Security and integrity of transmission model

AT_ES_15
Evaluate cases of man-in- the-middle attacks and data sniffing that could compromise driver privacy and/or corrupt model training.
Features regarding driver identity and cognitive/health state are transmitted to cloud server for model training, nefarious stealing and parsing of such data could endanger driver’s privacy.
Evaluation Scenario Requirements
V&V Methods
VALU3S Framework
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