Trends in Artificial Intelligence (AI) in Cybersecurity
The world runs on data, and humans alone could never monitor or safeguard all of it.
When applied thoughtfully, artificial intelligence (AI)-enhanced cybersecurity can add essential layers of protection for modern enterprise networks.
AI in cybersecurity today
Research firm Technavio expects the AI-based cybersecurity market to grow by $19 billion from 2021 to 2025. The company cites the increased complexity of enterprise networking environments, which often include a mix of legacy, on-premises infrastructure, and cloud resources, all of which need to be accessed remotely. AI approaches add efficiency and accuracy and reduce the impact of the ongoing worker shortage in this field.
As organizations have become more comfortable with autonomous applications that help streamline workflows and reduce human error, it’s only natural that we would see more AI in cybersecurity adoption as well. These five AI in cybersecurity trends underscore the overall shift toward AI business applications across many fields:
5 trends in AI in cybersecurity
1. AI will reduce burden from cybersecurity worker shortage
As workers around the world were sent home from their offices to work remotely in 2020 during the COVID-19 pandemic, cybercriminals were already lying in wait, ready to pounce on vulnerabilities widened by the mass influx of unsecure network connections. Those same tactics have played out across the SecOps field, which has been dealing with a significant skilled worker shortage for several years.
According to its 2020 Cybersecurity Workforce report, (ISC)2 estimates the cybersecurity industry is in need of about 3 million qualified cybersecurity workers. Additionally, the report says, 64% of the cybersecurity professionals surveyed say their organization is impacted by the cybersecurity skills shortage.
When SecOps teams are lacking in staffing, vulnerabilities naturally increase. No human could keep up with every viable threat, as cybercriminals know.
AI is playing a role in these situations. Sophisticated AI-driven algorithms can recognize patterns of attacks, suspicious email activity, and identify the most vulnerable network endpoints. AI can also tackle repetitive, error-prone tasks, like data labeling, and generate automated reports for human analyst review. All of these features will help to reduce SecOps teams’ bandwidth, so team members can focus on other important security roles.
2. AI will automate identity and access management security measures
Identity and access management (IAM) is becoming more important than ever with the increased adoption of zero-trust security frameworks, which require every network user to be authenticated, authorized, and continuously validated.
AI can greatly reduce the amount of manual labor required to carry out these goals by introducing smart automation into security systems. AI can monitor and analyze user activities, including typing and mouse movements. It can also power supervised algorithms and unsupervised learning, both of which help SecOps teams identify anomalous behavior.
AI can improve security across the customer authentication experience as well, from the point of account creation and login to interacting with service accounts. AI monitoring of these activities helps organizations to assign risk scores related to potentially suspicious events, instead of simply locking users out or terminating their connections mid-session. This more nuanced approach improves efficiency and helps analysts zero in on genuine threats.
3. AI will improve blockchain
Blockchain adoption has been increasing dramatically, as cryptocurrencies have become more widely understood. Grandview Research values the global blockchain technology market size at around $3.67 billion in 2020 and expects that figure to skyrocket, growing at a compound annual growth rate (CAGR) of 82.4% from 2021 to 2028.
Bitcoin and other crypto coins are built on blockchain solutions that keep transactions secure and decentralized. Blockchain is also used within the medical field to better secure and monitor access to electronic records.
Advances in AI-powered blockchain have reduced the need for time-consuming SSL and TSL “handshake” methods that involve verification keys. Instead, newer systems can analyze data chains in bulk using high-powered AI, which is much faster and far more secure overall.
4. AI will enhance regulatory compliance efforts
AI can apply regulatory rules and requirements to data across complex networks, which is a quicker, more foolproof compliance method versus manual search processes.
Regulatory compliance enhanced with AI is a smart investment, considering the financial ramifications of being found out of compliance with regulatory data protocols, like the CCPA and GDPR.
5. AI cybersecurity will improve cloud network security
As more organizations move portions of their data to the cloud, cybersecurity has become more complex. Many legacy systems are incapable of monitoring cloud data, but newer AI-enhanced cybersecurity is specifically designed for the cloud.
Hybrid cybersecurity solutions that are able to monitor and analyze data across multiple environments will become a must. Many organizations have been getting by with an ad hoc approach, where enterprise data is pulled from various architectures, compiled, and then analyzed by a software platform. Not only are these approaches complicated and expensive, but they are also prone to missing important data.
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