|
|
|
Karolína Bílá
We attempt here to review recent studies focusing on droughts and hydrology in the ?umava Mts. The main question is can bark beetles affect water regimes in forest and what kind of measures might be taken ? if any ? to prevent bark beetle attacks. We com...
ver más
|
|
|
|
|
|
|
Hassan Khazane, Mohammed Ridouani, Fatima Salahdine and Naima Kaabouch
With the rapid advancements and notable achievements across various application domains, Machine Learning (ML) has become a vital element within the Internet of Things (IoT) ecosystem. Among these use cases is IoT security, where numerous systems are dep...
ver más
|
|
|
|
|
|
|
Saikat Das, Mohammad Ashrafuzzaman, Frederick T. Sheldon and Sajjan Shiva
The distributed denial of service (DDoS) attack is one of the most pernicious threats in cyberspace. Catastrophic failures over the past two decades have resulted in catastrophic and costly disruption of services across all sectors and critical infrastru...
ver más
|
|
|
|
|
|
|
Swati Kumari, Vatsal Tulshyan and Hitesh Tewari
Due to rising cyber threats, IoT devices? security vulnerabilities are expanding. However, these devices cannot run complicated security algorithms locally due to hardware restrictions. Data must be transferred to cloud nodes for processing, giving attac...
ver más
|
|
|
|
|
|
|
Davy Preuveneers and Wouter Joosen
Ontologies have the potential to play an important role in the cybersecurity landscape as they are able to provide a structured and standardized way to semantically represent and organize knowledge about a domain of interest. They help in unambiguously m...
ver más
|
|
|
|
|
|
|
Poornima Mahadevappa, Redhwan Al-amri, Gamal Alkawsi, Ammar Ahmed Alkahtani, Mohammed Fahad Alghenaim and Mohammed Alsamman
Edge data analytics refers to processing near data sources at the edge of the network to reduce delays in data transmission and, consequently, enable real-time interactions. However, data analytics at the edge introduces numerous security risks that can ...
ver más
|
|
|
|
|
|
|
Woonghee Lee, Mingeon Ju, Yura Sim, Young Kul Jung, Tae Hyung Kim and Younghoon Kim
Deep learning-based segmentation models have made a profound impact on medical procedures, with U-Net based computed tomography (CT) segmentation models exhibiting remarkable performance. Yet, even with these advances, these models are found to be vulner...
ver más
|
|
|
|
|
|
|
Sharoug Alzaidy and Hamad Binsalleeh
In the field of behavioral detection, deep learning has been extensively utilized. For example, deep learning models have been utilized to detect and classify malware. Deep learning, however, has vulnerabilities that can be exploited with crafted inputs,...
ver más
|
|
|
|
|
|
|
Meng Bi, Xianyun Yu, Zhida Jin and Jian Xu
In this paper, we propose an Iterative Greedy-Universal Adversarial Perturbations (IGUAP) approach based on an iterative greedy algorithm to create universal adversarial perturbations for acoustic prints. A thorough, objective account of the IG-UAP metho...
ver más
|
|
|
|
|
|
|
Hao An, Ruotong Ma, Yuhan Yan, Tailai Chen, Yuchen Zhao, Pan Li, Jifeng Li, Xinyue Wang, Dongchen Fan and Chunli Lv
This paper aims to address the increasingly severe security threats in financial systems by proposing a novel financial attack detection model, Finsformer. This model integrates the advanced Transformer architecture with the innovative cluster-attention ...
ver más
|
|
|
|