## IoT Security – 21st century solutions based on 9th century concepts

The internet of things (IoT) devices have been around for a number of years now, but very few smart sensors have any decent level of data security. For many organisations the issue of data security and secure remote updates to legacy products has become of paramount importance. Unfortunately, many of the engineers who design sensor products have little or no understanding a security algorithms, leading to systems that can be easily hacked – the fiasco of the UK smart meter system is a good example.

### Algorithms to the rescue

Algorithms and mathematics are usually regarded by many organisations as ‘academic black magic’ and are generally overlooked as a solution for a robust IoT commercial application. Nevertheless, some of you may be surprised by how old the concept of algorithms actually are in solving real world problems.

A few weeks ago, I looked through my old PhD thesis and stumbled across a reference to one of world’s first documented algorithms from the 9th century mathematician, Al-Khwarizmi (where, the word ‘algorithm’ is derived from al-Khwarizmi’s name).

Al-Khwarizmi undertook pioneering work in algebra, which was popularized in his book, “al-Mukhtasar fi Hisab al-Jabr wa l-Muqabala” and altered society’s perspective of analyzing problems, be they a simple domestic chore or a complex mathematical concept.

An excerpt from “Al-Mukhtasar fi Hisab al-Jabr wa l-Muqabala” for the solution to x^2 + 10x = 39.

Translation: For the squares and roots equal to a number, it is as saying: a square and ten of its roots is equal to thirty-nine dirhams. The solution is to halve roots, equal to five in this problem, then, multiplying the root by itself then this will be twenty-five. Then add it to thirty-nine and this will be sixty-four. Then take the square root, which will be eight and subtract from it half the root, which is five. The remainder is three and that is the root you are seeking and the square is nine.

I had forgotten (well, it was 14 years ago!) how elegant Al-Khwarizmi work actually was, and how I’m sure he would probably smile at the challenges that we’re facing today. Nevertheless, without his pioneering work, we wouldn’t have any of the IoT and security algorithms that we take for granted today.

### Solutions in the 21st century

We’ve been pleasantly surprised by the rich offering from commercial IC vendors, such as: Atmel, NXP and Analog Devices in producing secure micro-controllers for the IoT market. Many of these micro-controllers include all of the necessary hardware encryption building blocks needed for building a secure IoT sensor, and some even offer a decent amount of processor power for data analytics algorithms.

Sounds ideal, right?

The Achilles heel of all of these solutions is how engineers implement them in a system. The micro-controller itself may be ‘secure’, but what about the system architecture (i.e. the algorithmic building blocks and and how they interact with each other). And what about encryption keys? How are they stored and updated? For the UK smart meter system mentioned above, the system just used one key for the whole system – not very secure ! It is this fact that is painfully overlooked by many, and as such, which eventually leads to the system being hacked and rendered useless.

In short, hardware based encryption technology is a great step in right direction for IoT device security, but without good understanding of encryption technology as part of the system architecture the solution is doomed to failure.

## Author

• Sanjeev is an AIoT visionary and expert in signals and systems with a track record of successfully developing over 25 commercial products. He is a Distinguished Arm Ambassador and advises top international blue chip companies on their AIoT solutions and strategies for I4.0, telemedicine, smart healthcare, smart grids and smart buildings.

## 2018: The death of big data for IoT

With the advent of smart cities, and society’s obsession of ‘being connected’, data networks have been overloaded with thousands of IoT sensors sending their data to the cloud, needing massive and very expensive computing resources to crunch the data.

### Is it really a problem?

The collection of all these smaller IoT data streams (from smart sensors), has ironically resulted in a big data challenge for IT infrastructures in the cloud which need to process

massive datasets – as such there is no more room for scalability. The situation is further complicated with the fact, that a majority of sensor data is coming from remote locations, which also presents a massive security risk.

It’s estimated that the global smart sensor market will have over 50 billion smart devices in 2020. At least 80% of these IoT/IIoT smart sensors (temperature, pressure, gas, image, motion, loadcells) will use Arm’s Cortex-M technology, but have little or no smart data reduction or security implemented.

### The current state of play

The modern IoT eco system problem is three-fold:

• Endpoint security
• Data reduction
• Data quality

Namely, how do we reduce our data that we send to the cloud, ensure that the data is genuine and how do ensure that our Endpoint (i.e. the IoT sensor) hasn’t been hacked?

### The cloud is not infallible!

Traditionally, many system designers have thrown the problem over to the cloud. Data is sent from IoT sensors via a data network (Wifi, Bluetooth, LoRa etc) and is then encrypted in the cloud. Extra services in the cloud then perform data analysis in order to extract useful data.

So, what’s the problem then?

This model doesn’t take into account invalid sensor data. A simple example of this, could be glue failing on a temperature sensor, such that it’s not bonded to the motor or casing that it’s monitoring. The sensor will still give out temperature data, but it’s not valid for the application.

As for data reduction – the current model is ok for a few sensors, but when the network grows (as is the case with smart cities), the solution becomes untenable, as the cloud is overloaded with data that it needs to process.

No endpoint security, i.e. the sensor could be hacked, and the hacker could send fake data to the cloud, which will then be encrypted and passed onto the ML (machine learning) algorithm as genuine data.

### What’s the solution?

Algorithms, algorithms….. and in built security blocks.

Over the last few years, hundreds of silicon vendors have been placing security IP blocks into their silicon together with a high performance Arm Cortex-M4 core. These so called enhanced micro-controllers offer designers a low cost and efficient solution for IoT systems for the foreseeable future.

A lot can be achieved by pre-filtering sensor data, checking it and only sending what is neccessary to the cloud. However, as with so many things, knowledge of security and algorithms are paramount for success.