevent massive contagion between mobile devices. In this work, a model based on Network Automata and compartmental epidemiological models is presented, aiming to simulate, analyze and study the spread of worm-like malware through sending SMS on smartphones.