Table of Contents
- 1. Project description
- 2. what is it ?
- 3. Why is it vital to our business ?
- 4. How do we keep the system secure?
Project description
Distributed systems rely on coordination mechanisms (e.g., consensus, replication) to provide a logically centralised service. However, these mechanisms introduce attack surfaces such as routing attacks, Sybil attacks, and Eclipse attacks. In particular, Eclipse attacks isolate a node by surrounding it with malicious peers, thereby compromising availability, integrity, and confidentiality. This project work analyses Eclipse attacks on a blockchain network (e.g., Bitcoin or Ethereum) and designs a set of countermeasures based on the principles outlined in the Distributed Systems Security Knowledge Area.
what is it ?
A Distributed System is a composition of geo-dispersed computing and communication resources that function collectively to provide the illusion of a single, logically centralized service. By leveraging replication and orchestration, these systems ensure high availability, fault tolerance, and low-latency access for users regardless of their physical location.
Architecturally, a distributed system is defined by four core functional elements:
- Data Flows: Managed via admission and access control.
- Data Transport: The mechanisms for moving data across the network.
- Coordination Services: The schema used to synchronize resources.
- Data Management: Ensuring consistency, ordering, and consensus (e.g., virtualization or time-based ordering).
Classification Professional models generally categorize these systems by their coordination schema:
- Decentralized (Peer-to-Peer): Systems without central coordination (e.g., Gnutella, Blockchain) where entities interact primarily with "neighbors."
- Coordinated Clustering: Systems that use communication processes to realize virtual centralized control, including Client-Server models, Cloud Computing (Azure/AWS), and Distributed Databases.
Why it's Important to Our Business
Securing our distributed infrastructure is not merely a technical requirement but a strategic necessity. The complexity of dispersed resources introduces specific risks that directly impact our bottom line:
- Operational Resilience & SLAs: Failures in Resource Management (such as synchronization or consensus errors) do not just slow down operations — they can crash entire services. Ensuring coordination stability is critical to maintaining high availability and meeting our Service Level Agreements (SLAs).
- Trust, Privacy, and Compliance: Our Data Security framework maps directly to regulatory mandates like GDPR. Protecting against confidentiality breaches and side-channel attacks is essential to avoiding legal liabilities and preserving the trust of our clients and partners.
- Financial & Transactional Integrity: In distributed environments, maintaining Data Consistency is vital. Errors in transactional logic or "split-brain" scenarios can lead to financial discrepancies, double-spending, or corrupted records, posing a direct threat to our fiscal reliability.
- Strategic Security Evolution: Recognizing that threats exist at the Data Transportation and middleware levels allows us to move beyond legacy defenses. By investing in Zero-Trust architectures and robust mutual authentication, we secure our modern cloud-based operations against sophisticated active attacks like Man-in-the-Middle (MITM).
How Do We Keep the System Secure?
Securing a distributed environment requires a multi-layered approach that addresses identity, data integrity, and network resilience. Based on industry standards (CyBOK), we implement the following four pillars of defense:
1. Identity & Access Governance
To maintain a "benign peer population," we must control who enters the network and how they are identified.
- Secure Admission Control: Utilizing a centralized authority or a Certificate Authority (CA) to handle peer enrollment.
- Cryptographic Identity: Assigning network IDs via public-key cryptography to prevent malicious entities from self-selecting their identifiers (a key defense against Sybil attacks).
2. Structural & Routing Resilience
In distributed systems, the "path" to data is a primary attack vector. We secure this by:
- Disjoint Path Routing: Implementing multiple, non-overlapping routing paths for each lookup. This ensures that even if one path is compromised (e.g., an Eclipse attack), the system still reaches the correct destination.
- Divergent Lookups: Using search techniques that avoid proximity-based bottlenecks where attackers typically cluster false information.
3. Data & Storage Integrity
We prevent unauthorized or "illicit" data modifications — often referred to as "cheating" in distributed logic — through:
- Secure Storage Protocols: Encrypting data at rest and using cryptographic hashes to verify that data has not been altered during its lifecycle.
- State Monitoring: Deploying "network crawlers" or monitors to track the health of the system and identify malicious nodes in real-time.
4. Coordination & Consensus Protection
For systems that rely on "Coordinated Clustering" (like Cloud or Transactional Databases), we protect the Middleware:
- Orchestration Security: Securing the schedulers and resource managers that provide the "illusion" of a centralized system.
- Consistency Enforcement: Applying strict ordering (causality) and precedence rules to distributed transactions to prevent state corruption.