Enterprise Data Privacy

Accelerated Risk:

The advent of COVID-19 has accelerated the need for digital transformation and market-driven digitization. This has created an opportunity for the beginning of new Privacy Technology era. This advent also presented new opportunities to hacker communities and state sponsored actors resulting in record setting data breaches and cyber-attacks on companies, government, and individuals.

These sophisticated and collaborated attacks by hackers and state actors have been carried out with state-of-the-art technologies. Consequently, there are significantly higher risks to data breaches and financial losses for enterprises and governments all around the globe.

Data Safeguard was formed to provide Data Privacy solutions for global enterprises and government organizations around the world by redacting (ID-REDACT®) and masking (ID-MASK®) sensitive and personal data using AI/ML technology. Data Safeguard is quickly becoming the first line of defence for sensitive and personal data, while meeting global Data Privacy compliance policies including but not limited to GDPR, NIST, CCPA and other global data privacy laws in countries around the world.

Evolving Challenge:

Data Privacy and stopping the unwanted proliferation of sensitive and personal data is a complex and ever evolving problem. The dynamics of data privacy will continue to shift with business and product demand, public sentiment, global and country-based data privacy compliance requirements that are ever changing to meet the influx of unstructured, semi-structured and structured data into the enterprise.

The highlights of privacy laws can be summarized as follows:

1. easier access to users owns data.
2. a right to data portability for easier transfer of personal data between service providers.
3. a clarified "right to be forgotten".
4. the right to know when a user's data has been hacked.
5. one-stop-shop with one single supervisory authority.
6. Consistency of rules (to a certain extent) by companies based outside globally.

Global Rules and Regulations:

For global Data Privacy regulations, the difficulty of identity and privacy identification is accomplished by the concept of any data defining a "natural person". By using "natural person," the privacy regulations are saying data about companies, which are sometimes considered "legal persons," are not personal data. This puts the obligation on the enterprise to be context aware and protect personal information from proliferating. A final caveat is that this individual must be alive. Data related to the deceased are not considered personal data in most cases.

Consumers and their elected representatives are seeking some level of sensitive and personal data privacy and discretion. Consumers do not want passwords, family finances, details of personal relationships, medical history, location, purchase history, and private discussions being exposed and used for unintentional purposes. The results are made public. consumers various forms of pervasive spam, phishing, unsolicited sales calls, blackmail, and ransom. Privacy does not necessarily have to be about hiding something. Rather, privacy is about limiting the provided sensitive and personal data to the explicit and intended use only.

At the same time, we realize that too little privacy can undermine commerce, liberty, and the reporting of victimizations. It also empowers powerful entities to manipulate people's digital world to coerce, manipulate, and victimize them. Too much privacy can allow criminal actors to thrive and hide from authorities. It can spawn artificial identities, used to steal, and undermine, what Data Safeguard labels as Frankenstein Identities.

Conclusion:

The global perspective on sensitive and personal data is that it should only be kept in a form which permits identification of data subjects for as long as is necessary for the purposes for which the personal data are processed.

Data Privacy should be processed in a manner that ensures appropriate security and confidentiality of the sensitive and personal data, including protection against unauthorized or unlawful access to or use of personal data and the equipment used for the processing and against accidental loss, destruction, using appropriate technical or organizational measures.

Enterprises are responsible for, and must be able to demonstrate, their compliance with all the above-named principles of Data Privacy. Enterprises must take responsibility for their processing of sensitive and personal data and how they comply with the privacy laws and regulations, like GDPR, and be able to demonstrate (through appropriate records and measures) their compliance.

Data Safeguard understands the current and future trend of Data Privacy requirements. "We believe the best solution is for the enterprise to control data proliferation across unstructured, semi-structured and structured data within the ecosystem" said Mr. Lowen, Chief Privacy Officer at Data Safeguard Inc. "I am excited about our Data Privacy suite of products that control the proliferation of data in the enterprise environment". Our products (ID-REDACT® and ID-MASK®) are built using our core AI/ML based Cognitive Computing Engine^TM, to prevent sensitive and personal data from inadvertently spreading and being used in unintended ways. This is accomplished by redacting or masking the personal identifiable data at the origin. In addition, the Cognitive Computing Engine^TM, an AI/ML based tool safeguards personally identifiable information (PII) at source and tracks the lineage across the environment.