The Data Privacy Asia 2016 Conference will feature top ranked industry experts from more than 15 countries and a more interactive audience experience than ever before. The Conference, which is themed Building Digital Trust: Establishing an Ecosystem of Trust and Protection in the Digital Age will examine subjects like trust vs. innovation and privacy vs. security, how enterprises can meet the challenges of a globally diverse regulatory and compliance landscape, and the privacy challenges on IT and security.
The European Commission has released its proposal for a comprehensive framework of cybersecurity requirements for products with digital elements in the EU – the EU Cyber Resilience Act. This is an important step towards a more robust harmonized set of cybersecurity rules.
In just a few years, Anthropic transformed from a safety-focused AI startup into one of the most consequential companies in cybersecurity. But, aside from systems generally considered secure today, what does this mean for systems that have routinely proven to be insecure? This is where Microsoft comes into play.
With collection of personal data getting harder under legislations like GDPR and CCPA, ensuring adequate data protection will be the driving factor of success for organizations of the future.
There are clear benefits for taking extra steps to demonstrate your company's commitment to data privacy by using measures like data privacy scores, external audits and reviews, and empowering consumers to make their own choices for their own data.
Many companies may now be afraid of data monetization because of concerns over potential privacy violations. There is also a growing concern over being legally compliant but still making customers unhappy or uncomfortable. Is differential privacy the answer?
SaaS applications are not going anywhere, and we must face the fact that they have access to our company’s most sensitive data. With SaaS, the shadow IT challenge has expanded and deepened even further.
Upgrading to the “latest and greatest” technology isn’t always feasible for businesses, given the cost and disruption involved in constantly changing processes and switching solutions. So how can today’s organizations better understand when it makes sense to upgrade—and when it doesn’t?
When leveraged for machine learning applications, Privacy Enhancing Technologies (PETs) manifest as Preserving Machine Learning (PPML) to ensure that privacy is both protected and prioritized when building and utilizing models.
The question of data privacy has become one that is shaping the business world of the 21st century. With many technologies advancing in leaps and bounds – as well as the increasing importance of ‘The Internet of Things’ the appointment of a professional Data Protection Officer to ensure legal and mandatory compliance has become a business imperative. We look at how failure to appoint such professionals who can operate at all levels of an organisation can be a costly mistake – not only in terms of revenue – but also in terms of customer trust.










