Generative AI

The impact of Generative AI on cybersecurity

In a fast-moving digital world, it is impossible for humans to manually detect and handle cyber threats. The volume and complexity of threats have generated a demand for an intelligent system that not only detects and neutralises threats but also learns, adapts, and grows. This is where Generative AI (Gen AI) saves the day for cybersecurity.

According to a survey by a leading management consulting firm, 40% of organisations plan to increase their investment in the advancements of Gen AI, including cybersecurity. This article explores the benefits and challenges of Gen AI in cybersecurity and ways organisations can prepare themselves.

Gen AI in cybersecurity

Gen AI can learn from patterns within cyber threats and adapt to enhance security. It can parse the security documentation quickly, thus enabling analysts to run queries on their security tools. Using the learnings of historical events, Gen AI can predict future threats and vulnerabilities before they arise. Let us understand the benefits in greater detail.

Benefits and challenges of Gen AI in cybersecurity

From greater efficiency to proactiveness, Gen AI has several benefits for security analysts and organisations wanting to protect their assets –

Greater efficiency

With Gen AI, you can significantly improve threat detection and response time. As the Gen AI system learns from historical data, it helps security analysts make quick decisions, accelerating workflows and team output.

Detailed analysis

Gen AI can ingest and analyse data from several sources, such as emails, documents, storage drives, cloud, chat history, and more. This helps security analysts be on top of data analysis with speed and accuracy. Gen AI can create threat, incident, and resolution summaries in natural language, making it easy for the team to understand.

Proactive threat detection

The shift from reactive to proactive threat detection is perhaps the most important application of Gen AI in cybersecurity. Security analyst teams can take proactive actions before the threat can cause any damage.

Like any other technology, Gen AI comes with some challenges that your service provider must deal with responsibly. The challenges are –

Protection from cyber criminals using Gen AI

As more Gen AI tools become openly accessible at a low cost, cybercriminals can use them to build and execute sophisticated attacks that can bypass existing security measures of an organisation. With new GPT-based Gen AI tools, the entry barrier for miscreants is low.

Ethical use of Gen AI

Gen AI models use vast historical and model data to train themselves. The system must consider data access control and privacy considerations regarding the training datasets.

Resources for computation

Smaller organisations can find it challenging to implement Gen AI due to its high computational power and storage requirements.

This is where the role of a trusted and experienced service provider becomes crucial. They will not only have the necessary technology resources but also know the current security and ethical concerns to take care of.

Ways how Gen AI is boosting cybersecurity

Gen AI is becoming increasingly accessible and positively impacting organisations. Several ways it is boosting cybersecurity are –

Supporting short-staffed security teams

93% of IT executives are using Gen AI to augment their security capabilities, especially the Tier 1 threats, false positives, and zero-day attacks. Gen AI helps them allocate resources and manage capacity better.

Real-time threat detection

Gen AI uses identity patterns and anomalies to quickly filter potential incidents and reject the noise. It speeds up an organisation’s ability to respond to cyberattacks.

Achieving a higher threat intelligence

Gen AI is replacing the need for complex query-based languages, reverse engineering, and operations to analyse vast data and isolate threats. It provides rich insights to security analysts through higher threat intelligence.

Automating security patches

Gen AI uses neural networks to scan the code, detect vulnerabilities, and suggest patches using NLP to the team of security analysts.

Better incident response

Security analysts do not depend on manual cyberattack responses. Gen AI isolates the most effective response strategies to accelerate incidence response and create reports for analysis.