Synthetic Data drives Cyber Security
The information security industry is on high alert due to threats that keep evolving. As technology advances, cybercriminals continue to come up with sophisticated means of launching their attacks. For that reason, individuals and businesses need to be vigilant regarding safeguarding their data. But big data has created a buzz in the industry as companies discover how valuable it is. Data mining has made it possible for companies to understand their customers better, develop new products and services, and much more to improve their productivity and revenue.
The increase in the development of data mining technology has only increased security concerns. Data mining is being considered a serious threat to the privacy of individuals’ sensitive information. While data mining remains to be a valuable technology to businesses in different sectors, a solution regarding the security of data had to be found. This is where synthetic data generation comes in.
Synthetic data versus anonymous data versus raw data
The initial data mining techniques focused on raw data, which created a considerable risk to privacy. Then came anonymized data which tended to either go too far to obscand the usefulness out of the data, or it maintained utility and risked re-identification. On the other hand, a synthetic data generator dramatically reduces the ability to re-identify. Machine learning algorithms learn from the data insights and then create useful, yet completely synthetic data that follows the overall user patterns and behaviors…
Synthetic data opens access to the benefits of data
Regulated industries have been locked out from exploring the full benefits of data mining. And as usual, the reason behind the limitations are cybersecurity threats. To access privacy-sensitive data for artificial intelligence, such institutions have to wait for months before getting their hands on whatever information they need. This has held back businesses in terms of identifying opportunities in the market.
Privacy restrictions had been limiting, especially at a time where cybercrime is on the rise. Many large corporates have had their data locked in fear of breaching. This has held back a lot of valuable information that can be used to change the industry. The emergence of synthetic data mining has encouraged the cooperation of different institutions. The transfer of information between researchers, small businesses, big corporations, among other agencies, has been made seamless.
Today’s synthetic data allows businesses to simulate data and get real trends without interfering with the privacy and security of their customers. Artificial data generation has opened previously shut doors for many enterprises in light of leveraging big data, third-party strategic partnerships and the cloud.
Finally, businesses are able to make data-driven decisions without the fear of compromising the security of data. Since it is completely artificial, synthetic data limits privacy risks. Synthetic data can easily be shared, monetized, and used without the usual compliance restrictions.