Search results for " Network Security"

showing 5 items of 5 documents

Bio-inspired security analysis for IoT scenarios

2020

Computer security has recently become more and more important as the world economy dependency from data has kept growing. The complexity of the systems that need to be kept secure calls for new models capable of abstracting the interdependencies among heterogeneous components that cooperate at providing the desired service. A promising approach is attack graph analysis, however, the manual analysis of attack graphs is tedious and error prone. In this paper we propose to apply the metabolic network model to attack graph analysis, using three interacting bio-inspired algorithms: topological analysis, flux balance analysis, and extreme pathway analysis. A developed framework for graph building…

Bio-inspired techniqueService (systems architecture)Security analysisIoTDependency (UML)Computer scienceNetwork securityDistributed computingmedia_common.quotation_subject0211 other engineering and technologies02 engineering and technologyMetabolic networksAttack graphs; Bio-inspired algorithms; Bio-inspired techniques; IoT; Metabolic networks; Network security; Security analysis; System securityAttack graph03 medical and health sciences0302 clinical medicineUse casemedia_common021110 strategic defence & security studiesSecurity analysisbusiness.industryMetabolic network030208 emergency & critical care medicineBio-inspired techniquesNetwork securitySystem securityFlux balance analysisInterdependenceHardware and ArchitectureBio-inspired algorithmGraph (abstract data type)businessSoftwareAttack graphsBio-inspired algorithms
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A bio-inspired approach to attack graphs analysis

2018

Computer security has recently become more and more important as the world economy dependency from data has kept growing. The complexity of the systems that need to be kept secure calls for new models capable of abstracting the interdependencies among heterogeneous components that cooperate at providing the desired service. A promising approach is attack graph analysis, however the manual analysis of attack graphs is tedious and error prone. In this paper we propose to apply the metabolic network model to attack graphs analysis, using three interacting bio-inspired algorithms: topological analysis, flux balance analysis, and extreme pathway analysis. A developed framework for graph building…

Bio-inspired techniqueTheoretical computer scienceComputer scienceNetwork securitybusiness.industrymedia_common.quotation_subjectComputer Science (all)Bio-inspired techniquesNetwork securityAttack graphPathway analysisFlux balance analysisTheoretical Computer ScienceInterdependenceAttack graphMetabolic network modelAttack graphs; Bio-inspired techniques; Network securityGraph (abstract data type)businessAttack graphsmedia_common
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A TRNG Exploiting Multi-Source Physical Data

2010

In recent years, the considerable progress of miniaturization and the consequent increase of the efficiency of digital circuits has allowed a great diffusion of the wireless sensor network technology. This has led to the growth of applications and protocols for applying these networks to several scenarios, such as the military one, where it is essential to deploy security protocols in order to prevent opponents from accessing the information exchanged among sensor nodes. This paper analyzes security issues of data processed by the WSN and describes a system able to generate sequences of random numbers, which can be used by security algorithms and protocols. The proposed True Random Number G…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniRandom number generationbusiness.industryNetwork securityComputer scienceDistributed computingNode (networking)Cryptographic protocolTrusted third partyKey distribution in wireless sensor networksWireless Sensor Networks Random Number Generator Network SecurityNISTbusinessWireless sensor networkComputer network
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SpADe: Multi-Stage Spam Account Detection for Online Social Networks

2022

In recent years, Online Social Networks (OSNs) have radically changed the way people communicate. The most widely used platforms, such as Facebook, Youtube, and Instagram, claim more than one billion monthly active users each. Beyond these, news-oriented micro-blogging services, e.g., Twitter, are daily accessed by more than 120 million users sharing contents from all over the world. Unfortunately, legitimate users of the OSNs are mixed with malicious ones, which are interested in spreading unwanted, misleading, harmful, or discriminatory content. Spam detection in OSNs is generally approached by considering the characteristics of the account under analysis, its connection with the rest of …

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSocial Network Security Spam Detection Artificial IntelligenceElectrical and Electronic EngineeringIEEE Transactions on Dependable and Secure Computing
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Twitter spam account detection by effective labeling

2019

In the last years, the widespread diffusion of Online Social Networks (OSNs) has enabled new forms of communications that make it easier for people to interact remotely. Unfortunately, one of the first consequences of such a popularity is the increasing number of malicious users who sign-up and use OSNs for non-legit activities. In this paper we focus on spam detection, and present some preliminary results of a system that aims at speeding up the creation of a large-scale annotated dataset for spam account detection on Twitter. To this aim, two different algorithms capable of capturing the spammer behaviors, i.e., to share malicious urls and recurrent contents, are exploited. Experimental r…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSocial Network Security Spam Detection Twitter Data Analysis
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