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Data privacy examples

IBM Big Data Hub

These are just some examples of how organizations support data privacy , the principle that people should have control of their personal data, including who can see it, who can collect it, and how it can be used. For example, they can decline to have their data shared with third parties while allowing the app to generate personalized offers.

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Network Security Architecture: Best Practices & Tools

eSecurity Planet

Perimeter security tools include: Firewalls: Filter traffic and monitor access based upon firewall rules and policies for the network, network segment, or assets protected by different types of firewalls. Cloud Security Cloud security provides focused security tools and techniques to protect cloud resources. behind the proxy.

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How generative AI delivers value to insurance companies and their customers

IBM Big Data Hub

Insurers struggle to manage profitability while trying to grow their businesses and retain clients. Large, well-established insurance companies have a reputation of being very conservative in their decision making, and they have been slow to adopt new technologies.

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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. However, these systems lack genuine understanding and can’t adapt to situations outside their training. Regardless, these are examples of narrow AI.

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What Is Encryption? Definition, How it Works, & Examples

eSecurity Planet

Encryption Tools and IT Security Fundamental protocols incorporate encryption to automatically protect data and include internet protocol security (IPSec), Kerberos, Secure Shell (SSH), and the transmission control protocol (TCP). More complex commercial tools provide a variety of encryption solutions or even end-to-end encryption.

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Top 8 Cyber Insurance Companies for 2022

eSecurity Planet

That’s where cyber insurance may be able to help. For that reason, most experts now recognize that a complete cybersecurity strategy not only includes technological solutions aimed at preventing, detecting, and mitigating attacks, it should also include cyber insurance to help manage the associated financial risks. That’s a 29.1%

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The risks and limitations of AI in insurance

IBM Big Data Hub

In my previous post , I described the different capabilities of both discriminative and generative AI, and sketched a world of opportunities where AI changes the way that insurers and insured would interact. One example of this is facial recognition being used for the illegal tracking of people’s movement.