Non-technological barriers: the last frontier towards AI-powered intelligent optical networks
FN Khan - Nature Communications, 2024 - nature.com
Abstract Machine learning (ML) has been remarkably successful in transforming numerous
scientific and technological fields in recent years including computer vision, natural …
scientific and technological fields in recent years including computer vision, natural …
[HTML][HTML] Leveraging ai for network threat detection—a conceptual overview
Network forensics is commonly used to identify and analyse evidence of any illegal or
unauthorised activity in a given network. The collected information can be used for …
unauthorised activity in a given network. The collected information can be used for …
Optical network security management: requirements, architecture, and efficient machine learning models for detection of evolving threats
As the communication infrastructure that sustains critical societal services, optical networks
need to function in a secure and agile way. Thus, cognitive and automated security …
need to function in a secure and agile way. Thus, cognitive and automated security …
Anomaly prediction with hybrid supervised/unsupervised deep learning for elastic optical networks: a multi-index correlative approach
With the emergence of new services, the complex optical network environment makes it
more difficult to predict network anomalies. This paper proposes a multi-index anomaly …
more difficult to predict network anomalies. This paper proposes a multi-index anomaly …
Confidentiality-preserving machine learning algorithms for soft-failure detection in optical communication networks
Automated fault management is at the forefront of next-generation optical communication
networks. The increase in complexity of modern networks has triggered the need for …
networks. The increase in complexity of modern networks has triggered the need for …
Teraflow: Secured autonomic traffic management for a tera of sdn flows
TeraFlow proposes a new type of secure, cloud-native Software Defined Networking (SDN)
controller that will radically advance the state-of-the-art in beyond 5G networks by …
controller that will radically advance the state-of-the-art in beyond 5G networks by …
An artificial intelligence model based on multi-step feature engineering and deep attention network for optical network performance monitoring
Optical network performance monitoring technology, which can effectively identify physical
impairment in the network, is of great significance to ensure network stability and prevent …
impairment in the network, is of great significance to ensure network stability and prevent …
Supervised and semi-supervised learning for failure identification in microwave networks
Automated failure-cause identification in communication networks allows operators to
reduce service unavailability. Once the most likely failure root-cause is identified …
reduce service unavailability. Once the most likely failure root-cause is identified …
Flexible and scalable ML-based diagnosis module for optical networks: a security use case
To support the pervasive digital evolution, optical network infrastructures must be able to
quickly and effectively adapt to changes arising from traffic dynamicity or external factors …
quickly and effectively adapt to changes arising from traffic dynamicity or external factors …
BDDTPA: Blockchain-driven deep traffic pattern analysis for enhanced security in cognitive radio ad-hoc networks
Cognitive Radio Ad-hoc Networks (CRAHNs) combines characteristics of ad-hoc networks
with cognitive radios to facilitate a variety of communication scenarios. However, these …
with cognitive radios to facilitate a variety of communication scenarios. However, these …