2,471 research outputs found

    Deep Learning Methods for Device Identification Using Symbols Trace Plot

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    Devices authentication is one crucial aspect of any communication system. Recently, the physical layer approach radio frequency (RF) fingerprinting has gained increased interest as it provides an extra layer of security without requiring additional components. In this work, we propose an RF fingerprinting based transmitter authentication approach density trace plot (DTP) to exploit device-identifiable fingerprints. By considering IQ imbalance solely as the feature source, DTP can efficiently extract device-identifiable fingerprints from symbol transition trajectories and density center drifts. In total, three DTP modalities based on constellation, eye and phase traces are respectively generated and tested against three deep learning classifiers: the 2D-CNN, 2D-CNN+biLSTM and 3D-CNN. The feasibility of these DTP and classifier pairs is verified using a practical dataset collected from the ADALM-PLUTO software-defined radios (SDRs)

    Detection of Abnormal SIP Signaling Patterns: A Deep Learning Comparison

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    UIDB/ 50008/2020This paper investigates the detection of abnormal sequences of signaling packets purposely generated to perpetuate signaling-based attacks in computer networks. The problem is studied for the Session Initiation Protocol (SIP) using a dataset of signaling packets exchanged by multiple end-users. A sequence of SIP messages never observed before can indicate possible exploitation of a vulnerability and its detection or prediction is of high importance to avoid security attacks due to unknown abnormal SIP dialogs. The paper starts to briefly characterize the adopted dataset and introduces multiple definitions to detail how the deep learning-based approach is adopted to detect possible attacks. The proposed solution is based on a convolutional neural network capable of exploring the definition of an orthogonal space representing the SIP dialogs. The space is then used to train the neural network model to classify the type of SIP dialog according to a sequence of SIP packets prior observed. The classifier of unknown SIP dialogs relies on the statistical properties of the supervised learning of known SIP dialogs. Experimental results are presented to assess the solution in terms of SIP dialogs prediction, unknown SIP dialogs detection, and computational performance, demonstrating the usefulness of the proposed methodology to rapidly detect signaling-based attacks.publishersversionpublishe

    Privacy-preserving network path validation

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    The end-users communicating over a network path currently have no control over the path. For a better quality of service, the source node often opts for a superior (or premium) network path in order to send packets to the destination node. However, the current Internet architecture provides no assurance that the packets indeed follow the designated path. Network path validation schemes address this issue and enable each node present on a network path to validate whether each packet has followed the specific path so far. In this work, we introduce two notions of privacy -- path privacy and index privacy -- in the context of network path validation. We show that, in case a network path validation scheme does not satisfy these two properties, the scheme is vulnerable to certain practical attacks (that affect the reliability, neutrality and quality of service offered by the underlying network). To the best of our knowledge, ours is the first work that addresses privacy issues related to network path validation. We design PrivNPV, a privacy-preserving network path validation protocol, that satisfies both path privacy and index privacy. We discuss several attacks related to network path validation and how PrivNPV defends against these attacks. Finally, we discuss the practicality of PrivNPV based on relevant parameters

    WiMAX Networks – architecture and data security

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    This document presents thorough information on the WiMAX technology, itsdetailed architecture and illustrates security mechanisms employed. The first part discusses basic properties and components of WiMAX network. Individual sub-layers of the network operation have been presented. The second part describes all security-related aspects and solutions employed to ensure secure data exchange: cryptographic keys generation and exchange, authentication processes and encrypted data exchange. The last part illustrates potential attacks, means of effective protection and methods for improving security in WiMAXnetworks

    Policy issues in interconnecting networks

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    To support the activities of the Federal Research Coordinating Committee (FRICC) in creating an interconnected set of networks to serve the research community, two workshops were held to address the technical support of policy issues that arise when interconnecting such networks. The workshops addressed the required and feasible technologies and architectures that could be used to satisfy the desired policies for interconnection. The results of the workshop are documented
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