Abstract:

Aiming at the problems of being incomplete,subjective and difficult to quantify loss in privacy disclosure risk assessment of intelligent connected vehicles,a privacy risk assessment model combining qualitative and quantitative methods is proposed.First,based on the qualitative risk assessment model,a new privacy classification is proposed,which extends the privacy impact rating of the existing standard.Second,a privacy leakage detection scheme based on Wi-Fi is designed to solve the problem of data collection in quantitative evaluation.Finally,the comprehensive value measurement of the leaked privacy data is carried out from the information entropy,influence level,personal identifiable information type and other factors.The privacy data pricing model is introduced to quantify the attack benefits,and the product of attack benefits and probability is taken as the estimated loss value.The feasibility of the privacy leakage detection scheme is proved through the real car experiment on three intelligent connected cars.The qualitative and quantitative risk assessment of privacy data shows that the extended impact rating,privacy measurement and pricing model are superior to those of the existing scheme,and that the scheme effectively quantifies the privacy disclosure risk of intelligent connected vehicles.The risk value of quantitative conversion is in good agreement with that of the risk value of qualitative assessment.

Key words: intelligent connected vehicles, Wi-Fi, privacy disclosure, risk assessment, ISO standards