What is Cognitive Security?

According to the World Economic Forum, misinformation and disinformation are the most critical issues facing global organizations today. Threat actors spread disinformation to undermine democratic institutions and the power of facts. These narrative attacks can generate a strong emotional reaction that leads people to share it without first looking into the facts, manipulating healthy conversations about the issues and increasing societal divisions. According to the Pew Research Center, one in five Americans receive daily news from social media. That same survey found that 64% of adults said “fake news” confused basic facts, and 23% said they had shared “fake news,” knowingly or unknowingly. Cognitive Security or COGSEC and Narrative Intelligence, can help detect threat patterns, identify what actions to perform when a threat is detected, and more. 

LEARN MORE: What Is A Narrative Attack?

Read more: Unlocking the Power of Narrative Intelligence

Cognitive security is an advanced branch of cybersecurity that uses artificial intelligence (AI) and machine learning (ML) technologies and techniques. Therefore, cognitive security operates like the human thought process in making sense of complex situations. It is used to detect, identify, and counteract cyber threats. Cognitive security enhances traditional cybersecurity measures by automating threat detection and response, providing a more adaptive and proactive defense against cyberattacks.

Simply put, cognitive security is a defense mechanism that involves rational decision-making in adversarial situations. It consists in resisting or mitigating emotional manipulation and protecting individuals, organizations, and societies to enable collective action to solve problems. Learn more about cognitive security and why it’s vital. 

Read the report: 2024 TAG CYBER Analyst Report: Narrative Attacks By Sector

Risks to Cognitive Security

There are many risks to cognitive security. Today, we face persistent social-cyber adversarial conditions and environments. There continue to be attacks against individuals, organizations, and society that are designed to confuse, delay, and degrade action. Here are some risks to cognitive security:

• Politicized and monetized information environments
• Narrative weaponization
• Person-to-group behavior manipulation
• Hacking the “human” of the human-machine team
• Manipulating human decision-making

How the Blackbird.AI Platform Addresses Narrative Attacks on National Security and Government Leaders

Key Aspects of Cognitive Security

1. Enhanced Threat Detection and Response

Cognitive security systems analyze large datasets from diverse sources to detect anomalies and potential threats. By learning from past incidents, these systems can predict and mitigate future attacks more effectively.

2. Automated Decision-Making

Cognitive security tools can autonomously decide whether to block, delete, or quarantine threats, reducing the workload on human analysts and improving response times.

3. Improved Incident Response

By significantly reducing the time required to detect and respond to threats, cognitive security minimizes the damage caused by cyber incidents. This quick response is crucial in preventing data breaches and maintaining system integrity.

4. Adaptive Learning

Unlike traditional security measures, cognitive security systems continuously learn from new data, improving their accuracy over time. This reduces false positives and helps prioritize genuine threats for remediation.

Cognitive Security Applications

Cognitive Security Systems have many applications. Learn more about what these systems do.

1. Detect Threats

The main goal of cognitive security is to reduce the burden on security analysts by supporting threat detection. Cognitive security systems can detect threats with exceptionally high accuracy. 

2. Understand the Context Behind Threats

Cognitive security systems do more than just identify threats, they can look deeper for context and characteristics of a given threat. 

3. Identify Threat Patterns

By contextualizing threats and identifying their common characteristics, cognitive security systems can find patterns, leading to threat modeling and prediction. 

4. Make Decisions

With cognitive security systems, security analysts aren’t required to evaluate every threat detected. The solutions can decide whether to block, delete, or quarantine the threat.

5. Interact With Other Machines

Cognitive security solutions may need to communicate with other machines, including software, cloud platforms, processors, and hardware components. 

Examples of Cognitive Security (COGSEC)

Cognitive security can be used in many ways to protect against cyber threats that exploit human behavior. Here are some examples of cognitive security. 

Designing online systems

Online systems and interactions can be designed to reduce vulnerability to narrative attacks created by misinformation and manipulation. 

Detecting information manipulation

Cognitive security technologies, including machine learning and AI, can be used to detect and mitigate targeted information manipulation attempts, such as those targeted at government insiders. 

