Essays about: "Adversarial Attack Detection"
Showing result 1 - 5 of 6 essays containing the words Adversarial Attack Detection.
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1. AI for Cybersecurity : A Study on Machine Learning and DoS Attacks AI Robustness and Bypassing Detection Methods
University essay from Högskolan i Halmstad/Akademin för informationsteknologiAbstract : Cybercrime has increased for several years; both in volume andsophistication. When the capabilities of threat actors increase, techniques andtactics within cybersecurity also need to evolve. AI and machine learninghave potential to prevent and mitigate attacks. READ MORE
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2. Anomalous Behavior Detection in Aircraft based Automatic Dependent Surveillance–Broadcast (ADS-B) system using Deep Graph Convolution and Generative model (GA-GAN)
University essay from Linköpings universitet/Databas och informationsteknikAbstract : The Automatic Dependent Surveillance-Broadcast (ADS-B) is a key component of the Next Generation Air Transportation System (Next Gen) that manages the increasingly congested airspace and operation. From Jan 2020, the U.S. Federal Aviation Administration (FAA) mandated the use of (ADS-B) as a key component of Next Gen project. READ MORE
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3. Generation and Detection of Adversarial Attacks in the Power Grid
University essay from Uppsala universitet/Avdelningen för systemteknikAbstract : Machine learning models are vulnerable to adversarial attacks that add perturbations to the input data. Here we model and simulate power flow in a power grid test case and generate adversarial attacks for these measurements in three different ways. READ MORE
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4. Generation and Detection of Adversarial Attacks for Reinforcement Learning Policies
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In this project we investigate the susceptibility ofreinforcement rearning (RL) algorithms to adversarial attacks.Adversarial attacks have been proven to be very effective atreducing performance of deep learning classifiers, and recently,have also been shown to reduce performance of RL agents. READ MORE
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5. On the Use of Model-Agnostic Interpretation Methods as Defense Against Adversarial Input Attacks on Tabular Data
University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskapAbstract : Context. Machine learning is a constantly developing subfield within the artificial intelligence field. The number of domains in which we deploy machine learning models is constantly growing and the systems using these models spread almost unnoticeably in our daily lives through different devices. READ MORE
