With the increasing dependency on technology, there is an equally increasing exposure to online threats. There has been an exponential rise of data breaches and ransomware attacks in recent times that has been affecting users as well as organizations. Enterprises across the globe are being victimized by the growing threat of cyberattacks. And thus, cybersecurity has become a top-of-the mind problem for everyone. In a business world where privacy and safety of customers’ data are vital factors, organizations need to focus on a comprehensive cybersecurity architecture. And this is where AI comes under the spotlight.
AI to the rescue
There is a compelling business case for using AI in cybersecurity to bolster cybersecurity as industries worldwide begin to investigate how the technology will help them improve their operations. Cybersecurity seeks to use AI (and its close cousin, ML i.e. machine learning) to improve the speed at which they detect cyber threats.
5 ways in which AI can help to bolster Cybersecurity:
- Threat Detection
Conventional cybersecurity technology relies heavily on past results but AI and ML can learn from it to improvise the algorithms which enables to detect threats in advance in a better way.
- Vulnerability Management
Managing vulnerabilities with traditional techniques is becoming extremely difficult for organizations due to the large volume of data. This is where AI comes in and helps to proactively address vulnerabilities before they wreak too much havoc. The machine learning techniques determine with high accuracy what vulnerabilities will likely be used in an attack.
- Quick Response
AI proves its efficiency in helping organizations to respond faster to the next generation of cyberattacks. AI can process massive amounts of unstructured information and can learn patterns much more quickly. This enables a quick response time and makes it relatively easy to prevent threats.
- Secure Authentication
Conventional passwords have always been a weak link in cybersecurity. Although biometric authentication is now being used, it still isn’t enough. Thus, developers are now utilizing the power of AI to improvise on the existing biometric authentication set up to make it more robust.
- Threat Prediction
AI enables threat prediction through anomaly detection. It scans through huge amounts of data of various types to make predictions based on how the system has been trained. Any unusual pattern or anomaly in the data indicates a possible threat and is reported by the AI-based cybersecurity systems. Pre-emptive actions can then be taken based on the data to avoid attacks.
Key Benefits of AI-enabled Cybersecurity:
- Improves the accuracy and efficiency of cyber analysts: The analysts spend a substantial amount of time in going through the logs. AI takes away this burden to a great extent and enables them to spend more quality time in analyzing incidents that the algorithms identify.
- Allows organizations to respond faster to breaches: AI-driven technology can help companies to automate countermeasures to prevent being the victim of a cyberattack and fight against online threats. This time reduction is achieved by continuously scanning for known or unknown anomalies that show threat patterns.
- Lowers the cost of detecting and responding to breaches: Using AI for cybersecurity enables organizations to understand and reuse threat patterns to identify new threats. This leads to an overall reduction in time and effort to identify incidents, investigate them, and remediate threats.
Is there a flip side?
There’s no doubt that AI is extremely helpful, but there are always two sides to a coin. Cyber threats are constantly evolving. Cybercriminals can also acquire similar AI-driven tactics to launch an attack. Thus, the implemented AI-based cybersecurity solution needs to be constantly re-trained in order to keep up and specialists are required to continually update the same. The crux of the AI is its ability to learn with the data being fed into the system and the algorithm can be easily outsmarted in the absence of relevant data. Also, AI requires an unusual blend of skills. However, currently a substantial gap exists between the demand and the supply of trained cybersecurity workers.
The Future of AI in Cybersecurity
AI-use in cybersecurity systems can still be termed as nascent at the moment. Businesses need to ensure that their systems are being trained with inputs from cybersecurity experts which will make the software better at identifying true cyber-attacks with far more accuracy than traditional cybersecurity systems. In a nutshell, AI can definitely be a good first line of defence in cybersecurity solutions but one should not be overly relied on it. Organizations, with the help of cybersecurity experts, must identify where deploying an AI-enabled cybersecurity can yield maximum ROI and build a roadmap with appropriate goals accordingly.