"What Is the Problem Space?" Defining Host-Space Adversarial Perturbations against Network Intrusion Detection Systems

Network Intrusion Detection Systems NIDS are now increasingly leveraging Machine Learning ML techniques to detect malicious network activities. Numerous papers have scrutinized the security of ML-based NIDS ML-NIDS by testing them against various attacks involving adversarial perturbations. The...

A No-Defense Defense against Gradient-Based Adversarial Attacks on ML-NIDS: Is Less More?

Gradient-based adversarial attacks subtly manipulate inputs of Machine Learning ML models to induce incorrect predictions. This paper investigates whether careful architectural choices alone can yield an inherently robust Deep Neural Network DNN-based Network Intrusion Detection Systems NIDS,...

Enhancing Adversarial Robustness in Network Intrusion Detection: A Layer-Wise Adaptive Regularization Approach

The new wave of adversarial attacks that utilize gradient-related vulnerabilities in neural network-based classifiers makes Network Intrusion Detection Systems more open to such threats. Although state-of-the-art adversarial training methods have shown promising results in producing more robust...

SoK: Reshaping Research on Network Intrusion Detection Systems

Network Intrusion Detection Systems NIDS have been studied for decades. Hundreds of papers have, e.g., proposed ways to enhance, harden or bypass NIDS. However, the findings of prior literature are hardly reflected in real-world operational contexts. Such a disconnection is problematic for resear...

ML Defender (ARGus NDR): An Open-Source Embedded ML NIDS for Botnet and Anomalous Traffic Detection in Resource-Constrained Organizations

Ransomware and DDoS attacks disproportionately impact hospitals, schools, and small organizations that cannot afford enterprise security solutions. We present ML Defender aRGus NDR, an open-source network intrusion detection system built in C++20, deployable on commodity hardware at approximately...

CVE-2026-31931

Suricata is a network IDS, IPS and NSM engine. From version 8.0.0 to before version 8.0.4, use of the "tls.alpn" rule keyword can cause Suricata to crash with a NULL dereference. This issue has been patched in version 8.0.4...

CVE-2026-31933

Suricata is a network IDS, IPS and NSM engine. Prior to versions 7.0.15 and 8.0.4, specially crafted traffic can cause Suricata to slow down, affecting performance in IDS mode. This issue has been patched in versions 7.0.15 and 8.0.4...

CVE-2026-31932

Suricata is a network IDS, IPS and NSM engine. Prior to versions 7.0.15 and 8.0.4, inefficiency in KRB5 buffering can lead to performance degradation. This issue has been patched in versions 7.0.15 and 8.0.4...

CVE-2026-31933

Suricata is a network IDS, IPS and NSM engine. Prior to versions 7.0.15 and 8.0.4, specially crafted traffic can cause Suricata to slow down, affecting performance in IDS mode. This issue has been patched in versions 7.0.15 and 8.0.4...

EUVD-2026-18237

Suricata is a network IDS, IPS and NSM engine. From version 8.0.0 to before version 8.0.4, use of the "tls.alpn" rule keyword can cause Suricata to crash with a NULL dereference. This issue has been patched in version 8.0.4...

Suricata IDPE 8.0.4

Suricata is a network intrusion detection and prevention engine developed by the Open Information Security Foundation and its supporting vendors. The engine is multi-threaded and has native IPv6 support. It's capable of loading existing Snort rules and signatures and supports the Barnyard and...

Enhancing Network Intrusion Detection Systems: A Multi-Layer Ensemble Approach to Mitigate Adversarial Attacks

Adversarial examples can represent a serious threat to machine learning ML algorithms. If used to manipulate the behaviour of ML-based Network Intrusion Detection Systems NIDS, they can jeopardize network security. In this work, we aim to mitigate such risks by increasing the robustness of NIDS...

CVE-2026-22264

Suricata is a network IDS, IPS and NSM engine. Prior to version 8.0.3 and 7.0.14, an unsigned integer overflow can lead to a heap use-after-free condition when generating excessive amounts of alerts for a single packet. Versions 8.0.3 and 7.0.14 contain a patch. As a workaround, do not run...

CVE-2026-22260

Suricata is a network IDS, IPS and NSM engine. Starting in version 8.0.0 and prior to version 8.0.3, Suricata can crash with a stack overflow. Version 8.0.3 patches the issue. As a workaround, use default values for request-body-limit and response-body-limit...

CVE-1999-0599

A network intrusion detection system IDS does not properly handle packets with improper sequence numbers...

CVE-1999-0601

A network intrusion detection system IDS does not properly handle data within TCP handshake packets...

CVE-1999-0598

A network intrusion detection system IDS does not properly handle packets that are sent out of order, allowing an attacker to escape detection...

CVE-1999-0600

A network intrusion detection system IDS does not verify the checksum on a packet...

CVE-1999-0602

A network intrusion detection system IDS does not properly reassemble fragmented packets...

Hyperparameter Tuning-Based Optimized Performance Analysis of Machine Learning Algorithms for Network Intrusion Detection

Network Intrusion Detection Systems NIDS are essential for securing networks by identifying and mitigating unauthorized activities indicative of cyberattacks. As cyber threats grow increasingly sophisticated, NIDS must evolve to detect both emerging threats and deviations from normal behavior. Th...