Trends in artificial intelligence (AI) in cybersecurity



The world works with data, and humans alone could never monitor or protect it all.

When applied thoughtfully, cybersecurity enhanced by artificial intelligence (AI) can add essential layers of protection to modern enterprise networks.

AI in cybersecurity today

Research firm Technavio expects the AI-powered cybersecurity market to grow by $ 19 billion from 2021 to 2025. The company cites the growing complexity of enterprise network environments, which often include a mix of legacy infrastructure , on-premises and cloud resources, all of which must be accessible remotely. AI approaches add efficiency and precision and reduce the impact of the continuing shortage of workers in this field.

As organizations have become more comfortable with stand-alone applications that help streamline workflows and reduce human error, it’s only natural that we are also seeing more AI in cybersecurity adoption. These five cybersecurity trends underline the global shift towards business applications of AI in many areas:

5 trends: AI in cybersecurity

1. AI will reduce the burden of cybersecurity worker shortage

As workers around the world were sent home from their desks to work remotely in 2020 during the COVID-19 pandemic, cybercriminals were already waiting, ready to exploit the vulnerabilities widened by the massive influx of insecure network connections. These same tactics have been used in the SecOps field, which has faced a significant shortage of skilled workers for several years.

(ISC) 2 estimates that the cybersecurity market needs around 3 million skilled workers, according to its Cybersecurity workforce 2020 report. Additionally, the report shows that 64% of cybersecurity professionals surveyed said their organization was affected by the cybersecurity skills shortage.

When SecOps teams are understaffed, vulnerabilities naturally increase. No human could face all viable threats, as cybercriminals know.

AI plays a role in these situations. Sophisticated AI-based algorithms can recognize attack patterns, suspicious email activity, and identify the most vulnerable network endpoints. AI can also tackle repetitive, error-prone tasks, such as labeling data, and generate automated reports for human analyst review. All of these features will help reduce bandwidth for SecOps teams, so team members can focus on other security functions.

2. AI will automate identity and access management security measures

Identity and Access Management (IAM) is becoming more important than ever with the increasing adoption of zero-trust security frameworks, which require every user on the network to be authenticated, authorized and validated at all times.

AI can dramatically reduce the amount of manual labor required to achieve these goals by introducing intelligent 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 abnormal behavior.

AI can also improve security throughout the customer authentication experience, from account creation and login, to interacting with service accounts. AI monitoring of these activities helps organizations assign risk scores related to potentially suspicious events, rather than simply locking users out or terminating their connections mid-session. This more nuanced approach improves efficiency and helps analysts focus on real threats.

See more: Artificial Intelligence (AI) in Cyber ​​Security 2021

3. AI will improve the blockchain

Blockchain adoption has increased dramatically, as cryptocurrencies have become more widely understood. Grandview Research estimates the global blockchain technology market size to be around $ 3.67 billion in 2020 and expects this 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 in the medical field to better secure and monitor access to electronic records.

Advances in AI-powered blockchain have reduced the need for tedious Secure Socket Layer (SSL) and Transport Layer Security (TLS) “handshake” methods that involve verification keys . Instead, newer systems can analyze strings of data in bulk using powerful AI, which is a much faster process and a lot more secure overall.

4. AI will strengthen regulatory compliance efforts

AI can apply rules and regulatory requirements to data on complex networks, which is a faster and more foolproof method of compliance compared to manual research processes.

AI-powered data processing will be critical as more than 300 million new regulations are expected over the next decade, according to LogicGate.

Businesses can use AI to track regulatory agencies around the world to monitor and maintain ongoing compliance, as rules change and new rules are adopted, Logic Door said.

Improved regulatory compliance with AI is a smart investment, given the financial ramifications of not complying with general data laws, such as GDPR and HIPAA.

5. AI will improve cloud network security

As more organizations move parts of their data to the cloud, cybersecurity has become more complex. Many legacy systems are unable to monitor cloud data, but new AI-enhanced cybersecurity is designed specifically for the cloud.

Hybrid cybersecurity solutions involving AI capable of monitoring and analyzing data in multiple environments will become a must. Many organizations get by with an ad hoc approach, where corporate 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 the lack of important data.

See more: Top Performing Artificial Intelligence Companies of 2021


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