Why AI Technology Is the future of Cybersecurity?

AI AI

While 61 percent of enterprises state without the use of AI technologies they will not be able to detect breach attempts today, 48 percent say that they will increase their budgets for AI in cybersecurity by an average of 29 percent in financial year 2020.

Breach attempts are growing with Cisco reporting that in 2018, they blocked seven trillion threats for their customers.

These and various other insights from Capgemini’s Reinventing Cybersecurity with Artificial Intelligence Report published recently. Capgemini Research Institute studied 850 senior executives from seven industries, with consumer products, retail, banking, insurance, automotive, utilities, and telecom. Around 20 percent of the executive respondents are CIOs, and 10 percent are CISOs. Enterprises headquartered in France, Germany, the UK, the US, Australia, the Netherlands, India, Italy, Spain, and Sweden are included in the report.

Capgemini found that with the growth of their digital businesses, their threat of cyberattacks exponentially increases. According to 21 percent respondents, their organization experienced a cybersecurity breach causing unauthorized access in 2018. Enterprises are paying a huge price for cybersecurity breaches. Centrify’s most recent survey, Privileged Access Management in the Modern Threatscape, found that 74 percent of all breaches involved access to a privileged account. Privileged access credentials are hackers’ most popular technique for initiating a breach to ex-filtrate valuable data from enterprise systems and sell it on the Dark Web.

Key insights include the following:

About 69 percent of enterprises think that AI will be essential to respond to cyberattacks. Most of the telecom companies (80 percent) say they are counting on AI to help identify threats and thwart attacks. Capgemini found the telecom industry has the most reported incidence of losses exceeding $50 million, making AI a main concern for thwarting costly breaches in that industry. It’s understandable by Consumer Products (78 percent), and Banks (75 percent) are 2nd and 3rd given each of these industry’s growing reliance on digitally-based business models. US-based enterprises are placing the highest priority on AI-based cybersecurity applications and platforms, 15 percent higher than the global average when calculated on a country basis.

Today around 73 percent of ventures are using cases for AI for cybersecurity over their organizations with network security leading all categories. Endpoint security, the 3rd-highest main concern for putting in AI-based cybersecurity solutions given the proliferation of endpoint devices, which are likely to increase to over $25 billion by 2021. Internet of Things (IoT) and Industrial Internet of Things (IIoT) sensors and systems they allow are exponentially expanding the number of endpoints and risk surfaces an enterprise should protect. The old “trust but verify” way to enterprise security can’t keep up with the pace and scale of threatscape growth today. Identities are the new security perimeter, and they require a Zero Trust Security framework to be safe.

Nearly 51 percent of officials are making widespread AI for cyber threat recognition, outpacing calculation, and response by a wide margin. Enterprise executives are concentrating their budgets and time on identifying cyber threats using AI above predicting and responding. As enterprises mature in their use and acceptance of AI as part of their cybersecurity endeavours, prediction and response will respectively increase.

Also 64 percent respondents state that AI reduces the cost to identify and react to breaches and decreases the whole time taken to detect threats and breaches up to 12 percent. The decrease in cost for a majority of enterprises ranges from 1– 15 percent (with an average of 12 percent). With AI, the overall time taken to detect threats and breaches is reduced by up to 12 percent. Dwell time – the amount of time threat actors stay unnoticed – falls by 11 percent with the use of AI. This time reduction is accomplished by continually scanning for known or unknown anomalies that show threat patterns. PetSmart, a US-based specialty retailer, was able to save up to $12 million by using AI in fraud detection from Kount. By collaborating with Kount, PetSmart was able to execute an AI/Machine Learning technology that aggregates millions of transactions and their outcomes.

The five highest AI use cases for improving cybersecurity are fraud detection, malware detection, intrusion detection, scoring risk in a network, and user/machine behavioral analysis. Capgemini analyzed 20 use cases across information technology (IT), operational technology (OT) and the Internet of Things (IoT) and levelled them as per their execution complexity and resultant benefits (in terms of time reduction).

According to 56 percent of senior executives, their cybersecurity analysts are overwhelmed and around 23 percent cannot successfully inspect all identified incidents. Capgemini got to know that hacking organizations are effectively using algorithms to send ‘spear phishing’ tweets (personalized tweets sent to focused users to trick them into sharing sensitive information). AI is able to send the tweets six times quicker than a human and with double the achievement. “It’s no surprise that Capgemini’s data shows that security analysts are overwhelmed. The cybersecurity skills shortage has been growing for some time, and so have the number and complexity of attacks; using machine learning to augment the few available skilled people can help ease this. What’s exciting about the state of the industry right now is that recent advances in Machine Learning methods are poised to make their way into deployable products,” said Nicko van Someren, Chief Technology Officer at Absolute Software.

Conclusion

Today AI and machine learning are redefining all aspect of cybersecurity. From improving organizations’ capability to expect and prevent breaches, protecting the propagating number of threat surfaces with Zero Trust Security frameworks to make passwords outdated, AI and machine learning are essential to securing the perimeters of any business. One of the most susceptible and fastest-growing risk surfaces are mobile phones.