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Network traffic generators are invaluable tools that allow for applied experimentation to evaluate the performance of networks, infrastructure, and security controls, by modelling and simulating the communication packets and payloads that would be produced by machines and devices on the network. Specifically for security applications, these tools can be used to consistently simulate malicious activity on the network and test the components designed to detect and mitigate malicious activities, in a highly reliable and customisable way. However, despite the promising features, most of these tools have some problems that can undermine the correctness of experiments. The accuracy of the simulation results depends strongly on the performance and reliability of the used generator. Thus, in this paper, we investigate the performance and accuracy of three of the most reviewed network traffic generators in literature, namely Cisco TRex, Ostinato and Genesids. Mainly, the comparative experiments examine the strengths and limitations of these tools, which can help the research community to choose the most suitable one to assess the performance of their networks and security controls, Comment: 10 pages, 7 figures. World Congress on Internet Security (WorldCIS-2020)

The rapid increase in the use of IoT devices brings many benefits to the digital society, ranging from improved efficiency to higher productivity. However, the limited resources and the open nature of these devices make them vulnerable to various cyber threats. A single compromised device can have an impact on the whole network and lead to major security and physical damages. This paper explores the potential of using network profiling and machine learning to secure IoT against cyber-attacks. The proposed anomaly-based intrusion detection solution dynamically and actively profiles and monitors all networked devices for the detection of IoT device tampering attempts as well as suspicious network transactions. Any deviation from the defined profile is considered to be an attack and is subject to further analysis. Raw traffic is also passed on to the machine learning classifier for examination and identification of potential attacks. Performance assessment of the proposed methodology is conducted on the Cyber-Trust testbed using normal and malicious network traffic. The experimental results show that the proposed anomaly detection system delivers promising results with an overall accuracy of 98.35% and 0.98% of false-positive alarms., Comment: 11 pages, 4 figures, 2 tables

The nonlinear forcing terms for the wave equation in general curvilinear coordinates are derived based on a hyperelastic material. The expressions for the nonlinear part of the first Piola-Kirchhoff stress are specialized for axisymmetric torsional and longitudinal fundamental wave fields in a cylinder. The matrix characteristics of the nonlinear forcing terms and secondary mode wavestructures are manipulated to analyze the higher harmonic generation due to the guided wave mode self interactions and mutual interactions. It is proven that both torsional and longitudinal mode secondary fields can be cumulative by specific type of guided wave mode interactions. A method for the selection of preferred fundamental excitations that generate strongly cumulative higher harmonics is formulated, and described in detail for second harmonic generation. Hyperelastic finite element models are built to simulate second harmonic generation by T(0,3) and L(0,4) modes. A linear increase of the modal amplitude ratio A2/A1^2 over the propagation distance is observed for both cases, which indicates mode L(0,5) is effectively generated as cumulative second harmonics., Comment: 36 pages, 6 figures, to appear in Journal of the Acoustical Society of America

This study is the final report from the National Center for Education Statistics task force on redesign of the Integrated Postsecondary Education Data System (IPEDS). Following an executive summary outlining the need for changes and a series of recommendations, Section 1 details the reasons, goals, and processes involved in the IPEDS redesign. Section 2 outlines recommended actions for the new IPEDS, including an implementation schedule and the resources required. A key element is the recommendation for a Web-based data collection system. Section 3 offers alternative options, recognizing that a Web-based system demands development of software and appropriate resources which might not be available. Attachments include: a listing of statutory data requirements specified in laws and regulations; the current components of IPEDS; externally mandated changes and additions to IPEDS; issues examined in the redesign; a discussion of the issues, origins, and potential solutions; and lists of groups, organizations and individuals consulted. (RH)