Inferring Social Ties in Academic Networks Using Short-Range Wireless Communications

International audienceWiFi base stations are increasingly deployed in both public spaces and private companies, and the increase in their density poses a significant threat to the privacy of connected users. Prior studies have provided evidence that it is possible to infer the social ties of users from their location and co-location traces but they lack one important component: the comparison of the inference accuracy between an internal attacker (e.g., a curious application running on a mobile device) and a realistic external eavesdropper in the same field trial. In this paper, we experimentally show that such an eavesdropper is able to infer the type of social relationships between mobile users better than an internal attacker. Moreover, our results indicate that by exploiting the underlying social community structure of mobile users, the accuracy of the inference attacks doubles. Based on our findings, we propose countermeasures to help users protect their privacy against eavesdroppers

Key Issues that apply to Wireless Local Area Networks (WLANs) Technology from a Study of the Chinese Campuses and UK Equivalent

With wireless technology developing quickly, the wireless network service has become more popular on university campuses. More and more universities provide wireless Internet access to all users in academic buildings and students villages and throughout the entire campus. The availability of wireless APs (Access Points) throughout campus offers many educational opportunities and learning benefits for faculty, staff and students. Compared with the wired local area network, WLANs (Wireless Local Area Networks) have many advantages, particularly in the area covered. However there are some issues with WLANs that are problematic for network managers such as usage, the signal stability and security. This investigation focuses on technical issues surrounding WLANs on the university campuses. Comparisons are made between the usage on campuses in the UK and China and a traffic model is created to enable simulations to be run on OPNET. This enables infrastructure comparisons to be made between different WLAN technologies such as WiFi and WiMAX and, following the analysis, conclusions to be drawn

Contextual Localization Through Network Traffic Analysis

opportunitiesforcontentserviceproviderstooptimizethecontent delivery based on user’s location. Since sharing precise location remainsamajorprivacyconcernamongtheusers,manylocationbased services rely on contextual location (e.g. residence, cafe etc.) as opposed to acquiring user’s exact physical location. In this paper, we present PACL (Privacy-Aware Contextual Localizer), which can learn user’s contextual location just by passively monitoring user’s network traffic. PACL can discern a set of vital attributes (statistical and application-based) from user’s network traffic, and predict user’s contextual location with a very high accuracy.WedesignandevaluatePACLusingreal-worldnetwork traces of over 1700 users with over 100 gigabytes of total data. OurresultsshowthatPACL(builtusingdecisiontree)canpredict user’s contextual location with the accuracy of around 87%. I

Discovering and Predicting Temporal Patterns of WiFi-interactive Social Populations

Extensive efforts have been devoted to characterizing the rich connectivity patterns among the nodes (components) of such complex networks (systems), and in the course of development of research in this area, people have been prompted to address on a fundamental question: How does the fascinating yet complex topological features of a network affect or determine the collective behavior and performance of the networked system? While elegant attempts to address this core issue have been made, for example, from the viewpoints of synchronization, epidemics, evolutionary cooperation, and the control of complex networks, theoretically or empirically, this widely concerned key question still remains open in the newly emergent field of network science. Such fruitful advances also push the desire to understand (mobile) social networks and characterize human social populations with the interdependent collective dynamics as well as the behavioral patterns. Nowadays, a great deal of digital technologies are unobtrusively embedded into the physical world of human daily activities, which offer unparalleled opportunities to explosively digitize human physical interactions, who is contacting with whom at what time. Such powerful technologies include the Bluetooth, the active Radio Frequency Identification (RFID) technology, wireless sensors and, more close to our interest in this paper, the WiFi technology. As a snapshot of the modern society, a university is in the coverage of WiFi signals, where the WiFi system records the digital access logs of the authorized WiFi users when they access the campus wireless services. Such WiFi access records, as the indirect proxy data, work as the effective proxy of a large-scale population's social interactions.Comment: 11 pages, 10 page

Reliability, availability and security of wireless networks in the community

Wireless networking increases the flexibility in the home, work place and community to connect to the Internet without being tied to a single location. Wireless networking has rapidly increased in popularity over recent years. There has also been a change in the use of the internet by users. Home users have embraced wireless technology and businesses see it as having a great impact on their operational efficiency. Both home users and industry are sending increasingly sensitive information through these wireless networks as online delivery of banking, commercial and governmental services becomes more widespread. However undeniable the benefits of wireless networking are, there are additional risks that do not exist in wired networks. It is imperative that adequate assessment and management of risk is undertaken by businesses and home users. This paper reviews wireless network protocols, investigates issues of reliability, availability and security when using wireless networks. The paper, by use of a case study, illustrates the issues and importance of implementing secured wireless networks, and shows the significance of the issue. The paper presents a discussion of the case study and a set of recommendations to mitigate the threat

