The Enterprise Security Meta Model

When talking about security, people often don't quite understand the big picture. They often jump into the details and specifics without necessarily understanding or have a clear view of what overall context drives the need for their specific solutions. So often, it turns into a spaghetti that can of-course be served on the table, but no one know - Who asked for it, Why we are serving this, To whom beside how it comes together as a whole to make a perfect sense out of it. Neither anyone knows if it tastes good !

Here is a meta model as how things look like from a bird eye view perspective and should help you better connect the dots next time to make some sense of the security mess such as  - Cyber security, Infra Security, Applications Security, Data Security, AI Security and so forth. 

A more detailed view was shared earlier here. 

And remember...

Further Readings:

How to Organize Your Cybersecurity Program

HTH...

A Tech Artist 🎨

AI/GenAI, Enthusiasm and the Missing Bits - The Expert Beginners

Amidst the AI/GenAI revolution, a new breed of "gurus" has emerged, often with inflated claims and limited practical experience. While genuine expertise is essential, it's crucial to distinguish between true AI practitioners and those who simply capitalize on the hype. It's important to critically evaluate the claims and contributions of such individuals, as superficial understanding can lead to misguided implementations and missed opportunities. 

Often during my conversations these days with the IT people and leaders from different markets within the Asia-Pacific, everyone is learning AI, since not being able to spell that out correctly means you are legacy.

On the flip side, interestingly enough, less than 1% people actually understand what AI really is and perhaps 0.1% are able to talk and follow through with the details around:

• AI Strategy
• AI project life cycle 
• AI infrastructure 
• AI Algorithms 
• AI Governance
• AI Ethics

While over simplification is good way to communicate effectively with the non-technical audience, but then we are talking about IT folks and industry. Just getting familiar with the lingo likely give the false sense of mastery. 

There seems to be significant gaps in terms of how IT industry folks are getting trained on these topics (outside the old traditional DS community people).

If people tells you that they understand what GenAI is and how it works, but haven't heard of "Semantic Model, Ontology & Knowledge Graphs", very unlikely they know anything beyond the lingo.

Further Readings:

Expert Beginners

HTH...

A Tech Artist 🎨