4 days ago · A study published in The Journal of Engineering Research at Sultan Qaboos University presents an advanced intrusion detection system (IDS) designed to improve the accuracy and …

Jan 1, 2024 · The use of encrypted data, the diversity of new protocols, and the surge in the number of malicious activities worldwide have posed new challenges for…

Nov 5, 2025 · These cutting-edge systems are designed to detect emerging cyberthreats. The current study investigates and compares various types of IDS and AI-based techniques that use ML and DL …

Jun 10, 2024 · However, IDSs still struggle with accuracy, false alarms, and detecting new intrusions. Therefore, organizations are using Machine Learning (ML) and Deep Learning (DL) algorithms in IDS …

These strategies contribute to modern intrusion detection systems’ overall resilience and accuracy. Figure 1 depicts general IDS architecture and the primary components and pro-cesses.

To evaluate the performance of deep learning-based intrusion detection systems (IDS), several metrics are used to assess their accuracy and effectiveness in detecting cyber threats.

Abstract—Intrusion detection in IoT and industrial networks requires models that can detect rare attacks at low false-positive rates while remaining reliable under evolving traffic and limited labels. Existing …

1 day ago · Explore AI-based intrusion detection systems, their benefits, key methodologies, and challenges in enhancing cybersecurity with AI-driven threat detection.

Mar 3, 2025 · Through complementary integration of these methods, organizations can build robust intrusion detection frameworks that balance detection accuracy, computational efficiency, and …

Aug 1, 2023 · In today's digital world, the tremendous amount of data poses a significant challenge to cyber security. The complexity of cyber-attacks makes it diff…