Design of a Temporary Optical Coupler Using Fiber Bending for Traffic Monitoring

Uematsu, Toshio; Hirota, Hidenobu; Kawano, Takeshi; Kiyokura, Takanori; Manabe, Tetsuya

doi:10.1109/jphot.2017.2762662

Cited by 14 publications

(11 citation statements)

References 7 publications

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“…Precision (P ) is defined in (2) and measures the sensitivity of an ML model to false positives. Recall (R) measures the sensitivity of a model to false negatives, as defined in (3). The f 1 score balances the importance of precision and recall into a single metric, which is equal to 1 when the model is perfectly accurate in detecting attacks, and smaller otherwise.…”

Section: Network-wide Attack Detection and Identification Approamentioning

confidence: 99%

“…More sophisticated methods include insertion of harmful, jamming signals (in-band or out-ofband) upon tampering with the patch-panels or breaching the fiber, e.g. by abusing a well-known monitoring technique for creating temporary passive couplers by bending the fiber [3]. Damage from such attacks depends on the power and spectral properties of the jamming signal as well as the underlying optical network design.…”

Section: Introductionmentioning

confidence: 99%

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Machine Learning for Optical Network Security Monitoring: A Practical Perspective

Furdek

Natalino

Lipp³

et al. 2020

J. Lightwave Technol.

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In order to accomplish cost-efficient management of complex optical communication networks, operators are seeking automation of network diagnosis and management by means of Machine Learning (ML). To support these objectives, new functions are needed to enable cognitive, autonomous management of optical network security. This paper focuses on the challenges related to the performance of ML-based approaches for detection and localization of optical-layer attacks, and to their integration with standard Network Management Systems (NMSs). We propose a framework for cognitive security diagnostics that comprises an attack detection module with Supervised Learning (SL), Semi-Supervised Learning (SSL) and Unsupervised Learning (UL) approaches, and an attack localization module that deduces the location of a harmful connection and/or a breached link. The influence of false positives and false negatives is addressed by a newly proposed Window-based Attack Detection (WAD) approach. We provide practical implementation guidelines for the integration of the framework into the NMS and evaluate its performance in an experimental network testbed subjected to attacks, resulting with the largest optical-layer security experimental dataset reported to date.

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Section: Network-wide Attack Detection and Identification Approamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Machine Learning for Optical Network Security Monitoring: A Practical Perspective

Furdek

Natalino

Lipp³

et al. 2020

J. Lightwave Technol.

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show abstract

“…We use convex and concave clamps to bend a fiber with the correct bending radius R and angle θ. We designed the bending condition to achieve high injection and extraction efficiencies and a low fiber failure probability [9]. We set the maximum bending loss at 2.0 dB at a wavelength of 1550 nm not to interrupt service.…”

Section: Temporary Optical Couplermentioning

confidence: 99%

“…This approach allows us to install the optical coupler without service interruption if the TOC has a sufficiently low bending loss to maintain the transmission system. We designed the bending condition of the TOC to realize a TOC with a low bending loss [9]. However, the injection and extraction efficiencies decreased along with the decrease in the bending loss of the TOC.…”

Section: Introductionmentioning

confidence: 99%

Temporary Optical Coupler for Optical Cable Re-Routing Without Service Interruption

et al. 2018

Self Cite

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We design a temporary optical coupler to obtain high injection and extraction efficiencies while keeping the bending loss low with the aim of realizing optical cable rerouting without service interruption. The temporary optical coupler injects/extracts signal lights into/from a fiber by using fiber bending. The extraction efficiency is improved by using a double-clad fiber or a graded-index fiber for light injection and extraction while the injection efficiency is maintained compared with that of a conventional temporary optical coupler that uses a single-mode fiber. This improvement enables us to realize an optical cable re-routing operation support system that requires no service interruption.

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“…One of the most harmful attack methods identified in the literature is power jamming. It is performed by inserting a harmful signal of excessive power into the fiber (e.g., by bending it [2]), which reduces the amount of gain allocated to co-propagating optical channels and aggravates the physical-layer impairments in the fiber. The damaging effects of this attack technique are not necessarily confined to the primarily intruded link but may propagate through the network.…”

Section: Introductionmentioning

confidence: 99%

Network-Wide Localization of Optical-Layer Attacks

Furdek

Chan

Natalino

et al. 2020

Optical Network Design and Modeling

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Optical networks are vulnerable to a range of attacks targeting service disruption at the physical layer, such as the insertion of harmful signals that can propagate through the network and affect co-propagating channels. Detection of such attacks and localization of their source, a prerequisite for secure network operation, is a challenging task due to the limitations in optical performance monitoring, as well as the scalability and cost issues. In this paper, we propose an approach for localizing the source of a jamming attack by modeling the worst-case scope of each connection as a potential carrier of a harmful signal. We define binary words called attack syndromes to model the health of each connection at the receiver which, when unique, unambiguously identify the harmful connection. To ensure attack syndrome uniqueness, we propose an optimization approach to design attack monitoring trails such that their number and length is minimal. This allows us to use the optical network as a sensor for physical-layer attacks. Numerical simulation results indicate that our approach obtains network-wide attack source localization at only 5.8% average resource overhead for the attack monitoring trails.Index Terms-optical network security, physical-layer attack detection, attack monitoring trails.

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Design of a Temporary Optical Coupler Using Fiber Bending for Traffic Monitoring

Cited by 14 publications

References 7 publications

Machine Learning for Optical Network Security Monitoring: A Practical Perspective

Machine Learning for Optical Network Security Monitoring: A Practical Perspective

Temporary Optical Coupler for Optical Cable Re-Routing Without Service Interruption

Network-Wide Localization of Optical-Layer Attacks

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