ELECTRONICS
Sunday, April 05, 2020
IoT (Internet of Things): Our Future
Life with IoT:
In just one year alone, we went from having 5 million IoT devices
connected to the internet to billions.
The future is happening now, and these devices are getting smarter every day through machine learning and artificial intelligence. IoT devices are becoming a part of the conventional electronics culture and people are adopting smart devices into their homes faster than ever. It is estimated that there will be up to 21 billion connected devices to the internet. IoT devices will be a huge part of how we interact with everyday objects. There is big money in the IoT space currently, and it will only continue to grow as technology improves. The more data that IoT devices collect, the smarter they will become. Cities will transform into Smart Cities through the use of IoT connected devices. Think of Smart Traffic Lights that collect data on traffic, and use that data to synchronized lights to peak traffic times.
Overall, this improves cities overall efficiency and saves the government money since everything can be remotely managed. Smart homes, thermostats, lighting systems and coffee makers will all collect data on your habits and patterns of usage. All this data will be collected to help facilitate Machine Learning.
The future is happening now, and these devices are getting smarter every day through machine learning and artificial intelligence. IoT devices are becoming a part of the conventional electronics culture and people are adopting smart devices into their homes faster than ever. It is estimated that there will be up to 21 billion connected devices to the internet. IoT devices will be a huge part of how we interact with everyday objects. There is big money in the IoT space currently, and it will only continue to grow as technology improves. The more data that IoT devices collect, the smarter they will become. Cities will transform into Smart Cities through the use of IoT connected devices. Think of Smart Traffic Lights that collect data on traffic, and use that data to synchronized lights to peak traffic times.
Overall, this improves cities overall efficiency and saves the government money since everything can be remotely managed. Smart homes, thermostats, lighting systems and coffee makers will all collect data on your habits and patterns of usage. All this data will be collected to help facilitate Machine Learning.
How do we security to these devices?
With the billions of IoT devices connected to the open internet,
how do we ensure these devices are secure?
Encryption
Scheme: AES vs. TLS/SSL
Encryption can solve a complicated problem. When people think
about encryption, many will turn to TLS/SSL, however, these protocols don’t cut
it for encryption and processing. The reason these protocols aren’t optimal is
they are point-to-point solutions and not end-to-end solutions. When data has
to go through many different points on the chain, we are going to have to
account for different security protocols and devices. This requires a security
solution like AES (Advanced
Encryption Standard) since it provides end-to-end
security, and encrypts the message all the way through. Only devices with the
encryption keys can decrypt the encrypted data as it’s sent and received.
AES also allows you to wrap the message body with AES and leave
all the actionable data in TLS. Actionable data, for instance, would be
temperature information that you are trying to read. In addition, we need to
prevent all inbound ports from being open at all costs since this can leave
your IoT devices open to vulnerabilities and DDOS attacks. Devices should only make
outbound connections, so that way the door is closed to accessing applications
and services behind those open ports. The connection outward can be left open
so the device can listen in with a secure tunnel back from the network.
Rather
than trying to fit all of the IoT Protocols on top of existing architecture
models like OSI Model, we
have divided the protocols into the following layers to provide some level of
organization:
- Infrastructure (ex:
6LowPAN, IPv4/IPv6, RPL)
- Identification (ex:
EPC, uCode, IPv6, URIs)
- Comms /
Transport (ex: Wifi, Bluetooth, LPWAN)
- Discovery (ex:
Physical Web, mDNS, DNS-SD)
- Data Protocols (ex:
MQTT, CoAP, AMQP, Websocket, Node)
- Device
Management (ex: TR-069, OMA-DM)
- Semantic (ex:
JSON-LD, Web Thing Model)
- Multi-layer
Frameworks (ex: Alljoyn, IoTivity, Weave,
Homekit)
Conclude: Machine learning and IoT together can do a miracle in today's
modern technology, if both of them are used with good understanding.
AUTHOR:
