Fast encryption and decryption-oriented car networking key management method based on reinforcement learning
A technology of intensive learning and key management, which is applied in the field of key management of the Internet of Vehicles for fast encryption and decryption, can solve the problems of roadside units that are not completely trusted facilities, reduce authentication overhead, etc., and achieve improved anti-eavesdropping interception rate, Effects of preventing data leakage and eavesdropping attacks
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[0023] The technical solutions of the present invention will be further described below in conjunction with the examples.
[0024] Embodiments of the present invention include the following steps:
[0025] Step 1: Establish a vehicle networking network, including one roadside unit, vehicle i, the current number n of vehicles is 20, and one active bug. The vehicle uses the AES encryption algorithm to encrypt communication information. There are three optional key lengths, namely l∈{128,192,256}, and the power of the active eavesdropper p∈[0,5]mW, which is quantized to 11 levels, namely p∈[0, 0.5,...,5].
[0026] Initialization parameters: the number of roadside unit states G is 100, the number of behaviors H is 80, learning factor α=0.5, discount factor γ=0.5, learning rate δ 1 = 0.1 and δ 2 =0.05, key length coefficient a=0.8, received interference power coefficient b=0.5, security level coefficient c 1 =0.7, risk level coefficient c 2 =0.4, the key update delay coefficie...
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