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Every organisation is data-driven. Sources of data are expanding rapidly, as are volumes. Digital transformation takes this even further, enabling organisations to make use of innovative technologies. Collaboration is a must for many organisations in the extended enterprise, requiring that data flows among partners.
But data must be trusted. An example is the growing and already widespread use of AI among businesses and by consumers, which can be a force for good. But it can also can reduce trust. AI can generate false information, especially if the data being input cannot be verified as trustworthy. Sometimes this is fake headlines. Another example is deep fakes, which can be used to generate synthetic content in an attempt to fool people into thinking they are real content that can be trusted.
This can have deep security implications for organisations. For example, a video of a CEO could be faked to show the executive giving bad news regarding the organisation’s revenue expectations, causing its share price to drop.
The use of AI has further implications for organisations as it is an additional attack surface regarding data. According to OWASP, data science uses an AI pipeline that is typically outside of the regular application development scope. It requires the collection, storage and preparation of data and therefore requires appropriate security to protect data against problems such as supply chain attacks and data poisoning, whereby attackers attempt to change data in order to sabotage the model being used to make decisions in favour of the attacker. It states that protection of data and quality assurance of data are effective countermeasures.
Data provenance is essential for ensuring trust
Part of data protection is to determine its provenance, which requires that all data exchanges are tracked, with changes made tied to the person responsible. Data provenance ensures data integrity and authenticity. It allows data to flow freely, with all partners assured that the data is correct and has not been tampered with.
RKVST is a vendor that offers an API-based platform that enables data provenance in order to verify the authenticity of any digital content, from websites to supply chain attacks, which are fast growing and rapidly evolving.
The platform uses cryptography to protect data and leverages blockchain distributed technology which provides immutability, meaning that nothing can be deleted or modified. This ensures that all partners in a supply chain can collaborate securely in the knowledge that data is trustworthy. Trust in data is further strengthened by the use of secure identity verification that ensures that parties involved in transactions and collaboration are who they claim to be to further enhance trust in all entities and data involved. Data authenticity is also ensured by the audit trails that the immutable ledger provides, better enabling organisations to ensure that their regulatory obligations are being met.
The platform is available as a SaaS-based cloud service that enables organisations to get value from data in a fast and efficient manner. The service can be scaled rapidly to meet the needs of any organisation and its partners, shielding all parties from damaging supply chain attacks. There is also a freemium version, so potential customers can try before they buy.