Kablosuz algılayıcı ağlar kullanan askeri uygulamalar için devs tabanlı güvenlik analizi

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Kablosuz Algılayıcı Ağlar (KAA); bilginin toplanması, kısmi işlenmesi ve iletimi için tasarlanmış, dağıtık uygulama ve ortak hareket edebilme kabiliyetine sahip ancak sınırlı hafıza, sınırlı işlem gücü, sınırlı güç kaynağı ve sınırlı iletim dezavantajlarını barındıran algılayıcı düğümlerden oluşan sistemlerdir. KAA sistemlerinin askeri amaçlı olarak kritik bina, bölge güvenliği ve sınır izleme amaçlı kullanımı uzun zamandan bu yana araştırılmakta, önemli model ve uygulamalar ortaya konulmaktadır. BU tez çalışmamızda KAA yapısının askeri maksatlı kullanımı için kurulum ve işletim maliyetlerin düşürülmesi, sistemden alınacak hedef tespit ve izleme verilerine verilecek olası tepkilerin anlamlı hale getirilmesi hedeflenmiştir. Çalışmamızda yaygın olan görüntü işleme tabanlı sistemler yerine hedefin konum, hız ve yükseklik/boy bilgilerinin işlenmesi yolu ile tehdit analizi yapabilecek DEVS tabanlı bir güvenlik modeli ortaya konmuştur.Wireless Sensor Networks(WSN) system, which are designed for collection, partially operating and transmission of information, are composed of sensor nodes which have the ability of making common action and distributed application. However this nodes have limited memory, processing capacity, power supplies and transmission feasibility. Several researches and crucial simulation have been carried out for a long time so as to use WSN for military purposes such as; for the security of critical structures, critical zones and for border tracking. In this dissertation study we intended to minimise the installation and the operation cost of using the WSN for military purposes and make possible which will be received from the systems, meaningful. Instead of image processing based systems, in our study, we designed a DEVS(Discrete Event System) based security model which is able to make a thread assessment by using the height, position and speed of target

Fault tolerant target localization and tracking in binary WSNs using sensor health state estimation

Tracking of a source (target) which is moving inside a binary Wireless Sensor Network (WSN) is a challenging problem particularly when sensors may fail either due to hardware and/or software malfunctions, energy depletion or adversary attacks. Using information from failed sensors to locate and track a target may lead to high estimation errors, therefore, there is a need to develop fault tolerant localization algorithms which perform well even when a percentage of the sensors report erroneous observations. Alternatively, one may fuse information from neighboring sensors in order to determine the health state of each sensor, and subsequently use only healthy sensors in the localization and tracking process. Our contribution is the development of an architecture which combines the sensor health state estimation together with fault tolerant localization algorithms that leads to more robust target tracking in binary WSNs. Simulation results indicate that the proposed approach is resilient to various types of faults

Fault tolerant target localization and tracking in binary WSNs using sensor health state estimation

Tracking of a source (target) which is moving inside a binary Wireless Sensor Network (WSN) is a challenging problem particularly when sensors may fail either due to hardware and/or software malfunctions, energy depletion or adversary attacks. Using information from failed sensors to locate and track a target may lead to high estimation errors, therefore, there is a need to develop fault tolerant localization algorithms which perform well even when a percentage of the sensors report erroneous observations. Alternatively, one may fuse information from neighboring sensors in order to determine the health state of each sensor, and subsequently use only healthy sensors in the localization and tracking process. Our contribution is the development of an architecture which combines the sensor health state estimation together with fault tolerant localization algorithms that leads to more robust target tracking in binary WSNs. Simulation results indicate that the proposed approach is resilient to various types of faults