Conceptualizing human resilience in the face of the global epidemiology of cyber attacks

Computer security is a complex global phenomenon where different populations interact, and the infection of one person creates risk for another. Given the dynamics and scope of cyber campaigns, studies of local resilience without reference to global populations are inadequate. In this paper we describe a set of minimal requirements for implementing a global epidemiological infrastructure to understand and respond to large-scale computer security outbreaks. We enumerate the relevant dimensions, the applicable measurement tools, and define a systematic approach to evaluate cyber security resilience. From the experience in conceptualizing and designing a cross-national coordinated phishing resilience evaluation we describe the cultural, logistic, and regulatory challenges to this proposed public health approach to global computer assault resilience. We conclude that mechanisms for systematic evaluations of global attacks and the resilience against those attacks exist. Coordinated global science is needed to address organised global ecrime

A Monte Carlo method for the spread of mobile malware

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 mean field theory.Comment: 11 pages, 2 figure

A Model of Virus Infection Dynamics in Mobile Personal Area Network

In this paper, the authors explore the mobile network security focused on the virus threat. Firstly, the authors explain the importance of mobile network security which sometimes not really takes into considerations by users. This paper then explains the virus threat of mobile devices virus where it explains how the viruses spread. The threats can be in three major forms namely the virus spreading via mobile personal area network, virus spreading via internet access and virus spreading via messaging. Lastly a model explains the dynamics of the infection on Mobile Network is introduced

A Survey on Security for Mobile Devices

Nowadays, mobile devices are an important part of our everyday lives since they enable us to access a large variety of ubiquitous services. In recent years, the availability of these ubiquitous and mobile services has signicantly increased due to the dierent form of connectivity provided by mobile devices, such as GSM, GPRS, Bluetooth and Wi-Fi. In the same trend, the number and typologies of vulnerabilities exploiting these services and communication channels have increased as well. Therefore, smartphones may now represent an ideal target for malware writers. As the number of vulnerabilities and, hence, of attacks increase, there has been a corresponding rise of security solutions proposed by researchers. Due to the fact that this research eld is immature and still unexplored in depth, with this paper we aim to provide a structured and comprehensive overview of the research on security solutions for mobile devices. This paper surveys the state of the art on threats, vulnerabilities and security solutions over the period 2004-2011. We focus on high-level attacks, such those to user applications, through SMS/MMS, denial-of-service, overcharging and privacy. We group existing approaches aimed at protecting mobile devices against these classes of attacks into dierent categories, based upon the detection principles, architectures, collected data and operating systems, especially focusing on IDS-based models and tools. With this categorization we aim to provide an easy and concise view of the underlying model adopted by each approach

Mathematical network models applied to the analysis of mobile applications behavior

