About this Research Topic

Manuscript Submission Deadline 12 September 2022

Communication networks are currently facing several challenges at the same time. The end of resource overprovisioning in optical fibers, brought by the exponential growth of Internet traffic is leading to more efficient, but also more complex, schemes for spectrum management. The emerging need to support 5G and 6G systems will necessitate the provision of ultra-reliable, low-latency communication to critical services, including in the operation of critical urban infrastructures. It will also give new impetus to the growth of the Internet of Things (IoT) and its security vulnerabilities. More often than not, solutions to these challenges lead to more flexible operation of the network, but more flexibility is a meaningful bonus only in-so-far as more intelligence and awareness is imparted to the system operation. Softwarization is a first step in this direction. The next step is machine-learning, duly matched with human knowledge as needed for agility and context.

Emerging scenarios for communication networks are fraught with prospective opportunities and risks. A major prospect of risk is that the next-generation networks may not be secure enough to support the upcoming opportunities. Hence the focus of this Research Topic is on the multifaceted approaches to the network security issue. In this context, the traditional emphasis on network survivability is subsumed by the more comprehensive notion of network robustness, which is related to the resilience, or ability to keep as much critical service as possible under attack, considering the many critical and non-critical missions which may be under the network responsibility during an emergency. These concerns should affect all stages of the network conception and evolution, encompassing regular planning, design, management and operation, as well as the prospective analysis of possible attacks from unintended and malicious sources and the design of appropriate responses and inbuilt preparedness schemes for launching them with the needed agility.

Even if the network is designed and built for maximal resilience, malicious attackers and eavesdroppers will still look for remaining vulnerabilities. For this reason, security is bound to become an integral part of the network operation, entrusted with the task of looking for new vulnerabilities, both in the network itself and its surrounding physical, social and cyber spaces. Taking all these environments into account will probably exceed the context-awareness capabilities of machines for some time yet, highlighting the importance of machine learning as a strategic tool for human operators to keep the network prepared for all possible emergencies.

In the pursuit of the announced objectives, this Research Topic will welcome papers discussing all aspects of the Optical Network security issue and its impact on networking to support 5G and the resulting growth of IoT and its critical applications including, but not limited to, the following topics:

- Spectral resource-aware Optical Network survivability
- Squeezed Protection and Restoration in Optical Networking
- Differentiated Levels of Protection for Connections and Slices
- Optical network resilience and robustness
- Metrics for Differentiated Protection Services in Optical Networks
- Security in the Physical Layer of Optical Networks
- Emergency Backup Networks in Optical Networking
- Organizational Issues in Network Security
- Software Fault Tolerance, including Byzantine failures.
- Cryptography in the Physical Layer with Coherent Detection
- Game-theoretical aspects of Network Security

Conflict of Interest statement: Philip Ji is employed by NEC Laboratories America Inc (Princeton, United States) and Yabin Ye is employed by Huawei Technologies Duesseldorf GmbH (Munich, Germany). No other Topic Editors have a Conflict of Interest to declare.

Keywords: Optical communication, optical networking, network security, 5G, 6G, network slicing, flexible networks, traffic awareness, machine learning, machine-type communication, ultra-reliable low latency communication


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Communication networks are currently facing several challenges at the same time. The end of resource overprovisioning in optical fibers, brought by the exponential growth of Internet traffic is leading to more efficient, but also more complex, schemes for spectrum management. The emerging need to support 5G and 6G systems will necessitate the provision of ultra-reliable, low-latency communication to critical services, including in the operation of critical urban infrastructures. It will also give new impetus to the growth of the Internet of Things (IoT) and its security vulnerabilities. More often than not, solutions to these challenges lead to more flexible operation of the network, but more flexibility is a meaningful bonus only in-so-far as more intelligence and awareness is imparted to the system operation. Softwarization is a first step in this direction. The next step is machine-learning, duly matched with human knowledge as needed for agility and context.

Emerging scenarios for communication networks are fraught with prospective opportunities and risks. A major prospect of risk is that the next-generation networks may not be secure enough to support the upcoming opportunities. Hence the focus of this Research Topic is on the multifaceted approaches to the network security issue. In this context, the traditional emphasis on network survivability is subsumed by the more comprehensive notion of network robustness, which is related to the resilience, or ability to keep as much critical service as possible under attack, considering the many critical and non-critical missions which may be under the network responsibility during an emergency. These concerns should affect all stages of the network conception and evolution, encompassing regular planning, design, management and operation, as well as the prospective analysis of possible attacks from unintended and malicious sources and the design of appropriate responses and inbuilt preparedness schemes for launching them with the needed agility.

Even if the network is designed and built for maximal resilience, malicious attackers and eavesdroppers will still look for remaining vulnerabilities. For this reason, security is bound to become an integral part of the network operation, entrusted with the task of looking for new vulnerabilities, both in the network itself and its surrounding physical, social and cyber spaces. Taking all these environments into account will probably exceed the context-awareness capabilities of machines for some time yet, highlighting the importance of machine learning as a strategic tool for human operators to keep the network prepared for all possible emergencies.

In the pursuit of the announced objectives, this Research Topic will welcome papers discussing all aspects of the Optical Network security issue and its impact on networking to support 5G and the resulting growth of IoT and its critical applications including, but not limited to, the following topics:

- Spectral resource-aware Optical Network survivability
- Squeezed Protection and Restoration in Optical Networking
- Differentiated Levels of Protection for Connections and Slices
- Optical network resilience and robustness
- Metrics for Differentiated Protection Services in Optical Networks
- Security in the Physical Layer of Optical Networks
- Emergency Backup Networks in Optical Networking
- Organizational Issues in Network Security
- Software Fault Tolerance, including Byzantine failures.
- Cryptography in the Physical Layer with Coherent Detection
- Game-theoretical aspects of Network Security

Conflict of Interest statement: Philip Ji is employed by NEC Laboratories America Inc (Princeton, United States) and Yabin Ye is employed by Huawei Technologies Duesseldorf GmbH (Munich, Germany). No other Topic Editors have a Conflict of Interest to declare.

Keywords: Optical communication, optical networking, network security, 5G, 6G, network slicing, flexible networks, traffic awareness, machine learning, machine-type communication, ultra-reliable low latency communication


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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