2019
Karyotis, V.
A Markov Random Field Framework for Modeling Malware Propagation in Complex Communications Networks Journal Article
In: IEEE Transactions on Dependable and Secure Computing, vol. 16, no. 4, pp. 551-564, 2019, ISSN: 15455971, (cited By 10).
Abstract | Links | BibTeX | Tags: Complex networks; Image segmentation; Magnetorheological fluids; Markov processes; Simulated annealing; Stochastic systems; Structural frames, Gibbs sampling; Malware propagation; Markov Random Fields; Network robustness; Network science, Malware
@article{Karyotis2019551,
title = {A Markov Random Field Framework for Modeling Malware Propagation in Complex Communications Networks},
author = {V. Karyotis},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068941002&doi=10.1109%2fTDSC.2017.2703622&partnerID=40&md5=2eaddbe72ca542b6f71f846ca8250533},
doi = {10.1109/TDSC.2017.2703622},
issn = {15455971},
year = {2019},
date = {2019-01-01},
journal = {IEEE Transactions on Dependable and Secure Computing},
volume = {16},
number = {4},
pages = {551-564},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The proliferation of complex communication networks (CCNs) and their importance for maintaining social coherency nowadays have urgently elevated the need for protecting networking infrastructures from malicious software attacks. In this paper, we propose a Markov Random Field (MRF) based spatio-stochastic framework for modeling the macroscopic behavior of a CCN under random attack, where malicious threats propagate through direct interactions and follow the Susceptible-Infected-Susceptible infection paradigm. We exploit the MRF framework for analytically studying the propagation dynamics in various types of CCNs, i.e., lattice, random, scale-free, small-world and multihop graphs, in a holistic manner. By combining Gibbs sampling with simulated annealing, we study the behavior of the above systems for various topological and malware related parameters with respect to the general random attacks considered. We demonstrate the effectiveness of the MRF framework in capturing the evolution of SIS malware propagation and use it to assess the robustness of synthetic and real CCNs with respect to the involved parameters. It is found that random networks are more robust, followed by scale-free, regular and small-world, while multihop emerge as the most vulnerable of all. © 2004-2012 IEEE.},
note = {cited By 10},
keywords = {Complex networks; Image segmentation; Magnetorheological fluids; Markov processes; Simulated annealing; Stochastic systems; Structural frames, Gibbs sampling; Malware propagation; Markov Random Fields; Network robustness; Network science, Malware},
pubstate = {published},
tppubtype = {article}
}
The proliferation of complex communication networks (CCNs) and their importance for maintaining social coherency nowadays have urgently elevated the need for protecting networking infrastructures from malicious software attacks. In this paper, we propose a Markov Random Field (MRF) based spatio-stochastic framework for modeling the macroscopic behavior of a CCN under random attack, where malicious threats propagate through direct interactions and follow the Susceptible-Infected-Susceptible infection paradigm. We exploit the MRF framework for analytically studying the propagation dynamics in various types of CCNs, i.e., lattice, random, scale-free, small-world and multihop graphs, in a holistic manner. By combining Gibbs sampling with simulated annealing, we study the behavior of the above systems for various topological and malware related parameters with respect to the general random attacks considered. We demonstrate the effectiveness of the MRF framework in capturing the evolution of SIS malware propagation and use it to assess the robustness of synthetic and real CCNs with respect to the involved parameters. It is found that random networks are more robust, followed by scale-free, regular and small-world, while multihop emerge as the most vulnerable of all. © 2004-2012 IEEE.
2016
Karyotis, V.; Khouzani, M. H. R.
Malware Diffusion Models for Modern Complex Networks: Theory and Applications Book
Elsevier Inc., 2016, ISBN: 9780128027141, (cited By 34).
