AI Is Closing The Cyber Skills Gap

People are still a definitive driving force behind cybersecurity protection and top talent is hard to come by. The widespread shortage of talented security operations and threat intelligence resources is creating a wave of new technologies and developments.

As more and more businesses incorporate Artificial Intelligence (AI) and machine learning into their products and services, several questions arise. Not least , “Will AI replace human jobs?” and, “Should we all be worried?”

Even though AI is the newest culprit, concerns over technology replacing humans date back to the 2nd Industrial Revolution when the economy shifted and farmers transitioned into more manufacturing and railroad jobs, society worried that they would see the end of the days where actual humans produced results, not machines. 

As AI and machine learning continue to advance, they will act as a tool to slowly replace the more menial tasks and ultimately, improve human workers’ experiences.

The 2019 Cybersecurity Workforce Study produced by(ICS)2 looked at the cybersecurity workforce in 11 markets. The report found that while 2.8 million people currently work in cybersecurity roles, an additional 4 million were needed and as organisations battle a developing cluster of external and internal threats, artificial intelligence (AI), machine learning (ML) and automation are playing progressively large roles in stopping that workforce gap.

How far can machines go in supporting and enhancing cyber defence teams. Is it possible they  will they supersede humans in cyber security?​

These questions penetrate most enterprises, yet the expense of cybercrime to organisations, governments and people is rising sharply. Studies show that the effect of cyberattacks could hit an exciting $6 trillion by 2021. What’s more, the expenses are not just financial.As organisations harness and harvest data from billions of people, endless high-profile data breaches have made privacy a top concern. Reputations and at times individuals’ lives are on the line.

The market for software to protect against cyberattacks is also growing and the current value of the AI-focused cyber security market, specifically, is pegged at around $9 billion. Companies can begin to close the skills gap by enlarging their workforce utilising AI abilities.

Although  AI isn’t about  to supplant people however, rather, it it offers an amazing mix of man and machine, intended to enhance human performance. Probably the best case of this is centaur versus supercomputer chess.

While supercomputers beat people at chess reliably, a centaur consolidates human instinct and innovativeness with a computer’s ability to recall and ascertain a huge number of moves, countermoves and results. Accordingly, novice chess players with desktop computers reliably beat the two supercomputers and chess champions by a wide edge.

Verizon’s 2018 Data Breach Investigations Report found thet the use of stolen credentials was the most widely recognised strategy of obtaining unauthorised access and the prvious 2017 report found that 81% of all breaches included some kind of user behavior activity.

Observing a huge number of malware-related and user activity events a day is time-consuming and tedious and this type of hard work lies behind the  high turnover at the tier one security operations center staff. Given the volume of false positive occasions, most organisations do not have the ability to analyse each event, particularly during the reconnaissance or delivery phase of the kill chain. As not everything suspicious is malevolent, most alerts are bogus positives.

User Behavior Analytics developed by the experts at Splunk and other cyber security firms have begun to use AI to distinguish patterns and analyse irregularities that definitely decrease the “signal to noise” proportion, hailing those alarms that bear investigating.

AI is a powerful way to improve SOC analyst productivity and effectiveness and reduce the time it atakes gor humans to to recognise, analyse, explore and prioritise security alerts. In short, AI in cyber security can be used as a force multiplier for security analysts by applying it directly to the investigation procedure.

Through AI powered analytics security teams can reduce manual, error-prone research, make investigation outcome predictions (high or low priority, real or false), and identify threat actors, campaigns, related alerts and more. Companies can assess the effectiveness of their current security efforts by distinguishing what stage along the cyber kill chain attacks are recognised.

Early-stage detection empowers organisations to respond before a hacker enters the earth, in any case, alerts detected at later stages present a fundamentally more serious risk. Adding AI powered analytical tools to the threat-monitoring process permits organisations to develop from a reactive to a proactive approach and address potential dangers before they escalate.

Accenture:       Venturebeat:       Analytics Insight:         Security Boulevard: 

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