<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Moustaka, Vaia</style></author><author><style face="normal" font="default" size="100%">Zenonas Theodosiou</style></author><author><style face="normal" font="default" size="100%">Athena Vakali</style></author><author><style face="normal" font="default" size="100%">Anastasis Kounoudes</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Smart Cities at Risk!: Privacy and Security Borderlines  from Social Networking in Cities</style></title><tertiary-title><style face="normal" font="default" size="100%">WWW ’18 Companion </style></tertiary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">online social networks</style></keyword><keyword><style  face="normal" font="default" size="100%">privacy threats</style></keyword><keyword><style  face="normal" font="default" size="100%">security threats</style></keyword><keyword><style  face="normal" font="default" size="100%">smart cities</style></keyword><keyword><style  face="normal" font="default" size="100%">smart living</style></keyword><keyword><style  face="normal" font="default" size="100%">smart people</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">Lyon, France</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;As smart cities infrastructures mature, data becomes a valuable asset which can radically improve city services and tools. Registration, acquisition and utilization of data, which will be transformed into smart services, are becoming more necessary than ever. Online social networks with their enormous momentum are one of the main sources of urban data offering heterogeneous real-time data at a minimal cost. However, various types of attacks often appear on them, which risk users' privacy and affect their online trust. The purpose of this article is to investigate how risks on online social networks affect smart cities and study the differences between privacy and security threats with regard to smart people and smart living dimensions.&lt;/p&gt;
</style></abstract><orig-pub><style face="normal" font="default" size="100%">WWW ’18 Companion </style></orig-pub></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Antonia Gogoglou</style></author><author><style face="normal" font="default" size="100%">Zenonas Theodosiou</style></author><author><style face="normal" font="default" size="100%">Tasos Kounoudes</style></author><author><style face="normal" font="default" size="100%">Athena Vakali</style></author><author><style face="normal" font="default" size="100%">Yannis Manolopoulos</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Early Malicious Activity Discovery in Microblogs by Social Bridges Detection</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><publisher><style face="normal" font="default" size="100%">16th International Symposium on Signal Processing and Information Technology</style></publisher><pub-location><style face="normal" font="default" size="100%">Limassol, Cyprus</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;With the emerging and intense use of Online Social Networks (OSNs) amongst young children and teenagers (youngters), safe networking and socializing on the Web has faced extensive scrutiny. Content and interactions which are considered safe for adult OSN users, might embed potentially threatening and malicious information when it comes to underage users. This work is motivated by the strong need to safeguard youngsters OSNs experience such that they can be empowered and aware. The topology of a graph is studied towards detecting the so called social bridges, i.e. the group(s) of malicious users and their supporters, who have links and ties to both honest and malicious user communities. A graph-topology based classification scheme is proposed to detect such bridge linkages which are suspicious for threatening youngsters networking vulnerability. The proposed scheme is validated by a Twitter network, at which potentially dangerous users are identified based on their Twitter connections. The achieved performance is higher compared to previous efforts, despite the increased complexity due to the variety of groups identified as malicious.&lt;/p&gt;
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