TDE – Consensus for Truth
The use of Consensus
Continuing from last week’s post we know want to explore further how consensus algorithms can be used to achieve truth for trust.
A mathematics-based mechanism would need to be highly resilient to unwanted changes. One way to accomplish that is through the use of consensus. To create consensus, it requires an agreement amongst a number of agents or processors for a single data value. The consensus protocol must be resilient or fault-tolerant to counteract unreliable or failing processors or agents. The process must be able to compare the candidate values, communicate it between nodes, and get an agreement on a single consensus value. For this, it must have three requirements fulfilled A consensus protocol tolerating / halting failure must satisfy the following properties:
- Integrity – If all the correct processes proposed the same value, then any correct process must decide.
- Termination – Eventually, every correct process decides some value.
- Agreement – Every correct process must agree on the same value.
Security for trust
The consensus can create a form of resilience against potential harm from single-point failures, for whatever reason. Increased number of agents/processes or nodes increases resilience against unwanted change. Resilience against potential harm and/or other unwanted change caused by external actors/factors is what we refer to as security.
Any institution, individual, group or object can be beneficiaries of security from unwanted change. Looking at the etymological origin of security, it derives from the Latin word securus, meaning freedom from anxiety: se (without) and cura (care/anxiety).1 This definition is essential due to the previously identified risk arising from uncertainty, the fundamental issue for digital (untrusted) data exchange.
Security most often refers to protection from hostile influences. The form of security needed for TDE is the resilience against harm or damage, laying a secure foundation. For digital TDE we refer to a system with the purpose to provide cybersecurity. A cybersecurity tool that embeds data integrity, creating resilience against unwanted change of data going unnoticed. The financial industry can be drastically hampered by lack of portable or any data integrity establishing trust. If data gets changed here millions of dollars may be lost.
In particular, IoT and AI applications need a trust mechanism based on mathematical truth. This is because machines are the acting parties which operate on a mathematical basis. If machines are being fed data which cannot be trusted, subsequent decisions and processes can be compromised. Results may be devastating.