ML and AI: Key Technology to Elevate Cybersecurity for the Digital Age

by Micro Focus Employee in CyberRes

Are you equipped to meet the needs of futuristic cybersecurity operations?

Cybersecurity Operations have been evolving and growing at an immensely high speed. Data is an asset for the organizations so it is important to ensure the organizational assets are secure and always protected. To prevent cyber attacks, organization establish a Security Operations Center or SOC. However with the humongous growth in data, event, and complexity it has been a tiresome task for SOC engineers to be on top of threats. Artificial Intelligence (AI) powered by Machine Learning (ML) enables threat identification and its remediation, and also counters Zero Day Threats. Let us explore what AI and ML is in cybersecurity, and how it is creating an impact.

Why AI/ML in Cybersecurity?

ML and AI Key Technology to Elevate Cybersecurity for the Digital Age.Artificial Intelligence: AI is a capability that can enrich other products—it hones the focus of prevention, detection, and response products, and provides options for prediction. AI is a solution that improves effectiveness within teams and departments

Machine Learning is a science to learn the behavioral pattern and tune the machines/systems to perform better without any human support with help of Artificial Intelligence.

Machine Learning has become a vital technology for cybersecurity. Machine Learning preemptively stamps out cyber threats and bolsters security infrastructure through pattern detection, real-time cyber-crime mapping, and thorough penetration testing.

Machine Learning is the most relevant AI cybersecurity discipline to date. Deep learning (DL) works similarly to Machine Learning by making decisions from past patterns but adjusting on its own. Deep learning in cybersecurity currently falls within the scope of Machine Learning, so we will focus mostly on ML here.

Current Usage of AI/ML in Cybersecurity:

AI analyzes relationships between threats like malicious files, suspicious IP addresses, or insiders in seconds or minutes. AI provides curated risk analysis, reducing the time security analysts take to make critical decisions and remediate threats.

Machine Learning, as evident from the name, helps to make the computer more like humans in the ability to learn and act. Machine Learning is actively used today, in many areas than one would expect. We use a learning algorithm dozen times without even knowing it.

Currently, Machine Learning is used in:

  • Web Search Engine:One of the reasons why search engines like Google, Bing, etc work so well is because the system has learned how to rank pages through a complex learning algorithm.
  • Photo tagging Applications:Be it Instagram, Facebook, or any other photo tagging application, the ability to tag friends makes it even more engaging. It is all possible because of a face recognition algorithm that runs behind the application.
  • Spam Detector:Our mail agent like Gmail or Hotmail does a lot of hard work for us in classifying the emails and moving the spam mails to the spam folder. This is again achieved by a spam classifier running in the back end of the mail application. 

In Cybersecurity AI/ML is Used For:

  • Password protection and authentication
  • Phishing detection and prevention control
  • Vulnerability management
  • Network security /Data Flow
  • Behavioral analytics 

Emerging Trends: Threat Detection/Functions where AI can ease off/help

Machine learning in cybersecurity plays a vital role in the reduction of repetitive tasks with help of automation and plays instrumentally in the orchestration of security events and actions. SIEM and SOAR tools have immense power with ML and AI and are now an important component to monitor and manage corporate information security. 

Machine Learning and Artificial Intelligence have emerged as critical tools for dealing with the ever-growing volume and complexity of cybersecurity threats.

The below graphs show how AI/ML is being used in different areas of cybersecurity.

AI in Cybersecurity executive survey

AI can help automate many tasks that a human analyst would often manage manually. It helps lessen the tasks of a SOC Analyst, SOC Manager, resolvers, and CISO. Also, enrichment potentially helps with predictive trends in any SecOps stream to determine the trend of the future based on the records and events of the past. The combination of AI and Machine Learning in cybersecurity is proving to be a competitive differentiator. It can allow you to adopt cybersecurity that is effective in preventing unknown, zero-day threats.

Automation:

Automation reduces repetitive tasks and minimizes the effort of a SOC engineer and leaves no chance for human errors, which in turn saves efforts in troubleshooting and resolving the change-related issue. Automation helps optimize the throughput from SOC by 12-15 times.

Security Orchestration Automation & Response utilities are based on AI, and with the ability to create playbooks for the repetitive task and further tune them based on the data enrichment. Automation along intelligent threat feeds also allows the creation of context-aware threat analysis and response faster which boost the confidence in the identified event. Automation also enables search, visualize, analysis, and building cooperation across your security use cases on deeply interoperable and context-aware analytics.

Machine Learning in Cybersecurity

Machine Learning has become a vital technology for cybersecurity. It preemptively stamps out cyber threats and bolsters security infrastructure through pattern detection, real-time cybercrime mapping, and thorough penetration testing.

The below diagram depicts the areas and attributes of a SOC where the AI/ML can be conducive and significantly can bring in effort reduction and a higher degree of confidence while enriching further to automate the response. It can enrich the telemetry, and analytics, and helps in the assessment.

AI ML for SOC

Conclusion:

AI has emerged as a key technology to elevate cybersecurity for the digital age. It’s already demonstrating its ability to improve the accuracy, detection, and prevention of cyber threats. AI-driven cybersecurity offers other business benefits as well, including reduced costs and improved user productivity time. Cyberattacks are an ugly reality for organizations around the globe, and the threats grow more challenging with each passing day. The emergence of AI technology that integrates into your cybersecurity is an important trend worth your investigation. AI is going to support your org in many ways, however, the human element will keep playing a crucial role with an increased level of confidence to support their decisions. 

CSA Bangalore Chapter in association with CyberRes are conducting a global webinar focusing around Artificial Intelligence-powered Security Solutions. 

You can join the live session, Multi-layer Intelligence for Cyber Resilience, on Sept 28th, 7:30 PM IST/ 4 PM CET / 10 AM EST by registering for the webinar. 

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