A review of state-of-the-art malware attack trends and defense mechanisms
The increasing sophistication of malware threats has led to growing concerns in the anti-
malware community, as malware poses a significant danger to online users despite the …
malware community, as malware poses a significant danger to online users despite the …
Deep learning-powered malware detection in cyberspace: a contemporary review
A Redhu, P Choudhary, K Srinivasan, TK Das - Frontiers in Physics, 2024 - frontiersin.org
This article explores deep learning models in the field of malware detection in cyberspace,
aiming to provide insights into their relevance and contributions. The primary objective of the …
aiming to provide insights into their relevance and contributions. The primary objective of the …
COVID-19 infection analysis framework using novel boosted CNNs and radiological images
COVID-19, a novel pathogen that emerged in late 2019, has the potential to cause
pneumonia with unique variants upon infection. Hence, the development of efficient …
pneumonia with unique variants upon infection. Hence, the development of efficient …
A malicious network traffic detection model based on bidirectional temporal convolutional network with multi-head self-attention mechanism
S Cai, H Xu, M Liu, Z Chen, G Zhang - Computers & Security, 2024 - Elsevier
The increasingly frequent network intrusions have brought serious impacts to the production
and life, thus malicious network traffic detection has received more and more attention in …
and life, thus malicious network traffic detection has received more and more attention in …
Intra-and inter-sector contextual information fusion with joint self-attention for file fragment classification
File fragment classification (FFC) aims to identify the file type of file fragments in memory
sectors, which is of great importance in memory forensics and information security. Existing …
sectors, which is of great importance in memory forensics and information security. Existing …
Evolving malware detection through instant dynamic graph inverse reinforcement learning
C Liu, B Li, X Liu, C Li, J Bao - Knowledge-Based Systems, 2024 - Elsevier
The rapid development and increasing evolution of malware necessitate novel defensive
techniques with high accuracy and minimal false positives to safeguard information systems …
techniques with high accuracy and minimal false positives to safeguard information systems …
Classification of Malware for Security Improvement in IoT using Heuristic Aided Adaptive Multi-scale and Dilated ResneXt with Gated Recurrent Unit
J Jagadeesan, S Nandhini, B Sathiyaprasad - Applied Soft Computing, 2024 - Elsevier
The rise of malware in the Internet of Things (IoT) realm exploits sensitive IoT devices that
lead to extensive malicious attacks that pose a significant danger to the integrity of the …
lead to extensive malicious attacks that pose a significant danger to the integrity of the …
A State-of-the-Art Review of Malware Attack Trends and Defense Mechanism.
The increasing sophistication of malware threats has led to growing concerns in the anti-
malware community, as malware poses a significant danger to online users despite the …
malware community, as malware poses a significant danger to online users despite the …
A Novel Decision Ensemble Framework: Customized Attention-BiLSTM and XGBoost for Speculative Stock Price Forecasting
RU Din, S Ahmed, SH Khan - arXiv preprint arXiv:2401.11621, 2024 - arxiv.org
Forecasting speculative stock prices is essential for effective investment risk management
that drives the need for the development of innovative algorithms. However, the speculative …
that drives the need for the development of innovative algorithms. However, the speculative …
The Role of LLMs in Sustainable Smart Cities: Applications, Challenges, and Future Directions
Smart cities stand as pivotal components in the ongoing pursuit of elevating urban living
standards, facilitating the rapid expansion of urban areas while efficiently managing …
standards, facilitating the rapid expansion of urban areas while efficiently managing …