# Anomaly Detection in Blockchain Networks Using Unsupervised Learning: A Survey
## 8 Challenges and Future Directions
### Implications of Zero-Trust and Zero-Knowledge Proof Environments  
The implications of zero-trust architecture (ZTA) and zero-knowledge proof (ZKP) environment on types of attacks are significant. Since these environments require continuous authentication and verification, traditional attack vectors such as unauthorized access, privilege escalation, and data breaches become more challenging to execute successfully. Attackers must overcome multiple layers of verification, making it more difficult to infiltrate systems or tamper with data [196].  
However, despite the enhanced security provided by those environments, new types of attacks may emerge. Attackers may focus on exploiting vulnerabilities in the authentication and verification mechanisms themselves, attempting to bypass or compromise them. For example, they might target weaknesses in the implementation of ZKP's protocols or attempt to deceive the ZTA infrastructure into granting unauthorized access [197].  
Anomaly detection approaches in such environments may need to adapt also in order to account for the unique characteristics of ZTA and ZKP. Traditional anomaly detection methods rely on identifying patterns of normal behavior and flagging deviations from these patterns as anomalies. In ZTA environments, where every interaction is treated with skepticism, normal behavior may vary significantly from user to user and over time [197]. Anomaly detection algorithms would need to be more dynamic and context-aware, continuously adjusting their understanding of normal behavior based on real-time observations.  
Furthermore, anomaly detection approaches in ZTA and ZKP may need to incorporate additional layers of verification and validation. For example, anomaly detection algorithms could leverage ZKP techniques to verify the authenticity of transactions or user interactions without revealing sensitive information. By combining anomaly detection with ZKPs, organizations can enhance their ability to detect and respond to suspicious activities while preserving privacy and security. It is worth noting that zero-knowledge attacks pose a significant challenge to authentication systems, particularly in decentralized peer-to-peer (P2P) environments. Traditional public key infrastructure models rely on centralized trust servers, such as certification authorities (CAs), to validate the binding of user public keys and identities. However, in decentralized P2P networks, the CA-based models become impractical. Instead, anonymous systems in P2P environments adopt self-signed certificates to authenticate peers, providing anonymity but leaving them vulnerable to man-in-the-middle attacks. In these attacks, an attacker can intercept and impersonate transaction participants without detection due to the lack of knowledge about communication channels. However, a promising approach to mitigating such types of attacks is the pseudo trust mechanism, which embeds the knowledge of the communication path in exchanged messages [197]. By verifying the validity of combined messages, transaction participants can detect impersonation attempts, offering enhanced security.