Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 13 of 13 for “"Network anomaly"”.
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Closed-loop network anomaly detection
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms
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Network Anomaly Detection with Incomplete Audit Data
… ever increasing deployment and usage of gigabit networks, traditional network anomaly detection based intrusion detection systems have not scaled accordingly. Most, if not all, systems deployed assume the availability of complete and clean data for the purpose of intrusion detection. We contend …
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Analysis and Evaluation of Social Network Anomaly Detection
As social networks become more prevalent, there is significant interest in studying these network data, the focus often being on detecting anomalous events. This area of research is referred to as social network surveillance or social network change detection. While there are a variety of proposed …
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Network anomaly detection using management information base (MIB) network traffic variables
… multi-tier, multiple-observation-window, network anomaly detection system (NADS) is introduced, namely, the MIB Anomaly Detection (MAD) system, which is capable of detecting and diagnosing network anomalies (including network faults and Denial of Service computer network attacks) …
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SuperB: Superior Behavior-based Anomaly Detection Defining Authorized Users' Traffic Patterns
<p>Network anomalies are correlated to activities that deviate from regular behavior patterns in a network, and they are undetectable until their actions are defined as malicious. Current work in network anomaly detection includes network-based and host-based intrusion detection systems. However, …
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Detection of network anomalies and novel attacks in the internet via statistical network traffic separation and normality prediction
… commerce environment, adaptive/automatic network and service anomaly detection is fast gaining critical research and practical importance. If the next generation of network technology is to operate beyond the levels of current networks, it will require a set of well-designed tools for its …
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Network Intrusion Detection: Monitoring, Simulation And Visualization
This dissertation presents our work on network intrusion detection and intrusion sim- ulation. The work in intrusion detection consists of two different network anomaly-based approaches. The work in intrusion simulation introduces a model using explicit traffic gen- eration for the packet level …
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Distributed AI-defense for Cyber Threats on Edge Computing Systems
… These uncontrolled variables expose physical, network, and application attack opportunities, often using newer and more exploitable protocols with limited protections. To tackle this issue, edge-level threat and attack detection systems require specialized solutions that leverage the local …
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Multiscale Modelling of Powder Bed Fusion with Electron Beam Process
L'abstract è presente nell'allegato / the abstract is in the attachment
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Implementation and simulation of mobile sensor networks for nuclear radiation detection
… make radiation detection a challenging problem. Anomaly detection, source localization, and isotope identification are three major parts of radiation detection. The concept of mobile radiation sensor networks, which utilize multiple mobile radiation detectors, has been proposed to solve these …
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Modeling Damage Evolution and Damage Healing using Data Driven Method
… contributions: (1) We used zero-bias deep neural networks to analyze a multisource dataset developed by Pragathi comprising grayscale images and strain contours during composite materials processing. We also utilized a Zero-Bias Deep Neural Network model to effectively detect defects in composite …
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Exploring anomaly detection methods using features extracted with a neural network
Anomaly (or outlier) detection is a problem with the goal of detecting outliers—or anomalous samples—within a dataset or distribution. Anomaly detection has important applications in computer vision, cybersecurity, biomedical imaging, and more. As the data becomes bigger (more samples collected) …
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Data Intensive Method For Processing Defect Detection and Mitigation For Composites
… the lack of in situ imaging data and effective anomaly detection models trained specifically for defect detection during composite curing. In this study, different methods were proposed to detect and reduce processing defects in conventional and additive manufacturing of composite materials. For …