## 9 Discussion
### Future Research Directions
[195] emphasized the importance of securing the integral vehicular technologies of emotionally intelligent autonomous vehicles (EIAVs), including sensing, positioning, and vision systems. As these systems serve as the foundation on which EIAVs operate and interact with their environment, they become prime targets for potential cyber attacks. Consequently, the development of system-specific security methodologies that provide a comprehensive defense is a crucial area for future research. This would entail analyzing the unique security requirements of each component, determining its inherent vulnerabilities, and customizing defensive strategies that are not only reactive but also anticipatory of potential cyber-attack patterns. In addition, these security methodologies would need to be adaptable and scalable to incorporate new technologies and standards, given the accelerated rate of technological advancement. Therefore, future research must incorporate the multifaceted task of designing, validating, and deploying comprehensive security methodologies that can protect these vital vehicular technologies from potential cyber attacks. The findings of [PERSON] et al. [24] underscore the critical need to comprehend potential attack vectors aimed at autonomous vehicle software and hardware. Due to the intricacy and interconnectedness of these systems, they offer cyber attackers numerous access points of entry. A thorough comprehension of these threats requires a detailed mapping of these potential attack vectors, as well as the identification of their patterns and implications. This would then inform the design of mitigation strategies that effectively mitigate these vulnerabilities. In addition, this comprehension must encompass the consequences of effective cyber attacks, ranging from immediate operational disruptions to long-term effects on user confidence and regulatory compliance. Future research should therefore employ a twofold strategy: constructing a detailed threat landscape particular to autonomous vehicle software and hardware and developing holistic countermeasures that can neutralize threats while ensuring optimal performance. This essential research direction would considerably contribute to the fortification of EIAV systems, thereby facilitating their secure incorporation into our social fabric. The highly sensitive emotional data involved in EIAVs pose a complex challenge that deserves particular attention. Identifying and implementing optimal strategies to protect these data from potential cyber threats will be crucial. This protective layer may encompass encryption techniques, privacy-preserving computation, and anonymization methods designed exclusively for emotional data. Lastly, considering the novel nature of EIAVs, the development of regulatory frameworks that effectively address their unique cyber security needs without impeding their technological advancement is critical. This endeavor will require a cooperative approach involving researchers, industry stakeholders, and policymakers. Moreover, some additional and potential research directions are presented below:  
1. **TinyML in autonomous vehicles for cyber security enhancement and predictive defense:** TinyML appears as a crucial tool in the world of autonomous vehicles (AVs), as first presented in [196], that has the potential to radically alter the structure of the security apparatus. Autonomous cars are often outfitted with a variety of sensors and communication modules, both of which are constantly producing new data. Processing these data centrally or in the cloud might be resource-intensive and, more importantly, offer a broader attack surface to prospective cyber enemies. The application and capabilities of TinyML may be considered in this aspect. TinyML allows for the localized processing of data by applying lightweight machine learning algorithms directly inside the embedded systems of the vehicle [196].