Integrating cyber and social media systems

COGSEC can integrate cyber and social media systems or simulations while monitoring factors outside social media environments. 

Combating smuggling

Cognitive security technologies can look for clues that help analysts determine which containers at ports potentially hold smuggled goods. 

Benefits of Cognitive Security

Think of cognitive security as fraud and threat detection at scale. It’s the equivalent of having thousands or even millions of fraud and threat analysts working around the clock. Organizations that invest in cognitive security solutions benefit from:

Fewer False Positives

Cognitive security systems have adaptive learning capabilities that help them identify threats while processing more data. With better accuracy, false positives can be avoided. 

Less Alert Fatigue

Security analysts can experience alert fatigue, 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. They are more likely to prioritize remediation and investigate better. 

More Flexibility

While cognitive security technology is working, security analysts can focus on investigating unique incidents that don’t fit any model. 

Higher Efficiency

Human analysts can leave mundane tasks to cognitive security technology and become more efficient and effective in performing their core functions. 

Trust & Safety: Navigating Social Media Integrity in an Election Year

Importance of Cognitive Security

Cognitive security is vital for modern organizations facing sophisticated cyber threats. It combines the capabilities of AI and ML to provide a robust defense mechanism, enabling organizations to stay ahead of cybercriminals. By automating threat analysis and response, cognitive security protects sensitive data and ensures business continuity and customer trust.

Challenges and Limitations

While cognitive security offers numerous benefits, it also faces challenges like data vulnerability and task limitations. Cognitive systems require large amounts of data to learn effectively, which can be a target for cyberattacks. Additionally, these systems may struggle with tasks involving natural language understanding and object recognition in images.

How Cognitive Security and Narrative Intelligence Work Together

Cognitive Security (COGSEC) and Narrative Intelligence are integral to combating misinformation and disinformation in modern cybersecurity. COGSEC utilizes artificial intelligence (AI) and machine learning (ML) to emulate human cognitive processes, enhancing the ability to detect, identify, and respond to cyber threats. It aims to rationalize decision-making in adversarial contexts, countering emotional manipulations and protecting societal structures.

Narrative Intelligence complements this by analyzing the stories and information circulating in society. It identifies the key narratives, their origins, how they spread, and their impact on communities. This analysis helps in understanding and mitigating narrative-driven threats that exploit misinformation.

Together, COGSEC and Narrative Intelligence provide a robust defense mechanism. They help detect threat patterns, automate responses, and offer a more adaptive and proactive defense against narrative attacks that seek to manipulate public opinion and destabilize institutions. By doing so, they ensure organizations can maintain operational integrity and safeguard against the growing sophistication of cyber threats.

Forrester identifies narrative attacks as one of the top five cybersecurity threats in 2024. These AI-enabled attacks manipulate, discredit, or distort stories by exploiting cultural biases and emotions. The brand damage from such attacks can be devastating. Wrozek emphasizes that countering narrative attacks requires early warning systems through threat intelligence.

Another significant threat is deepfakes, where AI is used to create convincing fake identities that can deceive organizations into taking damaging actions. For example, a recent deepfake scam in Hong Kong led a finance clerk to transfer $25 million to fraudsters. The quality of these fakes is improving rapidly, making it increasingly difficult to differentiate between real and fake videos or audio. Deepfakes can also be used to amplify narrative attacks. The role of the CISO is crucial in focusing on threat intelligence to avoid these attacks and in enhancing incident response capabilities to address deepfakes.

Summary

Cognitive security represents a significant advancement in cybersecurity, offering enhanced protection through AI and machine learning. By continuously learning and adapting, cognitive security systems provide a proactive defense against evolving cyber threats, making them an essential component of modern cybersecurity strategies.

As the threat of misinformation and disinformation grows, the need for effective narrative risk intelligence will become more vital. Organizations that embrace these technologies early will be better positioned to protect value, safeguard financial stability, and ensure long-term competitiveness.

To learn more about how Blackbird.AI helps global organizations, book a demo here.