How Can Artificial Intelligence Add Value to Cyber Security?

Posted on : 28-07-2018 | By : richard.gale | In : Uncategorized

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Cyber security is major concern for all organisations. A recent EY survey found that Cyber Security is the top risk for financial services. The cyber threat is ever growing and constantly changing. It is becoming increasingly difficult to put the right controls and procedures in place to detect potential attacks and guard against them. It is now imperative that we make use of advanced tools and technologies to get ahead of the game.

A major weapon in the race against the cyber attacker are Artificial Intelligence (AI) powered tools which can be used to prevent, detect and remediate potential threats.

Threat detection is a labour intensive arduous task and AI can help considerably with the workload which is often like looking for a needle in a haystack.

AI machines are intended to work and react like human beings. They can be trained to process substantial amounts of data and identify trends and patterns. A major cyber security issue has been the lack of skilled individuals with organisations unable to find staff with the necessary skills. AI and machine learning tools would help overcome these gaps.

Despite what you’ve seen in the movies, robotic machines are not about to take over the world!  Human intelligence is unique characteristic which a robot does not have (not yet anyway). Cybersecurity isn’t about man or machine but man and machine. A successful cyber strategy means machine intelligence and human analysts working together.

The machines perform the heavy lifting (data aggregation, pattern recognition, etc.) and provide a manageable number of actionable insights. The human analysts make decisions on how to act. Computers, after all, are extremely good at specific things, such as automating simple tasks and solving complex equations, but they have no passion, creativity, or intuition. Skilled humans, meanwhile, can display all these traits, but can be outperformed by even the most basic of computers when it comes to raw calculating power.

Data has posed perhaps the single greatest challenge in cybersecurity over the past decade. For a human, or even a large team of humans, the amount of data produced daily on a global scale is unthinkable. Add to this the massive number of alerts most organizations see from their SIEM, firewall logs, and user activity, and it’s clear human security analysts are simply unable to operate in isolation. Thankfully, this is where machines excel, automating simple tasks such as processing and classification to ensure analysts are left with a manageable quantity of actionable insights.

It’s essential that we respond quickly to security incidents, but we also need to understand enough about an incident to respond intelligently. Machines play a huge role here because they can process a massive amount of incoming data in a tiny fraction of the time it would take even a large group of skilled humans. They can’t make the decision of how to act, but they can provide an analyst with everything they need to do so.

Selecting a new “digitally focused” sourcing partner

Posted on : 18-07-2018 | By : john.vincent | In : Cloud, FinTech, Innovation, Uncategorized

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It was interesting to see the recent figures this month from the ISG Index, showing that the traditional outsourcing market in EMEA has rebounded. Figures for the second quarter for commercial outsourcing contracts show a combined annual contract value (ACV) of €3.7Bn. This is significantly up 23% on 2017 and for the traditional sourcing market, reverses a downward trend which had persisted for the previous four quarters.

This is an interesting change of direction, particularly against a backdrop of economic uncertainty around Brexit and the much “over indulged”, GDPR preparation. It seems that despite this, rather than hunkering down with a tin hat and stockpiling rations, companies in EMEA have invested in their technology service provision to support an agile digital growth for the future. The global number also accelerated, up 31% to a record ACV of €9.9Bn.

Underpinning some of these figures has been a huge acceleration in the As-a-Service market. In the last 2 years the ACV attributed to SaaS and IaaS has almost doubled. This has been fairly consistent across all sectors.

So when selecting a sourcing partner, what should companies consider outside of the usual criteria including size, capability, cultural fit, industry experience, flexibility, cost and so on?

One aspect that is interesting from these figures is the influence that technologies such as cloud based services, automation (including AI) and robotic process automation (RPA) are having both now and in the years to come. Many organisations have used sourcing models to fix costs and benefit from labour arbitrage as a pass-through from suppliers. Indeed, this shift of labour ownership has fuelled incredible growth within some of the service providers. For example, Tata Consultancy Services (TCS) has grown from 45.7k employees in 2005 to 394k in March 2018.

However, having reached this heady number if staff, the technologies mentioned previously are threatening the model of some of these companies. As-a-Service providers such as Microsoft Azure and Amazon AWS have platforms now which are carving their way through technology service provision, which previously would have been managed by human beings.

In the infrastructure space commoditisation is well under way. Indeed, we predict that the within 3 years the build, configure and manage skills in areas such Windows and Linux platforms will be rarely in demand. DevOps models, and variants of, are moving at a rapid pace with tools to support spinning up platforms on demand to support application services now mainstream. Service providers often focus on their technology overlay “value add” in this space, with portals or orchestration products which can manage cloud services. However, the value of these is often questionable over direct access or through commercial 3rd party products.

Secondly, as we’ve discussed here before, technology advances in RPA, machine learning and AI are transforming service provision. This of course is not just in terms of business applications but also in terms of the underpinning services. This is translating itself into areas such as self-service Bots which can be queried by end users to provide solutions and guidance, or self-learning AI processes which can predict potential system failures before they occur and take preventative actions.

These advances present a challenge to the workforce focused outsource providers.

Given the factors above, and the market shift, it is important that companies take these into account when selecting a technology service provider. Questions to consider are;

  • What are their strategic relationships with cloud providers, and not just at the “corporate” level, but do they have in depth knowledge of the whole technology ecosystem at a low level?
  • Can they demonstrate skills in the orchestration and automation of platforms at an “infrastructure as a code” level?
  • Do they have capability to deliver process automation through techniques such as Bots, can they scale to enterprise and where are their RPA alliances?
  • Does the potential partner have domain expertise and open to partnership around new products and shared reward/JV models?

The traditional sourcing engagement models are evolving which has developed new opportunities on both sides. Expect new entrants, without the technical debt, organisational overheads and with a more technology solution focus to disrupt the market.