Aerospace and Electronic Systems Magazine February 2018 - 10

Cyber-Secure Multiuser Superposition Covert Avionics System

Figure 6.

Similarity degree versus length of watermarks.

Figure 5.

Spectrum usage comparison between NOMA and OMA, where θ is the
power allocation coefficient and β is the bandwidth allocation coefficient.

same watermarks, the data center correlates the data received from
the sensors, and the correlation result at time t can be represented
1 L
by SD t , k =  i =1 (Wi , k + Mo[ PN i , k , Qk ( Akωi , k + ρ Bt )])·Mo( PN i , k ),
L
where L refers to the length of watermarks. Similarity degree SD t , k
is calculated as an evaluation metric to measure the detection performance.
To facilitate the analysis, we use M-sequence generation program from MATLAB to generate sequences of watermark bits
with values +1 or −1. Figure 6 illustrates the relationship between
similarity degree and the length of watermark in terms of amplitude of watermarks Ak when there is no attack. It is observed that
increasing the amplitude will cause an increase of the similarity
degree. Moreover, as the length of watermark increases, the similarity degree increases sharply at first and then becomes stable.
Note that regardless of the amplitude, a similar pattern is shown
for the similarity degree. We conclude that the similarity degree
can always approach a stable value by increasing the length of watermark, regardless of the amplitude variance.
Figure 7 shows the relationship between similarity degree and
strength of attack in the avionics scenario with different lengths
of watermarks (L = 25, 100, and 200). In this case, we set the am10

Figure 7.

Similarity degree versus severity of communication attack.

plitude of the watermark as 1. From Figure 7, when the strength
of the attack is 0, which means there is no attack, the similarity
degree is 1. It indicates that the received avionics data were not
manipulated during the data transmission. To simulate the scenario that the attack is strong enough to replace the transmitted data
completely, we define the strength of the attack as 1, the similarity
degree nearly appears to be 0, which represents that the received
data were completely changed. Then, a problem arises as to why
the similarity degree is not equal to 0 when the attack strength becomes 1, because the length of watermarks is very short, more or
less a relationship between the original data and modified data may
exist. Nonetheless, the similarity degree is inversely proportional
to the attack strength. We could easily determine whether there exists a malicious attack or not and what is the attack severity in our
proposed MuSC avionics system by applying the watermark-based
data validation.

IEEE A&E SYSTEMS MAGAZINE

FEBRUARY 2018



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