It’s clear that the introduction of generative AI to the mainstream is tipping the scales towards a war of algorithms against algorithms, machines fighting machines. For cyber security, the time to introduce AI into the toolkits of defenders is now.
While we wait for the social media companies to become fully transparent and show us that they’re taking all their users' privacy and security seriously, it’s up to the brands and marketers to be the change makers. Soon data privacy will be the issue for brands, just like sustainability and diversity.
A growing number of organizations are beginning to recognize the potential that AI has to dramatically improve the process of cybersecurity training by improving efficiency in areas like content development, analytics, and enhanced accessibility.
The implementation of CPRA and introduction of civil penalties for theft of login information should encourage businesses to establish a strong data security posture management (DSPM) strategy. This is a key first step to protect and monitor personal information more effectively and allow consumers to control data sharing.
AI-based information risk assessment is allowing companies to mitigate potential security risks and even predict future attacks with greater speed and accuracy than they could ever achieve through manual processes.
Consumers want to be targeted with ads tailored to their needs and desires but are also more aware of their own privacy and the misuse of personal data. Businesses need to understand how to balance personalization and privacy by implementing strategies that allow for secure multi-party analytics.
Zero trust has firmly inserted itself into modern cybersecurity strategies but the perceived value of zero trust can vary widely, Organizations need to strike a balance between uninformed action and over-preparation when launching their zero trust strategy.
46% of cybersecurity professionals in a recent survey said their stress level has increased in the past 12 months, and an almost identical percentage – in the same study – indicated they’ve considered quitting the industry because of the stress level.
Siloed technologies with different management and configuration dashboards cobbled together create security gaps and visibility blind spots that slow cyber response, mitigation and recovery.
The focus is now turning to the cybersecurity implications of ChatGPT and other AI/machine learning (ML) platforms especially after the recent OpenAI security incident. What are some of the key security considerations that organizations need to consider before they explore how to utilize new AI/ML solutions?