Modeling mobility patterns

This work focuses on analysis and model generation for user mobility patterns given a sequence of observed WiFi signals. Built on the Android platform, the data collection mobile application gathers WiFi sensor readings (BSSID and SSID). The implemented pipeline performs location identification using an online hierarchical timeline clustering algorithm and segmentation algorithm. The segmentation algorithm constructs a tree of location candidates which are then aggregated by a similarity measure based on their BSSID and SSID features. The generated locations are processed to extract mobility patterns. A pattern is a sequence of location transitions which have high information content, high activity over time, and high degree of predictability. Each of these aspects are described by a numerical measure based on statistical properties of the location observations in a feature space

A framework for determining the adoption of new services in the South African mobile telecommunications market

Abstract in English, Afrikaans and ZuluThe aim of this study was to determine the key factors which explain the adoption of mobile data services in South Africa and incorporate them into an explanatory framework that can be used to indicate whether a new mobile data service that is introduced into the South African Mobile Market will be successful. Additionally, it shows that the current usage of mobile data services in South Africa supports the framework. The research used a design based on a mixed methods methodology. The research was conducted using a literature survey and two research phases. The literature survey was an extensive review of communication technology adoption frameworks and all the possible factors of adoption. This literature survey was also used to develop the discussion document which was used as the guidelines for the Phase 1 interviews. The interviews were with experts in the telecommunications market in South Africa and were used to determine the key drivers of adoption and possible moderating factors of mobile data services. From those interviews a preliminary model was proposed. Phase 2 was a market survey which tested the framework and moderating factors in different metropolitan areas as well as examined the current usage of mobile data services. The statistical analysis used in determining the framework incorporated Descriptive Statistics, Factor Analysis, using Principal Axis Factoring, and Structural Equation Modelling. The framework, which was based on the Technology Acceptance Model, introduced two new constructs. The first new construct was the Mobile Service Providers Marketing Tactics and the second was Social Pressure and Aspirational Value. The two constructs combined can be used to explain why mobile service providers with low cost strategies are not successful. Demographic factors such as Age were found to influence the adoption as well as Socio-economic factors such as Income. Personal factors such as Technical Knowledge, Ability and Skills and Attitude towards Technology were also found to influence adoption. Geographical location was found to be the most important moderating factor. The current mobile data usage supported the framework. The results of data usage highlighted the fact that nearly 50% of the study’s participants spent over 4 hours per day interacting with their mobile devices and that the participants from Gauteng spent more than 2½ times on mobile services than those in the other metropolitan municipalities of Cape Town and eThekwiniDie doel van hierdie studie was om die sleutelfaktore te bepaal wat die aanneming van selfoondatadienste in Suid-Afrika verklaar, en hulle te verenig in ʼn raamwerk waarmee aangetoon kan word of ʼn nuwe selfoondatadiens die Suid-Afrikaanse selfoondatamark suksesvol sal betree. Afgesien hiervan dui hierdie studie aan dat die huidige gebruik van selfoondatadienste in Suid-Afrika die geldigheid van die voorgestelde raamwerk bevestig. ʼn Mengsel van metodes is in die navorsing toegepas. Die navorsing het uit ʼn literatuuroorsig en twee navorsingsfases bestaan. Die literatuuroorsig het ʼn deurtastende oorsig van die raamwerke vir die aanneming van kommunikasietegnologie en alle moontlike faktore daarvoor behels. Uit die literatuuroorsig is die besprekingsdokument saamgestel wat as riglyn gedien het vir die onderhoude in fase 1 van die