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Showing result 1 - 5 of 63 essays matching the above criteria.
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1. A Prevention Technique for DDoS Attacks in SDN using Ryu Controller Application
University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskapAbstract : Software Defined Networking (SDN) modernizes network control, offering streamlined management. However, its centralized structure makes it more vulnerable to distributed Denial of Service (DDoS) attacks, posing serious threats to network stability. READ MORE
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2. Quantum Espionage
University essay from KTH/Tillämpad fysikAbstract : This thesis investigates the security of optical fiber communication and demonstrates the feasibility of eavesdropping using different tapping methods and superconducting nanowire single-photon detectors (SNSPDs). Methods for surveillance against fiber intrusion are also investigated. READ MORE
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3. Hidden Markov Models for Intrusion Detection Under Background Activity
University essay from KTH/Matematisk statistikAbstract : Detecting a malicious hacker intruding on a network system can be difficult. This challenge is made even more complex by the network activity generated by normal users and by the fact that it is impossible to know the hacker’s exact actions. READ MORE
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4. Observability in Machine Learning based Intrusion Detection Systems for RPL-based IoT
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : As IoT devices become more and more present in our daily lives, security in IoT networks has become a major concern. A promising approach for detecting attacks is the use of machine learning based Intrusion Detection Systems (IDSs). The attack studied in this thesis is the blackhole attack, an attack causing parts of the network to disconnect. READ MORE
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5. Differentially Private Random Forests for Network Intrusion Detection in a Federated Learning Setting
University essay from Mittuniversitetet/Institutionen för data- och elektroteknik (2023-)Abstract : För varje dag som går möter stora industrier en ökad mängd intrång i sina IT-system. De flesta befintliga verktyg som använder sig utav maskininlärning är starkt beroende av stora mängder data, vilket innebär risker under dataöverföringen. READ MORE