Cognitive security refers to the cybersecurity practice that applies artificial intelligence (AI) and machine learning (ML) techniques and technologies. Therefore, cognitive security is patterned after the human thought process in making sense of complex situations.
Cognitive security solutions are developed based on the skills of human threat, fraud, and other cybersecurity analysts. Hence, they are used in threat and fraud detection and strengthening an enterprise’s cybersecurity posture.
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To better understand cognitive security, we need to grasp the meaning of cognitive computing, which is the basis of this cybersecurity practice. Cognitive computing is the simulation of the human thought process through computerized models. In cognitive security, the goal is threat detection and modeling by mimicking the thought process of cybersecurity analysts.
How Does Cognitive Security Work?
In cognitive security, computer systems are fed vast amounts of data, which they process using AI and ML algorithms. These systems are taught to identify threat patterns, what actions to perform when a particular threat is detected, and how to process new data. Over time, they continue learning from all the data continuously fed to them. Their learning techniques become more refined and accurate, closely resembling the human security analyst’s thought process.
What Can Cognitive Security Systems Do?
Now that we know what cognitive security is and how it works in a nutshell, let us identify its specific capabilities. What, exactly, can cognitive security systems do? Below are five cognitive security capabilities:
- Detect threats: The primary goal of cognitive security is to alleviate security analysts’ threat detection tasks. Cognitive security systems can detect threats with high accuracy.
- Understand the context behind threats: Cognitive security systems go beyond identifying threats. They peel the threats and look deeper for context and characteristics.
- Identify threat patterns: Because they can contextualize threats and identify their common characteristics, cognitive security systems can detect patterns. This capability is helpful in threat modeling and prediction.
- Make decisions: Security analysts no longer have to evaluate every threat that cognitive security systems detect. The solutions themselves decide whether to block, delete, or quarantine the threat. Instead, security analysts can check the cognitive security system’s decision to ensure that it does what it’s supposed to do.
- Interact with human security analysts: Despite their autonomy when it comes to decision-making, cognitive security systems must still be able to interact with security analysts. For instance, security analysts may have to change requirements, and the algorithm as their organization’s security needs change over time.
- Interact with other machines: It may also become necessary for cognitive security systems to communicate with other machines, including software, cloud platforms, processors, and other hardware components.
What Are the Benefits of Cognitive Security?
Think of cognitive security as thousands, if not millions, of fraud and threat analysts at work 24 hours a day without taking breaks or succumbing to alert fatigue. With this in mind, organizations that employ cognitive security enjoy these advantages:
- Fewer false positives: Like other AI and ML applications, cognitive security systems have adaptive learning capabilities that allow them to accurately identify threats as they process more data. With better accuracy, false positives are avoided.
- Less alert fatigue: Security analysts face a major issue—alert fatigue, sometimes resulting in costly oversight of malicious incidents. Since cognitive security systems help reduce the number of false positives, analysts are more confident that the alerts they receive are accurate. Thus, they can prioritize remediation and investigation better.
- More flexibility: While cognitive security systems are at work, security analysts have the flexibility to evaluate and investigate unique incidents that don’t fall on any model. At the same time, analysts can further scrutinize cognitive security solutions’ decisions to strengthen their capabilities further.
- More efficient: Security analysts can leave the mundane task of sorting security incidents to cognitive security systems. As a result, they become more efficient and effective in performing their core functions as security analysts.
Cognitive security systems are among the many innovations cybersecurity professionals built to fight cybercrime. This AI and ML application continues to evolve and change the cybersecurity landscape.