Sökning: "Network Robustness"

Visar resultat 1 - 5 av 180 uppsatser innehållade orden Network Robustness.

1. 1. A Comparative Analysis of SecurityServices Using Identity and AccessManagement (IAM)

   Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Nithya Sree Muddychetty; [2024]
   Nyckelord :Access Control Lists; Identity Access Management; Multi-Factor Authentication; One time password; Single sign on; System Usability Scale; Virtual private network;

   Sammanfattning : Background: Identity and Access Management (IAM) is a critical IT securityframework for managing digital identities and resource access. With roots datingback to ancient civilizations, IAM has evolved from basic authentication to sophisticated methods. LÄS MER

3. 2. Improvement of anautomatic networkdrawing algorithm in thecontext of utility networks

   Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

   Författare :Hyacinthe Ménard; [2024]
   Nyckelord :District Heating Network; Mathematical Optimization; Python; Fjärrvärme; Optimeringslära; Python;

   Sammanfattning : The European Union’s ambitious climate targets necessitate substantial reductions in greenhouse gas emissions, particularly within the heating and cooling sector, which accounts for a significant portion of energy consumption. District Heating and Cooling (DHC) systems emerge as a key solution for decarbonizing this sector by enabling high efficiency heat production and the integration of renewable and carbon-neutral energy sources. LÄS MER

4. 3. Neural Network-based Anomaly Detection Models and Interpretability Methods for Multivariate Time Series Data

   Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Deepthy Prasad; Swathi Hampapura Sripada; [2023]
   Nyckelord :multivariate - time series; anomaly detection; neural networks; autoencoders; interpretability; counterfactuals;

   Sammanfattning : Anomaly detection plays a crucial role in various domains, such as transportation, cybersecurity, and industrial monitoring, where the timely identification of unusual patterns or outliers is of utmost importance. Traditional statistical techniques have limitations in handling complex and highdimensional data, which motivates the use of deep learning approaches. LÄS MER

5. 4. Literature review on trustworthiness of Signature-Based and Anomaly detection in Wireless Networks

   Kandidat-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Josephine Spångberg; Vainius Mikelinskas; [2023]
   Nyckelord :Cyber threats; Malware; Cyber attacks; Signature Based Detection; Anomaly Detection; Cyber defense; Sophisticated attacks; Modern cyberattacks; malware detection in wireless network; IoT;

   Sammanfattning : The internet has become an essential part of most people's daily lives in recent years, and as more devices connect to the internet, the risk of cyber threats increases dramatically. As malware becomes more sophisticated, traditional security prevention measures are becoming less effective at defending from cyber attacks. LÄS MER

7. 5. Modulating Depth Map Features to Estimate 3D Human Pose via Multi-Task Variational Autoencoders

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Kobe Moerman; [2023]
   Nyckelord :3D pose estimation; Joint landmarks; Variational autoencoder; Multi-task model; Loss discrimination; Latent-space modulation; Depth map; 3D-positionsuppskattning; Gemensamma landmärken; Variationell autoencoder; Multitask-modell; Förlustdiskriminering; Latent-space-modulering; Djupkarta;

   Sammanfattning : Human pose estimation (HPE) constitutes a fundamental problem within the domain of computer vision, finding applications in diverse fields like motion analysis and human-computer interaction. This paper introduces innovative methodologies aimed at enhancing the accuracy and robustness of 3D joint estimation. LÄS MER