Sökning: "vulnerabilities"
Visar resultat 1 - 5 av 739 uppsatser innehållade ordet vulnerabilities.
1. INTRODUCTION OF CYBERSECURITY INTO VERIFICATION PROCESSES FOR CONSTRUCTION EQUIPMENT : Cybersecurity Verification
Master-uppsats, Mälardalens universitet/Inbyggda systemSammanfattning : Technology is evolving at a very fast pace in various domains, including the construction equipment industry. Although the increased automation and connectivity in different products, such as vehicles, heavy machinery, and many others, have advantages, they also have disadvantages. LÄS MER
2. Kurds in the Crossfire: Trump's Troop Withdrawal, Statelessness and Political Interests
Kandidat-uppsats, Linnéuniversitetet/Institutionen för statsvetenskap (ST)Sammanfattning : This research adopts a theoretical framework grounded in political realism, serving as the guiding principle that shapes the analysis and drives the theory-driven exploration of President Donald Trump’s withdrawal of U.S. forces from Rojava. LÄS MER
3. EVALUATING CRYSTAL FRAMEWORK IN PRACTICE
Kandidat-uppsats, Mälardalens universitet/Akademin för innovation, design och teknikSammanfattning : Cyber-physical systems (CPSs) are used in several industries, such as healthcare, automotive, manufacturing, and more. The fact that CPSs often contain components integrated via communication networks means that malicious actors can exploit vulnerabilities in these components through cyber attacks. LÄS MER
4. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models
Master-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : Federated Learning (FL) has emerged as a promising approach for decentralized model training across multiple devices, while still preserving data privacy. Previous research has predominantly concentrated on classification tasks in FL settings, leaving a noticeable gap in FL research specifically for regression models. LÄS MER
5. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models
Master-uppsats, Umeå universitet/Institutionen för tillämpad fysik och elektronikSammanfattning : Federated Learning (FL) has emerged as a promising approach for decentralized model training across multiple devices, while still preserving data privacy. Previous research has predominantly concentrated on classification tasks in FL settings, leaving a noticeable gap in FL research specifically for regression models. LÄS MER