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 11 of 11 for “"Malicious Traffic"”.
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Polymorphic Adversarial DDoS attack on IDS using GAN
IDS are essential components in preventing malicious traffic from penetrating networks. IDS have been rapidly enhancing their detection ability using ML algorithms. As a result, attackers look for new methods to evade the IDS. Polymorphic attacks are favorites among the attackers as they can bypass …
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CLASSIFYING TCP NETWORK TRAFFIC FLOWS VIA TRAFFIC INTERACTION GRAPHS AND MACHINE LEARNING
Detecting malicious traffic on networks is a critical problem facing the Department of Defense. In this thesis we utilize cutting edge machine learning techniques to detect malicious network traffic. We begin with two real-world datasets. First, real internet traffic collected on the NPS Enterprise …
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Intrusion detection and prevention in advanced metering networks
… engine that examines both ingress and egress traffic to the AMI application layer. Policy engine rules may refer to the structure and behavior of the AMI protocol, and may also perform multi-stage analysis of data payloads and look for evidence that malicious content is carried, rather than …
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A fast and adaptive threat detection and prevention architecture
… a dataset by capturing both legitimate and malicious traffic and compare two ways of combining packets into flows, one gathering all packets in a time window and the other analyzing only the first few packets of each flow. Besides our created dataset, we also analyze our proposal on real …
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Statistical learning in network architecture
… component of the network's continued evolution. Malicious nodes, cooperative competition and lack of instrumentation on the Internet imply an environment with partial information. Learning is thus an attractive and principled means to ensure generality and reconcile noisy, missing or conflicting …
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Blockchain-based Architecture for Secured Cyberattack Signatures and Features Distribution
<p>One effective way of detecting malicious traffic in computer networks is intrusion detection systems (IDS). Despite the increased accuracy of IDSs, distributed or coordinated attacks can still go undetected because of the single vantage point of the IDSs. Due to this reason, there is a need for …
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Classification of Malicious Web Traffic
… turn this has made them attractive targets for malicious attacks. Given these trends there is a need to better understand and classify malicious cyber activities. The work presented in this thesis is based on malicious data collected by three high-interaction honeypots, and organized in HTTP …
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On mitigating distributed denial of service attacks
… a specified one, and (2) it can differentiate malicious traffic from normal ones. The receiver-center design avoids several related issues such as scalability, and lack of incentives to deploy a new scheme. Finally, conclusions are drawn and future works are discussed.
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Detection of HTTPS malware traffic without decryption
… social connections. More than 80% of internet traffic is encrypted using Transport Layer Security (TLS) protocol, and it is predicted that this number will increase [8]. However, threat actors are also increasingly using the TLS protocol to hide malicious activities such as Command and Control, …
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Robust Anomaly Detection in Critical Infrastructure
… knowledge of anomaly detection logic to generate malicious traffic that remains undetected. One way to solve this issue is to adopt adversarial training in which the training set is augmented with adversarially perturbed samples. This thesis presents an adversarial training approach called GADoT …
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Strengthening Privacy and Cybersecurity through Anonymization and Big Data
L'abstract è presente nell'allegato / the abstract is in the attachment