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  • 1. Caldwell, Sean On Traffic Analysis of 4G/LTE Traffic

    Master of Science in Electrical Engineering, Cleveland State University, 2021, Washkewicz College of Engineering

    In this thesis, we draw attention to the problem of cross-service attacks, that is, attacks that exploit information collected about users from one service to launch an attack on the same users on another service. With the increased deployment and use of what fundamentally are integrated-services networks, such as 4G/LTE networks and now 5G, we expect that cross-service attacks will become easier to stage and therefore more prevalent. As running example to illustrate the effectiveness and the potential impact of cross-service attacks we will use the problem of account association in 4G/LTE networks. Account association attacks aim at determining whether a target mobile phone number is associated with a particular online account. In the case of 4G/LTE, the adversary launches the account association attacks by sending SMS messages to the target phone number and analyzing patterns in traffic related to the online account. We evaluate the proposed attacks in both a local 4G/LTE testbed and a major commercial 4G/LTE network. Our extensive experiments show that the proposed attacks can successfully identify account association with close-to-zero false negative and false positive rates. Our experiments also illustrate that the proposed attacks can be launched in a way that the victim receives no indication of being under attack.

    Committee: Ye Zhu (Committee Chair); Yongjain Fu (Committee Member); Sui-Tung Yau (Committee Member) Subjects: Computer Engineering; Computer Science; Electrical Engineering; Information Technology; Technology
  • 2. Haldar, Kuheli Efficient Quality of Service Provision Techniques in Next Generation Wireless Networks

    PhD, University of Cincinnati, 2014, Engineering and Applied Science: Computer Science and Engineering

    Recent evolution of communication networks comprises of different segments and technologies, where each segment maybe implemented using different QoS. Further, the proposed all-IP core infrastructure of the future networks will offer varying QoS level multimedia services to the users. However, IP being a best effort service, seamless provision of end-to-end QoS guarantees is extremely important. In today's world, devices with multiple networking capabilities is quite common. The traditional approach in networking includes grouping identical traffic and allocating them to the network that has the maximum available data rate. This creates unbalanced traffic load in the network, leading to poor utilization of the associated resources. This problem can be greatly alleviated if the traffic can be allocated intelligently to the networks. For fair traffic distribution, we modeled the AP of each network as a single queuing server. Then, suitable equations and algorithms are designed to divide the incoming traffic flow into multiple subflows and allocated to the APs based on their available data rates. Network Selection in a Heterogeneous Cognitive Radio Wireless Network is a challenging task, since the users need to select the appropriate channels of the network in addition to the network itself. The varying levels of interference experienced by the secondary user (SUs) is due to the presence of primary user (PU)s in the adjacent channels. Hence, SUs transmitting highly sensitive data must find a channel that is interference free. In this dissertation, we develop a novel network and channel selection scheme that categorizes both the user applications and the network channels depending on their sensitivity level for interference and select them using a bipartite graph matching algorithm. The effectiveness of Cognitive Radios is based on opportunistic access of the licensed channels by SUs while protecting the PU transmission. But channel sensing incurs cost in terms (open full item for complete abstract)

    Committee: Dharma Agrawal D.Sc. (Committee Chair); Raj Bhatnagar Ph.D. (Committee Member); Yizong Cheng Ph.D. (Committee Member); Chia Han Ph.D. (Committee Member); Yiming Hu Ph.D. (Committee Member) Subjects: Computer Science