IEEE Consumer Electronics Magazine - January/February 2024 - 87

TABLE 1. Comparisons of security requirements and authentication features.
Li et al.15
Authentication Phase
Method
Dynamic
One
Crypto
Deng et al.16
One
Crypto
Badhib et al.17
Two
Crypto
Our Scheme
Two
Crypto, AI
√√
Mutual Authentication √√
Forward Security
√√ √
Resistance to Replay Attack √√ √
Resistance to Man-in-the-Middle Attack √√ √
Data Confidentiality and Integrity √√ √
√
√
√
√
adversary in the middle to register with the
role that already exists in the SAGIN. Besides,
the secret keys of any entities in the system
cannot be obtained. As a result, the adversary
cannot modify or manipulate transmitting
messages to invade the existing
connection. Therefore, the scheme would
not be exposed to man-in-the-middle attacks.
Data Confidentiality and Integrity: Data confidentiality
and integrity imply that a message
receiver can ensure the message has
not been tampered with during transmission.
In our proposed scheme, the private information
is encrypted with the public key of the
target entity. An adversary cannot decrypt
the information without the corresponding
private key. Therefore, our proposed scheme
achieves data integrity property.
Moreover, we also compare our proposed
ATMAS with its counterparts against security
requirements and authentication features in
Table 1. From this table, the work in Li
et al.15,16,17 adopts crypto-based authentication
schemes, in which the schemes15,16 have no
authentication at the user device side. The work
in Badhib et al.17 and our scheme use a twophase
authentication method, but the second
phase17 is still crypto-based, which is less robust
than ours.
CASE STUDY AND PERFORMANCE
EVALUATIONS
In this section, we first provide the factors/
features used in our analysis. Then, a
January/February 2024
TABLE 2. Descriptions of factors in the ATMAS.
Items
Factors
Factor 1
Factor 2
Factor 3
Factor 4
Factor 5
Factor 6
Factor 7
Factor 8
Traffic Volume
Service Type
Uplink Rate
Sinuosity of the MU
Index of the BS
Distance between the BS and the MU
Position of the MU
Heading azimuth of the MU
Factor 9 Elevation between the BS and the Satellite
comparison of the performance of classic AIbased
algorithms using selected factors is presented.
Lastly, we discuss the effect of factor
selection strategy on authentication accuracy.
In our case study, we consider three kinds of
services: conversational, streaming, and interactive.
We assume that the BSs in the SAGIN are
fixed and uniformly distributed, and the coverage
range of a BS is 20 km. The satellites in the
SAGIN orbit at a height of 20,000 km and have a
maximum beam scanning range of11:64.
Table 2 provides the factors used in our proposed
ATMAS, including identities, trajectory,
and communication attributes.
We compare the authentication accuracy of
different AI-based algorithms with respect to the
percentage of illegal access. The authentication
accuracy is defined as ACC ¼ðTP þTNÞ=ðTP þ
87
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