AI And The Cybersecurity Workforce: A Whole New World
Billions of people were affected by data breaches and cyberattacks last year – $765 million in damages was in the months of April, May and June alone. It, therefore, comes as no surprise that demand for cybersecurity expertise is higher than ever. The demand has increased to the point where unfilled positions in the cybersecurity sector outnumber the number of available specialists in the field.
With an anticipated 3.5 million cybersecurity jobs to go unfilled by 2021, artificial intelligence (AI) presents a real opportunity for businesses to help bridge the gap. For a long time, AI and machine learning (ML) have faced obstacles in cybersecurity applications, chiefly because the differentiation of attack styles and threat levels often make it very difficult for an algorithm to accurately predict a threat. However, as the volume of logged data increases, new AI solutions are being developed that can improve predictive accuracy and, at a minimum, vastly increase the capability of the limited cybersecurity workforce.
What advantages can AI offer to cybersecurity?
AI holds the upper hand when it comes to optimizing speed, accuracy and breadth of coverage, so it can help provide protection by automating complex processes for recognizing hacks, investigating attacks and addressing security breaches. AI is making leaps and bounds in the following areas:
• Prediction: Humans have the advantage over computers here because they can use their previous experiences and knowledge to deal with system abnormalities. However, advancements in machine learning are enabling computers to make decisions based on collected data. Each time a machine experiences something new, its proficiencies will increase to the point where they may be able to predict threats. Finnish cybersecurity and privacy company F-Securehas an automatic advanced-threat-identification solution that uses real-time behavioral, reputational and big data analysis with machine learning to contextualize detections. It gauges risk levels, affected host criticality and the current threat landscape to know the scope of a targeted attack.
• Prevention: Cybercriminals easily break through security barriers like passwords and firewalls. AI has the potential to make this much harder to do. For example, IBM provides out-of-band (OOB) authentication mechanisms to offer its customers more secure user identification methods. OOB uses a series of inputs to confirm user identity, sometimes without user involvement. Elements involved in this process include fingerprint scans, computer mouse movements, user operational environment and voiceprint analysis. In this way, AI could enable the system to constantly analyze the operator’s behavior and adapt the factors it uses accordingly, therefore increasing the security level.
• Detection: Cybercriminals try to maneuver around even the most efficient preventative methods, but businesses can also leverage AI to detect potential breaches. Systems already exist that use AI to detect existing and potential cyberthreats. Many attacks occur through individual applications rather than the wider network, which means current detection systems are insufficient for identifying these specific attacks. The AppSensor approach, developed by the Open Web Application Security Project (OWASP), detects cyberattacks within applications and responds, typically by locking the criminal user out of the application.
How does AI make human jobs easier?
The most obvious benefit is the minimization of human efforts. For most organizations, cybersecurity staff members need to be on site 24/7 to protect servers and systems. They are on duty to detect threats and address them in a timely manner before they can cause further damage.
AI is most commonly used to detect simple threats and attacks. Now, considering that the simplest attacks often have the simplest solutions, the systems can also likely remediate the situation on their own. Therefore, cybersecurity teams reliant on intelligent automation to raise risk red flags will find themselves with more time to allocate to increase efficiencies elsewhere, while reducing the pressure on available resources.
What do humans bring to the cybersecurity table that AI can’t?
Of course, these systems, even when powered by AI, are only as effective and efficient as their human masters. Humans are emotional, social and political. These qualities are our greatest weaknesses, but when it comes to competing with AI, they are also our greatest strengths.
In a cybersecurity context, AI can and likely will take over everything that is structured, logical, repeatable and systematic. But intuition, creativity and knowledge of culture are all traits that only humans can provide. Take AI and overlay it with human curation, and you’ll have a cybersecurity system that’s tougher, more flexible and strategically more capable of anticipating emerging cyberattack methods.
How will AI impact job roles in cybersecurity?
It’s evident that AI-driven systems have started to replace humans in numerous industries, but not in the cybersecurity space. Using AI alone to spot cyberattacks isn’t really practical because such systems lack contextual awareness, which can lead to attacks being wrongly identified or missed completely. Instead of taking over jobs, AI will simply change existing cybersecurity roles.
For example, cybersecurity professionals tend to sift through and rate security techniques and tools, deciding which ones are best for their workflow. AI could provide assistance, replacing roles that are repetitive and systematic, but it can’t offer easy answers. Companies must rely on their personnel to fill the roles that AI can’t at this point. They need people who understand more complex problems, including deeper layers of business risk. This may call for a cybersecurity professional with a bit of a different background, including some skills related to making key business calls.
Will AI replace human cybersecurity jobs completely?
Just as AI begins to take on roles previously undertaken by humans, it will create new human jobs. It will create new issues that humans need to solve through deeper analysis. AI and the humans that work so closely with it will be able to complement each other’s strengths and weaknesses, leading businesses to newer, more innovative destinations.
While a shortage of human talent in the cybersecurity industry remains, there is much to be gained from relying on technologies such as ML to augment the capabilities of the humans the sector does have.
Original report can be found on Forbes.
Machine Learning for Cybersecurity 101May 14, 2019
Cybersecurity Experts Share Tips And Insights For World Password DayMay 2, 2019
Hacker Finds He Can Remotely Kill Car Engines After Breaking Into GPS Tracking AppsApril 29, 2019
What your laptop-holding position says about youApril 19, 2019
Game of Thrones Guide to Cybersecurity: Preparing for Battle During a Staffing ShortageApril 19, 2019