AI Security

Introduction

AI simulates human intelligence processes by machines, especially computer systems. AI can learn from experience, adapt to new inputs, and perform tasks that typically require human intelligence. AI has been widely used in various industries, and cybersecurity is no exception.

The number and complexity of cybersecurity threats have increased with the increased use of technology and internet-connected devices. Organizations find it challenging to keep up with these threats, and traditional cybersecurity methods are becoming less effective. As a result, organizations are turning to AI to enhance their cybersecurity efforts.

AI for Security

At a fundamental level, AI security solutions are designed to differentiate between safe and malicious behaviors by comparing user behaviors in a given environment to those in a similar environment. This process, known as unsupervised learning, is performed by the system without human supervision.

For some AI platforms like Vectra, deep learning is another important application for identifying malicious behavior. Deep Learning is inspired by the biological structure and function of neurons in the brain and involves large, interconnected networks of artificial neurons. These neurons are arranged into layers, each connected to others by weights that adapt in response to new inputs.

Advanced AI cybersecurity tools can process and analyze large datasets, enabling them to identify patterns of activity that indicate potential malicious behavior. This allows AI to emulate the threat detection capabilities of human analysts. In addition to threat detection, AI can be used for automation, triaging, alert aggregation, alert sorting, and automated responses. As a result, AI is often utilized to augment the work of the first level of analysts.

Common Uses of AI in Cybersecurity

Artificial intelligence (AI) security solutions can detect, anticipate, respond to, and acquire knowledge about cybersecurity threats with minimal human involvement. Advanced AI security tools are capable of the following:

• Conducting unsupervised Learning based on past observed behaviors
• Interpreting and making decisions on new or incomplete data and behaviors based on context
• Providing effective solutions to mitigate threats or security weaknesses

AI for Improved Threat Defense

The concept of artificial intelligence has been highly coveted due to its potential to transform various aspects of modern business. For example, with machine learning and natural language processing, AI can now be used for cybersecurity. Combining it with other security solutions can improve prevention, detection, and response capabilities and even enable predictions. This leads to faster identification and remediation of threats.

AI Implementation

Implementing AI in cybersecurity provides several advantages, including reduced reliance on human management and improved efficiency in handling security operations. In addition, AI can be integrated with other security products to support specific use cases, such as detecting and neutralizing phishing, spam, or malware with high accuracy.

As AI technology matures and becomes more trusted, organizations can start to integrate individual tasks into an orchestrated sequence. This can help to improve overall security posture and enable AI to learn from encounters with cyber threats, allowing it to gather observations and apply logical conclusions to enhance its capabilities over time.

Three core capabilities of AI are essential in cybersecurity:

• Learning:
  AI can be trained to understand cybersecurity and associated risks by consuming large amounts of structured and unstructured data artifacts. Machine learning and deep learning techniques improve AI's knowledge and provide better tools than previously available. However, unstructured data, such as facial recognition and analysis of video and audio, is an area where AI can excel beyond human capabilities.

• Reasoning:
  AI can identify relationships between different attributes and gain insights through reasoning. For example, it can connect malicious files, insiders, or IP addresses and enrich findings with behavioral and historical insights. This enables exponentially quicker decision-making as AI gains more experience from which to draw insights.

• Automation:
  Organizations can optimize their automation efforts by combining them with AI advancements. Automated processes collect vital data, and AI runs the models to generate improved analytical insights.

By leveraging these core capabilities, organizations can improve their security operations and reduce their vulnerability to cyber threats.

Why do Artificial Intelligence, and Security Matter?

Determining the necessity of AI security for cyber defense can be challenging. However, the continuously evolving malicious programming and other threats make traditional cybersecurity more challenging.

According to Capgemini, approximately 60% of organizations use artificial intelligence technologies to identify critical threats. Considering the following factors can help in making a better decision:

• AI helps reinforce gaps in the cybersecurity workforce:
  The demand for cybersecurity professionals is high, and there need to be more qualified professionals. AI can help fill this gap by automating tasks that typically require human intervention, such as threat detection and response. This can free up cybersecurity professionals to focus on more complex tasks.

• AI promotes faster threat identification:
  AI can analyze vast amounts of data in real-time to identify threats. This can help organizations detect and respond quickly to threats before they can cause damage.

• AI allows businesses to counter threat escalation:
  Threats are becoming more sophisticated, and organizations are finding it difficult to keep up. AI can help organizations counter these threats by analyzing data to identify patterns and anomalies that indicate a potential threat. Once a threat is detected, the system can take action to mitigate the threat.

Automating Threat Analysis

During incident response, companies must perform incident triage and analysis to determine how to contain and remediate incidents while eliminating false positives. Some companies use threat intelligence feeds during the response process, and automatically correlating information while leveraging enrichment from other tools can reduce analysis time.

AI can improve these processes by analyzing significantly larger data in a shorter period and providing additional context, prediction, and historical insight.

The Use of AI across Cybersecurity Teams

AI can be used across cybersecurity teams to improve threat defense. This can include automating tasks like threat detection and response and analyzing data to identify patterns and anomalies that indicate a potential threat.

• Threat exposure:
  AI can help organizations identify areas of vulnerability in their systems. By analyzing data from multiple sources, AI algorithms can identify patterns and vulnerabilities that may not be apparent to human analysts.

• Incident response:
  AI can help organizations respond to security incidents quickly and effectively. Organizations can reduce the time it takes to respond to security incidents by automating threat detection and response.

• Breach risk prediction:
  AI can help organizations predict the likelihood of a security breach. By analyzing data from multiple sources, AI algorithms can identify patterns and anomalies that may indicate a potential breach. This can help organizations take proactive measures to prevent breaches from occurring.

• Controls effectiveness:
  AI can help organizations determine the effectiveness of their security controls. By analyzing data from multiple sources, AI algorithms can identify weaknesses in an organization's security posture and provide recommendations for improvement.

The Benefits of Leveraging AI Technologies in Security

• Increased accuracy and efficiency:
  AI algorithms can analyze vast amounts of data in real-time, making them more accurate and efficient than traditional methods.

• Reduced response time:
  By automating tasks such as threat detection and response, AI can reduce the time it takes to respond to security incidents.

• Improved threat detection:
  AI can analyze data from multiple sources to identify patterns and anomalies that indicate a potential threat. This can help organizations detect threats that have gone unnoticed with traditional methods.

• Reduced costs:
  By automating tasks and improving threat detection, AI can help organizations reduce the costs associated with cybersecurity.

How to Evaluate an AI Cybersecurity Vendor for Your Network?

Evaluating an AI cybersecurity vendor for your network requires asking the right questions to determine if their solution can protect your network. Here are nine essential questions to consider:

• What machine learning algorithms does the vendor's product use?
• How many machine learning algorithms are there, and how are they categorized? How often are they updated, and new ones released?
• How long does it take for machine learning algorithms to detect threats in a new environment? How many algorithms require a learning period, and how long does that take?
• How does the product prioritize critical and high-risk hosts that require immediate attention from an analyst?
• Does the product integrate seamlessly with existing detection, alerting, and incident response workflows?
• Does the product offer firewall, endpoint security, or network access control (NAC) integration to block or contain detected attacks? How does it integrate with these platforms?
• What level of workload reduction can the product provide for security analysts? What level of efficiency increase can be expected?
• Does the product support running red team exercises to test the value of machine learning algorithms and AI in real-world scenarios? Will the vendor pay for the red team if the product fails to detect anything?
• Does the vendor recommend that human analysts have remote access to the product during the evaluation? If so, why?