Abstract | Links | BibTeX | Tags: Application models; Calculus of variations; Communications networks; Diffusion process; General applications; Global economies; State of the art; Theoretical aspects, Application programs; Calculations; Complex networks; Computer crime; Computer games; Diffusion; Game theory; Information dissemination, Malware
@book{Karyotis20161,
title = {Malware Diffusion Models for Modern Complex Networks: Theory and Applications},
author = {V. Karyotis and M. H. R. Khouzani},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84966747178&doi=10.1016%2fC2014-0-02168-5&partnerID=40&md5=06baba5b752e60adbf37584ad2514605},
doi = {10.1016/C2014-0-02168-5},
isbn = {9780128027141},
year = {2016},
date = {2016-01-01},
journal = {Malware Diffusion Models for Modern Complex Networks: Theory and Applications},
pages = {1-296},
publisher = {Elsevier Inc.},
abstract = {Malware Diffusion Models for Wireless Complex Networks: Theory and Applications provides a timely update on malicious software (malware), a serious concern for all types of network users, from laymen to experienced administrators. As the proliferation of portable devices, namely smartphones and tablets, and their increased capabilities, has propelled the intensity of malware spreading and increased its consequences in social life and the global economy, this book provides the theoretical aspect of malware dissemination, also presenting modeling approaches that describe the behavior and dynamics of malware diffusion in various types of wireless complex networks. Sections include a systematic introduction to malware diffusion processes in computer and communications networks, an analysis of the latest state-of-the-art malware diffusion modeling frameworks, such as queuing-based techniques, calculus of variations based techniques, and game theory based techniques, also demonstrating how the methodologies can be used for modeling in more general applications and practical scenarios. Presents a timely update on malicious software (malware), a serious concern for all types of network users, from laymen to experienced administrators. Systematically introduces malware diffusion processes, providing the relevant mathematical background. Discusses malware modeling frameworks and how to apply them to complex wireless networks. Provides guidelines and directions for extending the corresponding theories in other application domains, demonstrating such possibility by using application models in information dissemination scenarios. © 2016 Elsevier Inc. All rights reserved.},
note = {cited By 34},
keywords = {Application models; Calculus of variations; Communications networks; Diffusion process; General applications; Global economies; State of the art; Theoretical aspects, Application programs; Calculations; Complex networks; Computer crime; Computer games; Diffusion; Game theory; Information dissemination, Malware},
pubstate = {published},
tppubtype = {book}
}
Malware Diffusion Models for Wireless Complex Networks: Theory and Applications provides a timely update on malicious software (malware), a serious concern for all types of network users, from laymen to experienced administrators. As the proliferation of portable devices, namely smartphones and tablets, and their increased capabilities, has propelled the intensity of malware spreading and increased its consequences in social life and the global economy, this book provides the theoretical aspect of malware dissemination, also presenting modeling approaches that describe the behavior and dynamics of malware diffusion in various types of wireless complex networks. Sections include a systematic introduction to malware diffusion processes in computer and communications networks, an analysis of the latest state-of-the-art malware diffusion modeling frameworks, such as queuing-based techniques, calculus of variations based techniques, and game theory based techniques, also demonstrating how the methodologies can be used for modeling in more general applications and practical scenarios. Presents a timely update on malicious software (malware), a serious concern for all types of network users, from laymen to experienced administrators. Systematically introduces malware diffusion processes, providing the relevant mathematical background. Discusses malware modeling frameworks and how to apply them to complex wireless networks. Provides guidelines and directions for extending the corresponding theories in other application domains, demonstrating such possibility by using application models in information dissemination scenarios. © 2016 Elsevier Inc. All rights reserved.
2014
Karyotis, V.; Papavassiliou, S.
Evaluation of malware spreading in wireless multihop networks with churn Journal Article
In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 140, pp. 63-74, 2014, ISSN: 18678211, (cited By 3; Conference of 6th International ICST Conference on Ad Hoc Networks, ADHOCNETS 2014 ; Conference Date: 18 August 2014 Through 19 August 2014; Conference Code:111559).
Abstract | Links | BibTeX | Tags: Computer crime; Wireless ad hoc networks, Distributed networks; Energy depletion; Internet access; Network behaviors; Network reliability; Network robustness; Queuing network; Wireless multi-hop network, Malware
@article{Karyotis201463,
title = {Evaluation of malware spreading in wireless multihop networks with churn},
author = {V. Karyotis and S. Papavassiliou},
editor = {Papavassiliou S. Gallais A. Mitton N.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84915750171&doi=10.1007%2f978-3-319-13329-4_6&partnerID=40&md5=a87d7ee86d6d9c71332184f75a466edb},
doi = {10.1007/978-3-319-13329-4_6},
issn = {18678211},
year = {2014},
date = {2014-01-01},
journal = {Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST},
volume = {140},
pages = {63-74},
publisher = {Springer Verlag},
abstract = {Modeling malware spreading in wireless networks has attracted significant interest lately, since this will increase the robustness of such networks that constitute the lion’s share of Internet access nowadays. However, all of previous works have considered networks with fixed number of devices. In this work, we focus on users that can dynamically join and leave the network (node churn) as a result of the effects of malware, or their own operation, i.e. energy depletion. We adopt and adapt a queuing-based model for malware spreading for the case of wireless distributed networks with churn. The corresponding methodology captures the dynamics of SIS-type malware, where nodes are always prone to receive new or already spreading infections over a long period. The employed framework can be exploited for quantifying network reliability and study network behavior, which can be further used for increasing the robustness of the system against the most severe attacks. © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2014.},
note = {cited By 3; Conference of 6th International ICST Conference on Ad Hoc Networks, ADHOCNETS 2014 ; Conference Date: 18 August 2014 Through 19 August 2014; Conference Code:111559},
keywords = {Computer crime; Wireless ad hoc networks, Distributed networks; Energy depletion; Internet access; Network behaviors; Network reliability; Network robustness; Queuing network; Wireless multi-hop network, Malware},
pubstate = {published},
tppubtype = {article}
}
Modeling malware spreading in wireless networks has attracted significant interest lately, since this will increase the robustness of such networks that constitute the lion’s share of Internet access nowadays. However, all of previous works have considered networks with fixed number of devices. In this work, we focus on users that can dynamically join and leave the network (node churn) as a result of the effects of malware, or their own operation, i.e. energy depletion. We adopt and adapt a queuing-based model for malware spreading for the case of wireless distributed networks with churn. The corresponding methodology captures the dynamics of SIS-type malware, where nodes are always prone to receive new or already spreading infections over a long period. The employed framework can be exploited for quantifying network reliability and study network behavior, which can be further used for increasing the robustness of the system against the most severe attacks. © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2014.