[EN] The network topologies are present in different social, political, economic and technological phenomena. These network structures allow to share information, alliances generation, behavior influence, opinion spread and virus transmission, among other aspects. Online networks are a reflection of the offline world and they also show these kind of network structures, in such a way that they allow the information transmission, social circle or community detection, affinity prediction between individuals, generation of recommendations, detection of influence people and generation of viral phenomena. Although all of these networks exhibit heterogeneity, they have enough underlying structure to allow their modelization for the study and analysis of all the listed phenomena. Nowadays, the line between the offline world and the online world is becoming more diffuse and there are network structures where both natures are mixed: There are almost as many mobile phones as individuals and in developed societies, the pervasiveness of smartphones on day-to-day is unquestionable in such a way that almost everybody is almost always connected everywhere. This permanent connection means that the individual, simultaneously and in a continuous mode, is a node belonging to its social network and its social network online. A key aspect of smartphones are the mobile applications that can be downloaded to the device. There are many applications for a host of different uses and the user behavior with these applications is the factor that determines how these applications behave. Also, mobile applications are the main source of infection of viruses on smartphones and, in this case, also the user behavior is what determines the transmission of these viruses. That is, the number of downloads of the application, the retention time of the application without being uninstalled, weekly minutes of usage, the popularity of the application, the transmission of viruses between smartphones, etc., depend on user behavior and, since the user is part of a social "offline" network and a social online network, in which the information is shared, communities are generated, behavior is influenced, opinion is spread and viruses are transmitted, we can intuit that the application behaviors can be modeled considering the network structure which user belongs to, so it is possible to analyze and study issues such as predicting the retention and download of applications and/or the transmission of viruses between smartphones. The purpose of this thesis is to analyze the behavior of mobile applications through mathematical network models. The behavior of mobile applications will be defined by the network of the users, taking into account parameters such as user behavior and technical issues of the mobile devices, so for model the networks both factors will be taken into account.[ES] Las estructuras de redes están presentes en multitud de fenómenos sociales, políticos, económicos y tecnológicos. Estas estructuras permiten compartir información, constituir alianzas, influir en comportamientos, generar corrientes de opinión, y transmitir virus, entre otros aspectos. Las redes online son un reflejo del mundo "analógico" y también presentan este tipo de estructura de red, de tal forma que permiten transmitir información, detectar comunidades, predecir afinidades entre individuos, generar recomendaciones, identificar individuos influyentes o producir fenómenos virales. Aunque todas estas redes son de naturaleza heterogénea, la estructura subyacente que presentan permiten su modelización para el estudio y análisis de los fenómenos indicados. Actualmente, la línea que divide el mundo "analógico" y el mundo online es cada vez más difusa produciéndose estructuras de redes donde se entremezclan ambas naturalezas: Existen casi tantos teléfonos móviles como individuos y, en las sociedades desarrolladas, la omnipresencia de los smartphones en el día día es incuestionable de tal forma que cualquier persona está conectada casi en todo momento y lugar. Esta conexión permanente conlleva que el individuo constituya simultáneamente y de un modo continuo un nodo de su estructura de red social y de su red social online. Una parte fundamental de los smartphones son las aplicaciones que se pueden descargar en el dispositivo. Existen multitud de aplicaciones para infinidad de utilidades distintas y el comportamiento del usuario frente a esas aplicaciones es el que determina cómo se comportan dichas aplicaciones. Asimismo, las aplicaciones móviles son la principal fuente de contagio de virus en los smartphones y en este caso, también el comportamiento del usuario es el que determina la transmisión de esos virus. Es decir, el número de descargas de la aplicación, el tiempo de retención de la aplicación sin ser desinstalada, los minutos semanales de uso, la popularidad de la aplicación, la transmisión de virus en smartphones, etc., dependen del comportamiento del usuario y, puesto que el usuario forma parte de una red social "offline" y una red social online, en las cuales se comparte y transmite información, se constituyen comunidades, se influye en los comportamientos, se generan corrientes de opinión y se transmiten virus, podemos intuir que los comportamientos de las aplicaciones pueden ser modelizados considerando la estructura de red de la que el usuario forma parte, de tal forma que sea posible analizar y estudiar aspectos tales como predecir la descarga y retención de aplicaciones y/o la transmisión de virus entre smartphones. El propósito de la presente tesis doctoral es modelizar y analizar el comportamiento de las aplicaciones móviles mediante estructuras de red. El comportamiento de las aplicaciones móviles vendrá definido por la red formada por los usuarios, teniendo en cuenta tanto parámetros de comportamiento de los usuarios como parámetros relacionados con aspectos técnicos de los dispositivos móviles, por lo que para la modelización de las redes se tendrán en cuenta ambos factores.[CA] Les estructures de xarxes estàn presents en multitud de fenòmens socials, pol'itics, econòmics i tecnològics. Estes estructures permeten compartir informació, constituir aliances, influir en comportaments, generar corrents d'opinió, i transmetre virus, entre altres aspectes. Les xarxes online són un reflex del món analògic i també presenten este tipus d'estructura de xarxa, de tal forma que permet transmetre informació, detectar comunitats, predir afinitats entre individus, generar recomanacions, identificar individus influents o produir fenòmens virals. Encara que totes estes xarxes són de naturalesa heterogènia, l'estructura subjacent que presenten permeten la seua modelització per a l'estudi i anàlisi dels fenòmens indicats. Actualment, la línia que dividix el món analògic i el món online és cada vegada més difusa produintse estructures de xarxes on s'entremesclen ambós naturaleses: Existixen quasi tants telèfons mòbils com individus i, en les societats desenvolupades, l'omnipresència dels smartphones en el dia a dia és inqüestionable de tal forma que qualsevol persona està connectada quasi en tot moment i lloc. Esta connexió permanent comporta que l'individu constituïsca simultàniament i d'una manera contínua un node de la seua estructura de xarxa social i de la seua xarxa social online. Una part fonamental dels smartphones són les aplicacions que es poden descarregar en el dispositiu. Hi ha multitud d'aplicacions per a infinitat d'utilitats distintes i el comportament de l'usuari enfront d'eixes aplicacions és el que determina com es comporten aquestes aplicacions. Així mateix, les aplicacions mòbils són la principal font de contagi de virus en els smartphones i en este cas, també el comportament de l'usuari és el que determina la transmissió d'eixos virus. És a dir, el nombre de descàrregues de l'aplicació, el temps de retenció de l'aplicació sense ser esborrada, els minuts setmanals d'ús, la popularitat de l'aplicació, la transmissió de virus entre smartphones, etc., depenen del comportament de l'usuari i, ja que l'usuari forma part d'una xarxa social "offline" i una xarxa social online, en les quals es compartix i es transmet informació, es constituïxen comunitats, s'influïx en els comportaments, es generen corrents d'opinió i es transmeten virus, podem intuir que els comportaments de les aplicacions poden ser modelitzats considerant l'estructura de xarxa de què l'usuari forma part, de tal forma que siga possible analitzar i estudiar aspectes com ara predir la descàrrega i retenció d'aplicacions i/o la transmissió de virus entre smartphones. El propòsit de la present tesi doctoral és modelitzar i analitzar el comportament de les aplicacions mòbils per mitjà d'estructures de xarxa. El comportament de les aplicacions mòbils vindrà definit per la xarxa formada pels usuaris, tenint en compte tant paràmetres de comportament dels usuaris com paràmetres relacionats amb aspectes tècnics dels dispositius mòbils, per la qual cosa per a la modelització de les xarxes es tindràn en compte ambdós factors.Alegre Sanahuja, J. (2016). Mathematical network models applied to the analysis of mobile applications behavior [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/67389TESI

The influence of user mobility in mobile virus propagation: An enterprise mobile security perspective

In this paper, the authors review the usage of mobile devices in the enterprise and also the major impact from the infected mobile devices.Then the authors highlight the virus threat to enterprise mobile security and how critical the problems are.The authors then discuss the mobile virus infection dynamics which are the Bluetooth infections, mobile emails infections and mobile internet infections which are the threats to the enterprise mobile security. Then the authors discuss on the influences of user mobility issue in spreading mobile viruses before concluded this article