To ensure that the patient information being generated, stored and exchanged is secure, healthcare organizations are rapidly implementing mobile device management (MDM solutions) to push extensive security policies and tailor the usage of their diverse types of devices to ensure that the data stored on them is secured efficiently.
As the war in Ukraine intensifies and the risk of cyber-attacks from Russia grows, protecting intellectual property is both a national security issue, and also an economic one.
Security is one of the greatest concerns for organizations in the airline industry when adopting cloud-based technologies in their digital transformation.
Without a pragmatic approach to ICS security, businesses could face serious consequences and shutdown of production when vulnerabilities are exploited by threat actors.
The annual ENISA threat landscape report is one of the most helpful tools for keeping a finger on the pulse of current trends in cyber threats. This year's report highlights the dramatic rise in denial of service and cryptojacking attacks.
The whole world seems to be slowly shifting since the rise of artificial intelligence applications. AI is finding its way into every corner of the world, and the journalism industry is quickly hopping on board.
Data privacy and technology are still missing political attention despite the petabytes of personal information collected by organizations every day and the rapid change in information technology.
The stakes of cybersecurity threats on a power plant are far higher than a bank account. What do the energy businesses need to know in order to keep their networks safe?
The shift to cloud-based collaboration platforms, the amount of sensitive data that is now stored and communicated on those platforms, and the level of trust that people put into communication on those platforms have an inevitable conclusion: we are going to see more attacks on those platforms.
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.










