A Method for Reducing the Severity of Epidemics by Allocating Vaccines According to Centrality

One long-standing question in epidemiological research is how best to allocate limited amounts of vaccine or similar preventative measures in order to minimize the severity of an epidemic. Much of the literature on the problem of vaccine allocation has focused on influenza epidemics and used mathematical models of epidemic spread to determine the effectiveness of proposed methods. Our work applies computational models of epidemics to the problem of geographically allocating a limited number of vaccines within several Texas counties. We developed a graph-based, stochastic model for epidemics that is based on the SEIR model, and tested vaccine allocation methods based on multiple centrality measures. This approach provides an alternative method for addressing the vaccine allocation problem, which can be combined with more conventional approaches to yield more effective epidemic suppression strategies. We found that allocation methods based on in-degree and inverse betweenness centralities tended to be the most effective at containing epidemics.Comment: 10 pages, accepted to ACM BCB 201

Modelling the malware propagation in mobile computer devices

Nowadays malware is a major threat to the security of cyber activities. The rapid development of the Internet and the progressive implementation of the Internet of Things (IoT) increase the security needs of networks. This research presents a theoretical model of malware propagation for mobile computer devices. It is based on the susceptible-exposed-infected-recovered-susceptible (SEIRS) epidemic model. The scheme is based on a concrete connection pattern between nodes defined by both a particular neighbourhood which fixes the connection between devices, and a local rule which sets whether the link is infective or not. The results corroborate the ability of our model to perform the behaviour patterns provided by the ordinary differential equation (ODE) traditional method

Malware propagation in Wireless Sensor Networks: global models vs Individual-based models

The main goal of this work is to propose a new framework to design a novel family of mathematical models to simulate malware spreading in wireless sensor networks (WSNs). An analysis of the proposed models in the scientific literature reveals that the great majority are global models based on systems of ordinary differential equations such that they do not consider the individual characteristics of the sensors and their local interactions. This is a major drawback when WSNs are considered. Taking into account the main characteristics of WSNs (elements and topologies of network, life cycle of the nodes, etc.) it is shown that individual-based models are more suitable for this purpose than global ones. The main features of this new type of malware propagation models for WSNs are stated

Simulación de la propagación del malware: modelos continuos vs. modelos discretos

La gran mayoría de modelos matemáticos propuestos hasta la fecha para simular la propagación del malware están basados en el uso de ecuaciones diferenciales. Dichos modelos son analizados de manera crítica en este trabajo, determinando las principales deficiencias que presentan y planteando distintas alternativas para su subsanación. En este sentido, se estudia el uso de los autómatas celulares como nuevo paradigma en el que basar los modelos epidemiológicos, proponiendo una alternativa explícita basada en ellos a un reciente modelo continuo.Este trabajo ha sido subvencionado por el Ministerio de Economía y Competitividad bajo el proyecto TUERI (TIN2011-25452) y por la Consejería de Educación de la Junta de Castilla y León

A two years simulation using a real data cellular automaton: A predictive case study with the schistosomiasis expansion process along the coastline of Brazil

This work presents a Cellular Automata model to characterize the social and environmental factors which contribute for the analysis of the expansion process of Schistosoma mansoni infection in Pernambuco - Brazil. The model has been experimented with a set of two years real data from a study area at North Coast of Pernambuco – Brazil. The main constraint equations, the modelling process and the results obtained until now with the simulating scenarios generated are presented here. The results identify, as in field works, endemic areas and human risk infection areas. Furthermore, predictive scenarios for a look ahead with a perspective into fifteen years are also presented.Peer ReviewedPostprint (published version

A novel dynamics model of fault propagation and equilibrium analysis in complex dynamical communication network

International audienceTo describe failure propagation dynamics in complex dynamical communication networks, we propose an efficient and compartmental standard-exception-failure propagation dynamics model based on the method of modeling disease propagation in social networks. Mathematical formulas are derived and differential equations are solved to analyze the equilibrium of the propagation dynamics. Stability is evaluated in terms of the balance factor G and it is shown that equilibrium where the number of nodes in different states does not change, is globally asymptotically stable if G≥1. The theoretical results derived are verified by numerical simulations. We also investigate the effect of some network parameters, e.g. node density and node movement speed, on the failure propagation dynamics in complex dynamical communication networks to gain insights for effective measures of control of the scale and duration of the failure propagation in complex dynamical communication networks

Моделювання розповсюдження комп'ютерних вірусів на основі імовірнісного клітинкового автомату

