# Toward Secure Smart Grid Systems: Risks, Threats, Challenges, and Future Directions
## 10 Future Research Directions
### Lightweight Cryptographic Solutions  
Data security is primarily protected by cryptographic solutions, which consist of cryptographic algorithms and protocols. Consequently, designing lightweight cryptographic  
Figure 8: Smart grid attacks and defenses at different layers. algorithms and protocols becomes vital for protecting smart grid systems, and these points are described in the following:  
10.1.1. Lightweight Cryptographic Algorithms  
These algorithms are needed to guarantee that the final entities are safely and securely connected. These adjustments will protect communicated/stored data from being intercepted, altered, or even destroyed. Therefore, to guarantee data availability, message authentication, and confidentiality/integrity, lightweight cryptographic algorithms are needed. Two possible directions are as follows:  
* Optimizing the hardware/software implementation of existing cryptographic algorithms, where a set of recent solutions follows this direction. * Algorithm optimization: Reducing the number of rounds or using simple round functions (symmetric algorithm) or operations instead of complicated ones. This approach may start with a collection of current lightweight cryptographic algorithms for IoT systems, such as [308; 309; 310]. Therefore, to ensure data confidentiality, integrity, and authenticity during communication, effective lightweight cryptographic algorithms are used to secure data exchanges while maintaining system performance by reducing computational and communication costs. Their significance lies in their ability to uphold strong security measures in settings where energy efficiency and conservation are top considerations. 10.1.2. Lightweight Cryptographic Authentication Protocols  
Defining and designing a lightweight symmetric/asymmetric authentication protocol that can effectively balance security and performance is one of the main steps in the right direction [311; 312]. To reach this goal, recent solutions use lightweight cryptographic algorithms. Let us indicate that recent authentication solutions are reinforced using other factors (you are and you know). Cybersecurity requires lightweight cryptographic authentication systems, particularly for situations with limited resources like smart grids and Internet of Things devices. 10.2. Lightweight and Robust ML/AI Solutions  
Integrating AI/ML-based grid security schemes into future directions can improve the resilience of the smart grid and ensure the reliability and security of the grid infrastructure with accuracy and efficiency by continuously adapting to evolving threats, detecting anomalies, and proactively mitigating potential attacks. Using cutting-edge machine learning algorithms to examine massive volumes of data produced by smart grid systems is necessary to include AI/ML-based grid security methods in future approaches. These algorithms make real-time detection of cyber threats or anomalous behavior possible, enabling prompt response and mitigation. Using these tactics will help smart grid systems become more resilient and dependable in the face of changing cyber threats. Edge AI for cybersecurity has become one of the main research directions and can benefit well from the federated learning approach. On the other hand, Edge AI can employ one or several techniques to construct lightweight machine learning techniques such as Pruning, Weight Sharing, Quantization, Low-rank Approximation, Sparse Regularization, and Distillation in addition to feature selection for tabular/time-series datasets. Distillation techniques are one of the main directions that should be improved to construct lightweight deep-learning models that can achieve a good balance between model performance and device/application requirements. In the following, a set of possible future research points is presented to protect AI/ML solutions for smart grids or to use AI/ML to protect smart grids. 10.2.1.