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Artificial Intelligence for Cybersecurity

Artificial intelligence endeavours to simulate human intelligence. It has immense potential in cybersecurity. If harnessed correctly, Artificial Intelligence or AI systems can be trained to generate alerts for threats, identify new types of malware and protect sensitive data for organisations. Artificial Intelligence is changing the game for cybersecurity, analyzing massive quantities of risk data to speed response times and augment under-resourced security operations. As cyberattacks grow in volume and complexity, artificial intelligence (AI) is helping under-resourced security operations analysts stay ahead of threats. Curating threat intelligence from millions of research papers, blogs and news stories, AI technologies like machine learning and natural language processing provide rapid insights to cut through the noise of daily alerts, drastically reducing response times. AI helps analysts connect the dots between threats also Artificial Intelligence improves its knowledge to “understand” cybersecurity threats and cyber risk by consuming billions of data artifacts. The important thing is AI analyzes relationships between threats like malicious files, suspicious IP addresses or insiders in seconds or minutes. Another thing to consider is that Artificial Intelligence provides curated risk analysis, reducing the time security analysts take to make critical decisions and remediate threats.



Understanding AI Basics

AI refers to technologies that can understand, learn, and act based on acquired and derived information. Today, AI works in three ways:

  • Assisted intelligence, widely available today, improves what people and organizations are already doing.

  • Augmented intelligence, emerging today, enables people and organizations to do things they couldn’t otherwise do.

  • Autonomous intelligence, being developed for the future, features machines that act on their own. An example of this will be self-driving vehicles, when they come into widespread use.


According to TechRepublic survey, a midsized company gets alerts for over 200,000 cyber events every day. A team of cybersecurity experts in an average company cannot deal with this volume of threats. Some of these threats will, therefore, naturally go unnoticed and cause severe damage to networks.

Artificial Intelligence is the ideal cybersecurity solution for businesses looking to thrive online today. Security professionals need strong support from intelligent machines and advanced technologies like AI to work successfully and protect their organisations from cyber attacks. Analyzing and improving cybersecurity posture is not a human-scale problem anymore.

In response to this unprecedented challenge, Artificial Intelligence (AI) based tools for cybersecurity have emerged to help information security teams reduce breach risk and improve their security posture efficiently and effectively. AI and machine learning (ML) have become critical technologies in information security, as they are able to quickly analyze millions of events and identify many different types of threats – from malware exploiting zero-day vulnerabilities to identifying risky behavior that might lead to a phishing attack or download of malicious code. These technologies learn over time, drawing from the past to identify new types of attacks now. Histories of behavior build profiles on users, assets, and networks, allowing AI to detect and respond to deviations from established norms.

Applying AI to cybersecurity

AI is ideally suited to solve some of our most difficult problems, and cybersecurity certainly falls into that category. With today’s ever evolving cyber-attacks and proliferation of devices, machine learning and AI can be used to “keep up with the bad guys,” automating threat detection and respond more efficiently than traditional software-driven approaches.

At the same time, cybersecurity presents some unique challenges:

  • A vast attack surface

  • 10s or 100s of thousands of devices per organization

  • Hundreds of attack vectors

  • Big shortfalls in the number of skilled security professionals

  • Masses of data that have moved beyond a human-scale problem


A self-learning, AI-based cybersecurity posture management system should be able to solve many of these challenges. Technologies exist to properly train a self-learning system to continuously and independently gather data from across your enterprise information systems. That data is then analyzed and used to perform correlation of patterns across millions to billions of signals relevant to the enterprise attack surface.

The result is new levels of intelligence feeding human teams across diverse categories of cybersecurity, including:


  • IT Asset Inventory – gaining a complete, accurate inventory of all devices, users, and applications with any access to information systems. Categorization and measurement of business criticality also play big roles in inventory.

  • Threat Exposure – hackers follow trends just like everyone else, so what’s fashionable with hackers changes regularly. AI-based cybersecurity systems can provide up to date knowledge of global and industry specific threats to help make critical prioritization decisions based not only on what could be used to attack your enterprise, but based on what is likely to be used to attack your enterprise.

  • Controls Effectiveness – it is important to understand the impact of the various security tools and security processes that you have employed to maintain a strong security posture. AI can help understand where your infosec program has strengths, and where it has gaps.

  • Breach Risk Prediction – Accounting for IT asset inventory, threat exposure, and controls effectiveness, AI-based systems can predict how and where you are most likely to be breached, so that you can plan for resource and tool allocation towards areas of weakness. Prescriptive insights derived from AI analysis can help you configure and enhance controls and processes to most effectively improve your organization’s cyber resilience.

  • Incident response – AI powered systems can provide improved context for prioritization and response to security alerts, for fast response to incidents, and to surface root causes in order to mitigate vulnerabilities and avoid future issues.

  • Explainability – Key to harnessing AI to augment human infosec teams is explainability of recommendations and analysis. This is important in getting buy-in from stakeholders across the organization, for understanding the impact of various infosec programs, and for reporting relevant information to all involved stakeholders, including end users, security operations, CISO, auditors, CIO, CEO and board of directors.



Companies using Artificial Intelligence for Cyber security


1. DNSFilter


To defend those navigating internet domain connections, DNSFilter is providing more efficient and comprehensive protection. The company’s content filtering and threat detection system divides threats into 36 categories, allowing for flexibility and peace of mind. Companies can adopt DNSFilter’s roaming clients to tailor security features to the nature of their workforce. This way, businesses can stave off domain-based threats without disrupting their workflows.


2. Versive


Versive helps businesses and organizations identify crucial threats, helping teams save time that might otherwise be spent investigating alerts that don’t require immediate attention. The Versive Security Engine (VSE) uses artificial intelligence to separate critical risks from routine network activity, identifying chains of activities that result in attacks and helping security teams to get ahead of those attacks.


3. LogRhythm


LogRhythm provides an end-to-end security solution for companies and organizations to detect and quickly respond to cybersecurity threats. The company uses machine learning to profile and detect threats, compromised accounts, privilege abuse and other anomalies. A user interface allows security teams to more easily and quickly respond to threats.


4. Cybereason


Cybereason is a cybersecurity analytics platform that provides threat monitoring, hunting and analysis. It gives companies and organizations greater visibility within their security environment as well as the ability to get ahead of threats. Cybereason’s AI-powered hunting technology determines whether or not an organization is under attack. Threat hunting typically requires significant resources, but Cybereason automates the job so security teams of all sizes and skill levels can benefit.


5. SparkCognition

SparkCognition provides AI-powered operations, security and automation solutions to a range of industries, from cybersecurity and aviation to finance and manufacturing. For organizations and businesses in need of cyber defense solutions, SparkCognition provides machine learning-powered products that detect and protect against malware, ransomware, trojans and other threats

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