Three Key Artificial Intelligence Applications For Cybersecurity
AI is certainly the core technology leading the smart digital transformation of our 4 Industrial Era. Computers with AI are designed for automation activities that include, speech recognition, learning, planning, and problem solving. These technologies can provide for more efficient decision making by prioritizing and acting on data, especially across larger networks with many users and variables. AI is a catalyst for driving fundamental changes in many industries such as customer service, marketing, online banking, healthcare, business accounting, public safety, retail, education, and public transport.
We are at the doorstep of a new era of smart technology and cybersecurity is already a testing ground. The cybersecurity industry is increasingly impacted by the deployment of solutions supported by artificial intelligence. According to research from cybersecurity experts Darktrace, an attempted cyberattack during the Tokyo Olympics was thwarted thanks to the assistance of a cybersecurity artificial intelligence (AI). The firm discovered an attempted attack a week before the games began using artificial intelligence monitoring tools. AI neutralizes IoT attack that threatened to disrupt the Tokyo Olympics | Blog | Darktrace
The core of AI smart capabilities is rooted in its subcomponent of machine learning, ML. AI is largely used to protect networks as well as increase data security and endpoint security according to 850 senior IT executives surveyed in 2019 (Statista 2021). Moreover, the market of artificial intelligence in cybersecurity is expected to grow at a compound annual growth rate of 23.6% from 2020 to 2027 to reach $46.3 billion by 2027 (Meticulous Research 2020). This predicted growth is likely to increase when considering all the social changes that have been provoked by the Covid-19 pandemic – from a boost to the digital economy to the displacement of millions of workers who now work remotely. Add the exponential increase in the number of Internet of Things (IoT) connected devices, the major shortage of skilled cybersecurity workers, and rapidly growing internet attack surface, the need to automate and use AI will become a market driver for years to come.
There are, among others four specific areas where AI technology can contribute to make cybersecurity responses to threats a smarter:
According to Cybersecurity Ventures CEO Steve Morgan, the human attack surface is to reach 6 billion people by 2022 and Cyber-crime damage costs to hit $6 trillion annually by 2021. That is a large and costly cyber-ecosystem to surveil, protect, and remedy. Data breaches and cyber-attacks have dire consequences for companies as loss of data from a breach or ransomware attack can cost millions of dollars and can lead to bankruptcy. In 2020, it took on average two hundred days for an organization to detect a data breach and an additional 80 days to contain the incident. That is too long to be able to effectively respond and mitigate a serious breach.
AI can provide a faster means to detect and identify cyber-threats. Cybersecurity companies have developed software and platform powered by AI that monitors in real time activities on network by, scanning data and files to recognize unauthorized communication attempts, unauthorized connections, abnormal/malicious credential use, brute force login attempts, unusual data movement, and data exfiltration. This allows businesses to draw statistical inferences and protect against anomalies before they are reported and patched.
AI threat hunting tools can cover cloud, data center, enterprise networks, and IoT devices. AI tools can allow for automatic updating and threat vetting of defense framework layers (network, server, payload, endpoint, firewalls, and anti-virus) and diagnostic and forensics analysis for cybersecurity.