In conditions of malware volumes and types growth, which are generally called viruses, the actual problem is simulation of its propagation for taking preventive actions. There are models of computer viruses propagation in form of ordinary differentional equations, but it don’t pay appropriate attention to a space distribution and logical peculiarities, concentrating on a quantitative indexes. In the paper the virus modelling approach based on cellular automata is considered. The new model of virus propagation is proposed. The model differs by its possibility to take into account some features of malware replication, antivirus defence and antivirus influence on infection propagation. The model was applied to some practical examples, the information about infection distribution in the network was obtained as a simulation result. The proposed model can be adapted to different types of malware.В условиях возрастания объемов и видов вредоносного программного обеспечения, которое обобщенно называют вирусами, актуальной задачей является моделирование его распространения для принятия упреждающих мероприятий. Существуют модели распро-странения компьютерных вирусов в виде обыкновенных дифференциальных уравнений, но они не уделяют должного внимания их пространственному распределению и логическим особенностям, сосредотачиваясь на количественных показателях. В данной статье рассмотрен подход к моделированию вирусов на основе клеточного автомата, предложена новая модель распрострaнения вирусов, которая отличается возможностью учитывать некоторые черты самовоспроизвод-ства вредоносного ПО, принимает во внимание действие антивирусной защиты и ее влияние на распро-странение заражения. Модель применена к ряду практических примеров, в результате моделирования получена информация относительно распределения зара-жения в сети. Предложенная модель может быть адап-тирована к разным видам вредоносного ПО.В умовах зростання обсягів та видів шкідливого програмного забезпечення, яке узагальнено називають вірусами, актуальною задачею є моделювання його розповсюдження для прийняття запобіжних заходів. Існують моделі розповсюдження комп’ютерних вірусів у вигляді звичайних диференціальних рівнянь, але вони не приділяють належної уваги їх просторовому розповсюдженню та логічним особливостям, зосереджуючись на кількісних показниках. В даній статті розглянуто підхід до моделювання вірусів на основі клітинкового автомату, запропоновано нову модель розповсюдження вірусів, яка відрізняється можливістю враховувати деякі риси самовідтворення шкідливого ПЗ, бере до уваги дію антивірусного захисту та його вплив на розповсюдження зараження. Модель застосовано до ряду практичних прикладів, в результаті моделювання одержано інформацію щодо розподілу зараження мережею. Запропонована модель може бути адаптована до різних видів шкідливого ПЗ

ENSURING SPECIFICATION COMPLIANCE, ROBUSTNESS, AND SECURITY OF WIRELESS NETWORK PROTOCOLS

Several newly emerged wireless technologies (e.g., Internet-of-Things, Bluetooth, NFC)—extensively backed by the tech industry—are being widely adopted and have resulted in a proliferation of diverse smart appliances and gadgets (e.g., smart thermostat, wearables, smartphones), which has ensuingly shaped our modern digital life. These technologies include several communication protocols that usually have stringent requirements stated in their specifications. Failing to comply with such requirements can result in incorrect behaviors, interoperability issues, or even security vulnerabilities. Moreover, lack of robustness of the protocol implementation to malicious attacks—exploiting subtle vulnerabilities in the implementation—mounted by the compromised nodes in an adversarial environment can limit the practical utility of the implementation by impairing the performance of the protocol and can even have detrimental effects on the availability of the network. Even having a compliant and robust implementation alone may not suffice in many cases because these technologies often expose new attack surfaces as well as new propagation vectors, which can be exploited by unprecedented malware and can quickly lead to an epidemic

Novel Analytical Modelling-based Simulation of Worm Propagation in Unstructured Peer-to-Peer Networks

Millions of users world-wide are sharing content using Peer-to-Peer (P2P) networks, such as Skype and Bit Torrent. While such new innovations undoubtedly bring benefits, there are nevertheless some associated threats. One of the main hazards is that P2P worms can penetrate the network, even from a single node and then spread rapidly. Understanding the propagation process of such worms has always been a challenge for researchers. Different techniques, such as simulations and analytical models, have been adopted in the literature. While simulations provide results for specific input parameter values, analytical models are rather more general and potentially cover the whole spectrum of given parameter values. Many attempts have been made to model the worm propagation process in P2P networks. However, the reported analytical models to-date have failed to cover the whole spectrum of all relevant parameters and have therefore resulted in high false-positives. This consequently affects the immunization and mitigation strategies that are adopted to cope with an outbreak of worms. The first key contribution of this thesis is the development of a susceptible, exposed, infectious, and Recovered (SEIR) analytical model for the worm propagation process in a P2P network, taking into account different factors such as the configuration diversity of nodes, user behaviour and the infection time-lag. These factors have not been considered in an integrated form previously and have been either ignored or partially addressed in state-of-the-art analytical models. Our proposed SEIR analytical model holistically integrates, for the first time, these key factors in order to capture a more realistic representation of the whole worm propagation process. The second key contribution is the extension of the proposed SEIR model to the mobile M-SEIR model by investigating and incorporating the role of node mobility, the size of the worm and the bandwidth of wireless links in the worm propagation process in mobile P2P networks. The model was designed to be flexible and applicable to both wired and wireless nodes. The third contribution is the exploitation of a promising modelling paradigm, Agent-based Modelling (ABM), in the P2P worm modelling context. Specifically, to exploit the synergies between ABM and P2P, an integrated ABM-Based worm propagation model has been built and trialled in this research for the first time. The introduced model combines the implementation of common, complex P2P protocols, such as Gnutella and GIA, along with the aforementioned analytical models. Moreover, a comparative evaluation between ABM and conventional modelling tools has been carried out, to demonstrate the key benefits of ease of real-time analysis and visualisation. As a fourth contribution, the research was further extended by utilizing the proposed SEIR model to examine and evaluate a real-world data set on one of the most recent worms, namely, the Conficker worm. Verification of the model was achieved using ABM and conventional tools and by then comparing the results on the same data set with those derived from developed benchmark models. Finally, the research concludes that the worm propagation process is to a great extent affected by different factors such as configuration diversity, user-behaviour, the infection time lag and the mobility of nodes. It was found that the infection propagation values derived from state-of-the-art mathematical models are hypothetical and do not actually reflect real-world values. In summary, our comparative research study has shown that infection propagation can be reduced due to the natural immunity against worms that can be provided by a holistic exploitation of the range of factors proposed in this work