Blockchain Security SBDM System
A Security-Based Decision Making System to Detect and Mitigate Blockchain Attacks
This prototype demonstrates machine learning-based detection of common blockchain attacks and implements proactive defensive measures.
View DashboardReal-time Protection
Continuously monitors blockchain transactions to detect anomalies and suspicious patterns.
AI-Powered Detection
Uses machine learning algorithms including Random Forest and Isolation Forest to identify attack patterns.
Automated Response
Implements proactive defensive measures to mitigate attacks once they are detected.
Priority Attack Vectors
Advanced Threats
These advanced attack vectors represent the primary focus of our research and pose the most significant security threats to blockchain networks.
BlackBird 51% Attack
An attacker gains control of more than 50% of network hash power, allowing them to manipulate consensus and potentially rewrite transaction history.
BBEDSA
Black Bird Embedded Double-Spending Attack combines elements of 51% attacks with strategic transaction manipulation across multiple blocks.
DoC Attack
Denial of Chain attacks flood the network with spam transactions, causing congestion and preventing legitimate transactions from being processed.
Additional Attack Vectors
Timejacking
Manipulates a node's time perception to affect block validation.
Sybil Attack
Creates multiple identities to gain influence in the network.
Eclipse Attack
Isolates a node from the network, manipulating their blockchain view.
Finney Attack
Double-spending using pre-mined blocks to reverse transactions.
How It Works
The SBDM System
The Sentinel Blockchain Defense Model (SBDM) operates through a multi-layered approach:
- Blockchain Monitoring: Continuously tracks transaction patterns, node behavior, and consensus parameters.
- Anomaly Detection: Uses machine learning to identify deviations from normal blockchain operation.
- Attack Classification: Categorizes potential threats based on their characteristics and severity.
- Response Mechanism: Implements appropriate countermeasures to mitigate detected attacks.