navorsing. Onderhoude is met kundiges uit die Suid-Afrikaanse telekommunikasiebedryf gevoer om die belangrikste dryfvere vir aanneming en moontlike remfaktore ten opsigte van selfoondatadienste te bepaal. ʼn Voorlopige model is op grond van die onderhoude aangebied. Fase 2 het ʼn markopname behels waarin die raamwerk en remfaktore in verskeie metropolitaanse gebiede getoets en die huidige gebruik van selfoondatadienste ondersoek is. Die statistiese analise waarop die raamwerk berus, het bestaan uit beskrywende statistiek, faktorontleding met behulp van hoofasfaktorering, en struktuurvergelykingsmodellering. Twee nuwe konstrukte het uit die raamwerk wat op die tegnologieaanvaardingsmodel gegrond was, gespruit. Die eerste was selfoondiensverskaffers se bemarkingstrategieë en die tweede sosiale druk en aspirerende waarde. Saam verklaar die twee konstrukte waarom selfoondiensverskaffers wat laekostestrategieë volg, misluk. Daar is bevind dat demografiese faktore soos ouderdom, en sosiaal-ekonomiese faktore soos inkomste, aanneming beïnvloed. Volgens die bevindings word aanneming eweneens bepaal deur persoonlike faktore soos tegniese kennis, vermoë en vaardighede asook houding jeens tegnologie. Daar is bevind dat geografiese ligging die belangrikste remfaktor is. Die huidige selfoondatagebruik bevestig die geldigheid van die raamwerk. Die uitslag van datagebruik benadruk die feit dat byna 50% van die deelnemers aan die studie langer as vier uur per dag met hulle selfone doenig is, en dat deelnemers in Gauteng twee en half keer meer as deelnemers in die metropolitaanse munisipaliteite van Kaapstad en eThekwini aan selfoondienste bestee.Inhloso yalolu cwaningo bekuwukuthola izinto ezibalulekile ezichaza ukwamukelwa kwezinsiza zamadatha amaselula eNingizimu Afrika nokuzifaka ohlakeni oluchazayo olungasetshenziswa ukukhombisa ukuthi ngabe insiza entsha yedatha ethulwe emakethe yamaselula eNingizimu Afrika izophumelela. Ngaphezu kwalokho, kukhombisa ukuthi ukusetshenziswa kwamanje kwezinsiza zedatha yamaselula eNingizimu Afrika kuyalusekela uhlaka. Ucwaningo lusebenzise umklamu osuselwe ezindleleni zokwenza ezixubile. Ucwaningo lwenziwe kusetshenziswa ucwaningo lwezincwadi kanye nezigaba ezimbili zocwaningo. Ucwaningo lwezincwadi belungukubuyekezwa okubanzi kokwamukela kwenzinhlaka zobuchwepheshe kwezokuxhumana kanye nazo zonke izici ezingenzeka ukuthi zamukelwe. Lolu cwaningo lwezincwadi lusetshenzisiwe futhi ukuthuthukisa umqulu wezingxoxo osetshenziswe njengezinkombandlela zokuxoxisana nabantu besigaba 1. Izingxoxo ebezinazo bezingochwepheshe emakethe yezokuxhumana eNingizimu Afrika futhi zasetshenziselwa ukuthola izidingongqangi zokwamukelwa kanye nezici zokulingisanisa kwezinsiza zamadatha amaselula. Kulezo zingxoxo, kuphakanyiswe isifaniselo sokuqala. Isigaba 2 bekungukucwaningo lwezimakethe oluhlola uhlaka kanye nezici zokulinganisa ezindaweni ezahlukahlukene zedolobha kanye nokuhlola ukusetshenziswa kwamanje kwezinsiza zedatha yamaselula. Ukuhlaziywa kwezibalo okusetshenzisiwe ekunqumeni uhlaka lufake izibalo ezichazayo, ukuhlaziya izakhi, kusetshenziswa izisekelo eziyinhloko zokuphamba, kanye nesifaniselo sokulinganisa esihlelekile. Uhlaka, olwalususelwa kusifaniselo sokwamukela ubuchwepheshe, lwethule izakhiwo ezimbili ezintsha. Isakhiwo esisha sokuqala kwakungamacebo wokukhangisa wabahlinzeki bezinsiza zamaselula futhi owesibili kwakuyingcindezi yomphakathi nenani lesifiso. Lezi zakhiwo zombili ezihlanganisiwe zingasetshenziswa ukuchaza ukuthi kungani abahlinzeki bezinsizakalo zamaselula abanamasu ezindleko eziphansi bengaphumeleli. Izici ezithinta abantu ezinjengobudala zitholakele ukuthonya ukwamukelwa kanye nezici zezomnotho nezenhlalo ezifana nomholo. Izici ezithinta umuntu ngqo ezifana nolwazi lwezobuchwepheshe, ukwazi ukwenza kanye namakhono, nesimo sengqondo maqondana nezobuchwepheshe zatholakala zithonya ukwamukelwa. Indawo yendawo yatholakala njengesici sokulinganisa esibaluleke kakhulu. Ukusetshenziswa kwedatha yeselula yamanje kusekele uhlaka. Imiphumela yokusetshenziswa kwedatha igcizelele iqiniso lokuthi bacishe babe ngama-50% ababambe iqhaza kulolu cwaningo bachithe isikhathi esingaphezu kwamahora amane ngosuku bexhumana nemishini yabo yamaselula nokuthi ababambiqhaza abavela eGauteng bachithe izikhathi ezingaphezu kwezingu-2½ kuzinsiza zamaselula kunalabo bakwamanye amadolobha amakhulu aseKapa naseThekwini.Business ManagementD.B.L