Efficient cross-information fusion decoder for semantic segmentation

S Zhang, G Ren, X Zeng, L Zhang, K Du, G Liu… - Computer Vision and …, 2024 - Elsevier
For fine-scale prediction tasks such as semantic segmentation, existing segmentation
models cannot support detailed segmentation due to the difficulty of assigning deep feature …

Securing IoT networks in cloud computing environments: a real-time IDS

S Biswas, MSA Ansari - The Journal of Supercomputing, 2024 - Springer
Abstract The term “Internet of Things”(IoT) encompasses an entire group of gadgets that are
capable of connecting to the Internet in order to gather and share data. The IoT paradigm is …

[HTML][HTML] Robust PDF Watermarking against Print–Scan Attack

L Li, HJ Zhang, JL Meng, ZM Lu - Sensors, 2023 - mdpi.com
Portable document format (PDF) files are widely used in file transmission, exchange, and
circulation because of their platform independence, small size, good browsing quality, and …

Similarity learning; Siamese networks; MCESTA; triplet loss; similarity metrics.

E Debas, N Alhumam, K Riad - International Journal of …, 2024 - search.ebscohost.com
In contemporary times, the landscape of malware analysis has advanced into an era of
sophisticated threat detection. Today's malware sandboxes conduct rudimentary analyses …

[PDF][PDF] DDOS ATTACK-DETECTION APPROACH BASED ON ENSEMBLE MODELS USING SPARK.

Y Alslman, A Khalil, R Younisse, E Alnagi… - Jordanian Journal of …, 2024 - researchgate.net
We live in an era where time is the most precious resource. Thus, dealing with the vast
amount of data collected from different resources for various purposes requires creating …

Scrutinization of Threats from a Cloud-based Network Traffic Environment

S Chopra, AG Sreedevi - 2024 11th International Conference …, 2024 - ieeexplore.ieee.org
In this age of digitalization, securing computer networks is of utmost importance to protect
sensitive data and critical infrastructure. Threat scrutinization plays an integral role in …

Unlocking the Potential of Naïve Bayes for Network Intrusion Detection: A RandomForest-Driven Feature Selection Strategy

R ElRabaa, S Rawas, A El-Zaart - … International Conference on …, 2023 - ieeexplore.ieee.org
Network intrusion detection systems play an essential role for ensuring an organization's
security success. This study focuses on the most recent intrusion detection systems built …

Modeling Attacks on Machine Learning Components of Intrusion Detection Systems

E Ichetovkin, I Kotenko - 2024 International Russian Smart …, 2024 - ieeexplore.ieee.org
Intrusion detection systems (IDS) perform a critical security function and can detect both
known and unknown and more complex attacks. However, intrusion detection systems …

An Efficient Real-Time NIDS Using Machine Learning Methods

KS Goud, M Shivani, BVSS Reddy… - … on Cognitive Computing …, 2023 - Springer
Recent developments in network technology and related services have caused a significant
rise in data traffic. However, there has also been a massive rise in the negative …