  The SCADA system is the foundation of the large-scale industrial control
system. It is widely used in industries of petrochemistry, electric power,
pipeline, etc. The natural gas SCADA system is among the critical
infrastructure systems that have security issues related to trusted
communications in transactions at the control system layer, and lack
quantitative risk assessment and mitigation models. However, to guarantee the
security of the Oil and Gas Transmission SCADA systems (OGTSS), there should be
a holistic security system that considers the nature of these SCADA systems. In
this paper, we augment our Security Awareness Framework with two new
contributions, (i) a Data Quantization and State Compression Approach (DQSCA)
that improves the classification accuracy, speeds up the detection algorithm,
and reduces the computational resource consumption. DQSCA reduces the size of
processed data while preserving original key events and patterns within the
datasets. (ii) A quantitative risk assessment model that carries out regular
system information security evaluation and assessment on the SCADA system using
a deductive process. Our experiments denote that DQSCA has a low negative
impact on the reduction of the detection accuracy (2.45% and 4.45%) while it
reduces the detection time much (27.74% and 42.06%) for the Turnipseed and Gao
datasets respectively. Furthermore, the mean absolute percentage error (MAPE)
rate for the proposed risk assessment model is lower than the intrusion
response system (Suricata) for the DOS, Response Injection, and Command
Injection attacks by 59.80%, 73.72%, and 66.96% respectively.
