Privacy and Data Sovereignty
In a time where our personal devices are constantly connected to the internet we have basically lost the sovereignty over our data. Corporations and many governments are grabbing every bit of information about us they can get hold of. Usually that information is used to sell us products, but it can be used to manipulate us. Often, we are not the customer anymore, we have become the product. We simply don’t know any more which applications are transferring what data to whom and have little means to control it.
Without any doubt, a technology like graph languages creates a whole new set of privacy and security concerns, maybe far more serious ones than we already have with conventional technology. If and how these can be under control depends largely on the design and implementation of the language itself and of the supporting tools. Havel and all supporting tools are designed with privacy and security as a top priority. Multiple levels of encryption and data access security are built into the systems.
On the other hand, a language like Havel, paired with well-designed supporting tools is also an opportunity to fix existing problems.
For example, assuming that users will store their private data in secured universal repositories, data will not be “lying around” scattered throughout the file system, readable by every process that runs on the machine. It is behind lockable doors, allowing the owner to fine tune who has what access to his or her data. Data access control is seamlessly integrated into the language and can be arbitrarily configured for any expression.
Encryption is omnipresent in Havel. Any expression or part of an expression, even single values, can be encrypted. Users can choose themselves precisely what information are encrypted in what way. Because encryption is seamlessly integrated into the language it becomes more natural to use. Havel supports advanced encryption key management enabling every information to be as secure as it needs to be. The breach of one single key does not have to compromise all information available on a system.
Samarai brains have a centralized communications module. All information coming in and going out the network has to go through that module; it acts as a kind of guard or firewall. This is not just a simple firewall that blocks sources, destinations and protocols. That guard can actually understand to a certain degree what kind of information is being shared and therefore block access depending on content.
Havel is used for all communication in a semantic social network and the transmitted data is therefore human-readable. Users have the chance to know what information is communicated (or at least be suspicious if the data is not human readable). System owners can setup very precisely what communication is allowed and the guard will automatically block suspicious events. Furthermore, every single communication using Havel is asynchronous and prepared for long delays, it is always expected that a user interaction is needed to authorize an information to leave the private space.
Overall, Samarai makes communication a bit more humane, reflecting our real-life needs and giving users much better control over who can access what information.
This post is part of a comprehensive introduction into SRDM, graph languages and Havel.
Continue reading: Information Trustworthiness
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