Explainable artificial intelligence for cybersecurity: a literature survey
With the extensive application of deep learning (DL) algorithms in recent years, eg, for
detecting Android malware or vulnerable source code, artificial intelligence (AI) and …
detecting Android malware or vulnerable source code, artificial intelligence (AI) and …
Dark-TRACER: Early Detection Framework for Malware Activity Based on Anomalous Spatiotemporal Patterns
As cyberattacks become increasingly prevalent globally, there is a need to identify trends in
these cyberattacks and take suitable countermeasures quickly. The darknet, an unused IP …
these cyberattacks and take suitable countermeasures quickly. The darknet, an unused IP …
Automated detection of malware activities using nonnegative matrix factorization
Malware is increasingly diversified and sophisti-cated. It is essential to rapidly and
accurately detect malware activities when malware infection spreads. However, accurately …
accurately detect malware activities when malware infection spreads. However, accurately …
Generating labeled training datasets towards unified network intrusion detection systems
It is crucial to implement innovative artificial intelligence (AI)-powered network intrusion
detection systems (NIDSes) to protect enterprise networks from cyberattacks, which have …
detection systems (NIDSes) to protect enterprise networks from cyberattacks, which have …
Scalable and fast algorithm for constructing phylogenetic trees with application to IoT malware clustering
With the development of IoT devices, there is a rapid increase in new types of IoT malware
and variants, causing social problems. The malware's phylogenetic tree has been used in …
and variants, causing social problems. The malware's phylogenetic tree has been used in …
Internet-wide scanner fingerprint identifier based on TCP/IP header
A Tanaka, C Han, T Takahashi… - 2021 Sixth International …, 2021 - ieeexplore.ieee.org
Identifying individual scan activities is a crucial and challenging activity for mitigating
emerging cyber threats or gaining insights into security scans. Sophisticated adversaries …
emerging cyber threats or gaining insights into security scans. Sophisticated adversaries …
Malicious packet classification based on neural network using kitsune features
Abstract Network Intrusion Detection Systems (NIDSes) play an important role in security
operations to detect and defend against cyberattacks. As artificial intelligence (AI)-powered …
operations to detect and defend against cyberattacks. As artificial intelligence (AI)-powered …
Which packet did they catch? Associating NIDS alerts with their communication sessions
Virtually every enterprise network has deployed intrusion detection systems (NIDSes) for
security threats detection, prevention, and response. To defend against cyberattacks with …
security threats detection, prevention, and response. To defend against cyberattacks with …
Scalable and fast hierarchical clustering of IoT malware using active data selection
The number of IoT malware specimens has in-creased rapidly and diversified in recent
years. To efficiently analyze a large number of malware specimens, we aim to reduce the …
years. To efficiently analyze a large number of malware specimens, we aim to reduce the …
Consolidating Packet-Level Features for Effective Network Intrusion Detection: A Novel Session-Level Approach
Network Intrusion Detection Systems (NIDSs) are crucial tools for ensuring cyber security.
Recently, machine learning-based NIDSs have gained popularity due to their ability to adapt …
Recently, machine learning-based NIDSs have gained popularity due to their ability to adapt …