The edge and the end point are interesting po9ints within the IT portfolio. The concept of edge computing is moving assets and compute capabilities from the core of an organization to the edge. Using Machine Learning to help IoT devices react and act more intelligently. I mentioned many years ago now, the concept of a smart sensor. I only provide data when the data I’ve captured is out of my expected range. IE something changed, and therefore I am reporting that change. But the reality of endpoints is they come in two distinct flavors. Sensors and sensor arrays, and human beings.
The human element to edge and endpoint computing is critical. Why? The greatest security risk for any system is the human endpoint. The reality of hackers and hacking is that they are most dangerous when they leverage the concept of social engineering. Social Engineering is where your point of attack is the human being holding that endpoint device. Either via gathering or acquiring their password and login information. The risk of any system is always the weakest link.
That is why the concept of edge security and end security is a critical conversation. You see the problem is you can’t apply stringent security to that mobile device that is the entry point to the IT world for the human. That remote cellular device has a minimal security stack. The more security you add, the more performance you take away. That balancing act becomes a critical problem. The world of mobile device management tor MDM has exploded in the past five years. Let’s try to minimize the risk of the remote mobile device. The greater the security applied to a device, the greater the desire to get around the security (it slows everything down).
Edge and endpoint computing becomes an extremely critical component going forward for both users and IT.
More to come…