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Advances in Electrical and Electronic Engineering

Network Physical Layer Attack in the Very High Capacity Networks

David Grenar, Jakub Frolka, Karel Slavíček, Otto Dostál, Martin Kyselák

Published May 14, 2023• 8 citations
Publisher

Abstract

This paper focuses on the analysis of fiber optic line eavesdropping options based on cheap and easy-to-use equipment - for example, the commonly used fiber optic splitters with suitable optical power division ratios. The fiber optic splitter takes a small portion of the optical power sufficient for the eavesdropper to read the data and lets as much signal power as possible pass in the original direction. We attempted to detect the presence of fiber optic splitter-based eavesdropping points on the communication line by using common techniques designated for fiber optic quality measurement and fault detection. The results are summarised in this paper.

DOI
10.15598/aeee.v21i1.4973

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This paper focuses on the analysis of fiber optic line eavesdropping options based on cheap and easy-to-use equipment - for example, the commonly used fiber optic splitters with suitable optical power division ratios. The fiber optic splitter takes a small portion of the optical power sufficient for the eavesdropper to read the data and lets as much signal power as possible pass in the original direction. We attempted to detect the presence of fiber optic splitter-based eavesdropping points on the communication line by using common techniques designated for fiber optic quality measurement and fault detection. The results are summarised in this paper.
The physical layer of an optical network is vulnerable to a variety of attacks, including jamming, physical infrastructure attacks, eavesdropping, and interception. As the demand for network capacity grows dramatically, the issue of securing the physical layer of optical network cannot be overlooked. In this survey paper, we discuss the security threats in an optical network as well as present several existing optical techniques to improve the security. In the first part of this paper, we discuss various types of security threats that could appear in the optical layer of an optical network, including jamming, physical infrastructure attacks, eavesdropping, and interception. Intensive research has focused on improving optical network security, in the above specific areas. Real-time processing of the optical signal is essential in order to integrate security functionality at the physical layer while not undermining the true value of optical communications, which is its speed. Optical layer security benefits from the unique properties of optical processing-instantaneous response, broadband operation, electromagnetic immunity, compactness, and low latency. In the second part of this paper, various defenses against the security threats outlined in this paper are discussed, including optical encryption, optical code-division multiple access (CDMA) confidentiality, self-healing survivable optical rings, anti-jamming, and optical steganography.
Optical communication networks transport an enormous aggregate client traffic, a good part of which is highly sensitive. As such, the optical signal in the fiber medium becomes attractive to bad actors in an attempt to tap the fiber or a component on the path in order to eavesdrop, source mimic, or attack to cause service denial. Therefore, it is important that the network has built-in security features to monitor the channel integrity and to also detect if and when unauthorized intervention has taken place. It is also important that the network is intelligent to countermeasure bad actors. Because the integrity of optical channels in are also affected by component degradation, photon-matter interactions and other non-linear phenomena, the network should be able to differentiate between malicious interventions and parametric degradations. In this paper we identify observable performance parameters and predictors, we describe a estimating method for in-line parameter monitoring, we conclusively distinguish between component degradations and intervention of a malicious eavesdropper and we describe countermeasure mechanisms.
Much work to date has been done in the identification of physical layer optical network attacks. Our own work has indicated additional attacks against data integrity through various forms of optical coupling. In this paper, we present an analysis of coupling attacks on a fiber optic link. In addition we demonstrate on such form of a coupling attack using standard hardware and allowing injection of additional data onto the fiber. This method introduces minimal power losses that are well below most physical layer intrusion detection sensor thresholds.
Optical communication networks transport an enormous aggregate client traffic, a good part of which is highly sensitive. As such, the optical signal in the fiber medium becomes attractive to bad actors in an attempt to tap the fiber or a component on the path in order to eavesdrop, source mimic, or attack to cause service denial. Therefore, it is important that the network has built-in security features to monitor the channel integrity and to also detect if and when unauthorized intervention has taken place. It is also important that the network is intelligent to countermeasure bad actors. Because the integrity of optical channels in are also affected by component degradation, photon-matter interactions and other non-linear phenomena, the network should be able to differentiate between malicious interventions and parametric degradations. In this paper we identify observable performance parameters and predictors, we describe a estimating method for in-line parameter monitoring, we conclusively distinguish between component degradations and intervention of a malicious eavesdropper and we describe countermeasure mechanisms.
Optical fiber communications are essential for all types of long and short distance transmissions. The aim of the article is to analyze the previously presented risks and evaluation of the two biggest and therefore the most critical risks. The first major risk is the possibility of inserting a splitter into optical distribution network and capturing portion of the entire spectrum, ie all channels in the optical fiber. The second significant security risk is crosstalk on multiplexer in networks with wavelength division multiplexing. Based on the measurements, risks were evaluated for both point-to-point and point-to-multipoint networks.
Security in optical communications has been recently a concern due primarily of the vast amount and the sensitivity of information that a single fiber carries. It is generally accepted that data security is encrypted by the end-user and that the optical network is not easy to tap as it was with wired networks. However, the sophistication of eavesdroppers has increased and if an optical link is accessed, then the encryption code of data can be broken with the use of supercomputers. In addition to data eavesdropping, eavesdroppers may access the link for malicious attacks, or for transmitting erroneous data by mimicking a source. Therefore, it is important that the receiver has the means and intelligence to recognize the signature of the source and the optical channel so that when the link is tapped, the receiver recognizes it and it alerts the network management or it triggers a data rerouting process. In fact, an optical channel, including source, fiber and optical components, has its own optical parameters that constitute a signature. These parameters are the result of linear and non-linear phenomena that affect the quality characteristics of the optical signal and which can not be mimicked. Therefore, the understanding of optical parameters that define the optical channel signature is very critical. In this paper we provide an analysis of the factors affecting the signal quality and thus they constitute the signature of the optical channel, we model the optical channel and demonstrate via simulations that small parametric variation affect the signature of the channel. As a result, monitoring the signal parameters leads to source and channel authentication whereas detecting the parametric variability of channel deducts channel degradation or tapping.