IEEE - Aerospace and Electronic Systems - February 2020 - 15

O'Mahony et al.
the PHY is seen as an appropriate continuation from this article. The focus lies in the development of a detection strategy,
which can distinguish between good operating and interference intensive channels, while classifying the cause. A
machine learning approach seems applicable due to previous
work in nonlinear time series [39].

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CONCLUSION

[4] H. J. Beesterm€oller et al., "Wireless-sensor networks in

This article discussed interference and intrusions in WSNs in
terms of the four pillars of security; vulnerabilities, requirements, attacks, and defenses. An extensive overview of both
WSN security issues and WSN attacks were provided and
two main types of adversaries were defined; the outlaw, who
breaks the spectrum laws, and the noncompliant operator,
who adheres to laws but does not follow protocol rules. By
utilizing ZigBee, certain attacks were simulated, using Matlab, and it was shown that matched protocol interference was
more of a threat than conventional CW jamming and, also,
harder to detect. This implies that traditional interference
detection schemes might be inadequate, as intruder signals
can be indistinguishable from legitimate ones. A real-time
analysis of coexisting signals causing interference and DoS
expanded this point and highlighted the two main types of
adversaries. Therefore, the work in this article implies that
WSN can be vulnerable to interference and/or intrusions, but
techniques can be used to add resilience and detectability.
To conclude, this article highlighted that if WSNs are to
become integrated into modern society and to be used frequently in critical applications, like the IoT and aerospace,
enhancements to both security and the detection of intentional and unintentional intrusions is necessary. Detection
strategies need to advance and look at aspects outside the
norm, for example, received raw bits, while maintaining the
optimization of device resources. Future designs should
encapsulate security at the beginning of the design process
and incorporate an IDS and utilize all layers from the PHY
upwards. The IDS should be able to characterize the intrusion and be able to distinguish between intentional and unintentional intrusions.

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ACKNOWLEDGMENTS

networks: A survey," IEEE Commun. Surv., vol. 10, no. 3,

This work was supported in part by the Irish Research
Council (IRC) and in part by United Technologies
Research Center Ireland (UTRC-I) under the postgraduate
Enterprise Partnership Scheme 2016, award number
EPSPG/2016/66.

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FEBRUARY 2020

IEEE A&E SYSTEMS MAGAZINE

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no. 4, pp. 42-56, Oct.-Dec. 2009.

15
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