# Trustworthiness of Situational Awareness: Significance and Quantification
## 2 Related Work  
Many works in the literature have explored SA. [PERSON] [5] has presented a theoretical model for SA considering its role in human decision-making. According to the [PERSON]'s model, SA consists of three levels, where the first level pertains to the perception of elements in the current situation, the second level means the comprehension and interpretation of the current situation, and the third level refers to the projection and prediction of the future status of entities in the environment, at least in the near term. [PERSON] et al. [1] have enhanced [PERSON]'s model to incorporate AI and dynamic data-driven application systems to adapt measurements and resources in accordance with changing situations. They have also discussed the measurement of SA and the challenges associated with the quantification of SA. They have also elaborated technologies that could improve SA, ranging from different means of intelligence gathering to AI to automated vision systems. Establishing metrics to quantify the performance of SA is very crucial for SA system design. Some of the metrics for SA assessment include [1]: (i) timeliness, (ii) accuracy, (iii) trust, (iv) credibility (can be characterized by a confusion matrix of probability of detection and probability of false alarm), (v) availability, (vi) cost, (vii) attention, (viii) performance (success in completing the mission and to evaluate decisions taken), and (ix) scope (local versus global or single-intelligence (single-INT) versus multi-intelligence (multi-INT)). These metrics can be used for design as well as to assess the SA by quantitatively evaluating various aspects of the SA. An SA measurement approach should include a variety of system design concepts, including [6]: (i) display symbolism, such as 3D displays, voice control, flat panel displays, HUDs, and HMD, etc. ; (ii) electronics, avionics, and sensing concepts; (iii) information fusion concepts; (iv) automation; (v) integrity; (vi) trustworthiness; and (vii) training techniques. [PERSON] et al. [7] have discussed different SA assessment approaches, which use different types of probes to measure SA, such as freeze-probe techniques, real-time probe techniques, post-trial self-rating techniques, observer-rating techniques, performance based rating techniques, and process indices-based rating techniques. These techniques can be used in many real-world applications. SA measurement techniques that are often utilized include (i) NASA task load index (TLX) (please note that it could also be utilized to assess situational awareness in cognitive workloads) [8], (ii) SA global assessment technique (SAGAT) [6], (iii) SA rating technique (SART) [9], and (iv) critical decision method (CDM) [10]. A rigorous summary of these techniques is presented in [1], and is omitted here for brevity. SA can be measured by empirically assessing an operator's performance via quantifiable metrics, such as time and accuracy, and then by comparing these assessments to the results of similar tests without SA assistance. However, little work exists on quantifying SA [11]. Furthermore, most of the existing methods for measuring SA have various shortcomings, such as subjectivity [12], physiology [13], limitedness [11], and coverage. Different metrics have been proposed to assess the worthiness of an SA system. These metrics can be characterized into five categories or dimensions [11]: (i) confidence, (ii) accuracy/purity, (iii) timeliness, (iv) throughput, and (v) cost. Although many works have discussed SA and SA assessment techniques, the security of SA has not been explored in the literature. The most relevant work related to the security of SA is [3], where the authors discussed the security and trust issues in SA, and contemplated various passive and active adversarial attacks on SA systems. The authors further presented different approaches for mitigating adversarial attacks on SA, such as robustness against transduction attacks, symmetric and asymmetric cryptography, hardware-based security, and AI security.