Table 45 Vulnerabilities and Mitigation strategies in blockchain-based reporting.
From: A hybrid deep learning model for detection and mitigation of DDoS attacks in VANETs
Vulnerability | Risk Level (1–10) | Impact Severity (1–10) | Mitigation Strategy | Effectiveness (%) | Resource Overhead (%) | Notes |
|---|---|---|---|---|---|---|
Sybil attack | 8 | 9 | Delegate node reputation & identity verification | 85 | 12 | Limits fake identities via voting |
Excessive resource consumption | 7 | 8 | Adaptive consensus mechanism & pruning | 80 | 15 | Reduces energy & storage costs |
51% attack | 6 | 10 | Distributed delegate selection & multi-layer consensus | 90 | 18 | Prevents single group takeover |
Transaction flooding (DoS) | 7 | 7 | Rate limiting & transaction fees | 75 | 10 | Controls spam transactions |
Data Privacy Leakage | 5 | 6 | Encryption & permissioned access | 70 | 8 | Protects sensitive vehicular data |
Smart contract vulnerabilities | 6 | 8 | Formal verification & runtime monitoring | 80 | 10 | Prevents exploit of automated logi |
