Saudi Arabia and the United Arab Emirates (UAE) have experienced some of the world’s biggest cyber attacks in recent months, prompting them to launch major digitalisation initiatives in a bid to protect their critical sectors, particularly their oil and gas operations.
One billion devices come online every day and this makes it imperative that businesses and government organisations, including those in the Middle East, expedite the adoption of artificial intelligence (AI) and machine-learning-capable systems.
As Maciej Kranz, vice-president for corporate strategic innovation group at US-based Cisco Systems, said: “There are not enough people to manage [the] data we are creating today.”
In the Middle East, the growing trend to develop smart cities in line with governments’ long-term economic and sustainability objectives, whether in Riyadh or Dubai, is facilitating widespread digital transformation initiatives.
This comprises enabling devices – ranging from CCTV, water metres and traffic lights to air conditioning units and turbomachinery – to generate, transmit and receive data.
In addition to smartphones and tablets that generate data and images every day, these devices, which were previously linked via a closed Ethernet-based local area network (LAN), are now being linked to an edge cloud – IP-based LANs located at branches or offsite locations.
The downside is this trend increases the attack potential for criminals, who view every new online device as a potential target.
According to the latest global figures, there are 20 billion cyber attacks every day.
Middle East countries, particularly Saudi Arabia and the UAE, receive a significant share of these attacks. Last year’s successful attacks on IT servers in the Middle East belonging to oil and gas services contractors Saipem and Petrofac are evidence of this.
Machine-learning technology
Technology giants such as GE and Siemens – which have heavily entrenched machinery across the utility, oil & gas, water and transport sectors – were among the first companies to embrace the internet of things.
This is expected given this equipment underpins critical infrastructure, essential to the functioning of economies and governments, and so any extended disruption could have dire consequences.
To combat this threat, networking and security technology providers such as Cisco are working with their industrial technology counterparts. They are spending billions of dollars on research every year to help customers minimise the chance of a successful cyber attack. These companies are now turning to machine-learning-capable technologies to help detect malicious activities as early as possible. A recent breakthrough involves the capability to detect malware without decrypting packets being transmitted through networks.
“Machine-learning technology now allows us to make an inference on what we can understand but cannot see … with a very high level of accuracy,” says TK Keanini, Cisco’s product line chief technology officer for analytics.
This implies that machine learning can potentially help users to lower the overall cost of threat detection and, by association, the overall financial impact of cyber attacks, which, in 2017, are estimated to have resulted in damage worth $500,000 or more in 53 per cent of cases.
Defence against attack
Mr Keanini, however, acknowledges the same technologies used to help defend networks are also available to adversaries and hackers, who are getting better at using automated systems to orchestrate attacks.
These realities highlight the need for the Middle East to quickly improve its cybersecurity defences by building local capacity and expertise.
The recent agreement between Saudi Aramco, arguably the top cyber attack target in the region, and US-based security contractor Raytheon to establish a joint-venture company to develop, market and provide cyber-security services “in Saudi Arabia and beyond” is an example of one such initiative.
MEED
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