Cybersecurity has become a daunting effect of technologization, as it’s underrated due to its significance. Companies scarcely invest in cybersecurity measures, especially in the risk management sector, leading to massive costs after data breaches.
Still, the main issue revolves around the changing dynamics of technology. There are more internet-connected devices and applications developed now than ever, so the high competition must deliver new products faster, leading to less attention to security compared to design and improvements. Moreover, cybercriminals often look for vulnerabilities in companies’ systems because they’re easier to break.
This is what happens in centralized systems, which is why decentralization is emerging among industries. These blockchain-based networks offer enhanced security and frequently leverage Bitcoin as a store of value because transactions cannot be compromised that easily.
But until blockchain becomes more accessible, we’re still waiting for automation to become bigger and help mitigate risks. So, let’s discuss cybersecurity automation features.
AI and ML as the backbone of cybersecurity automation
Cybersecurity automation technologies would be efficient measures of protecting data and systems by automating specific processes that humans otherwise perform. Some of these advanced methods include the use of artificial intelligence and machine learning through which each organization can prioritize their cybersecurity goals through better workflow.
Cybersecurity automation has the benefits of increasing efficiency in detecting potential threats with significant accuracy and developing a proper response. At the same time, it offers continuous system monitoring at a larger scale, which helps lower operation costs.
What parts of cybersecurity can be automated?
Although it seems unusual to automate something of this importance, the truth is that cybersecurity is prone to so many human-made errors that automation is necessary to implement. Phishing is still challenging to recognize for many users, while password attacks continue as users lack better digital literacy skills.
Automation in cybersecurity can help monitor and scan for vulnerabilities 24/7 through network scanners that can detect and report issues immediately and automatically. There’s also the possibility of introducing automated compliance monitoring, which helps companies stay up to date with the latest industry regulations to avoid fines and penalties.
Finally, the automated incident response should be already used because it’s one of the most important aspects of handling a data breach. Automated planned rules to respond to incidents without the need for human intervention can save a lot of time and resources.
Cybersecurity automation tools to consider
The cybersecurity automation sector is yet to be adequately developed, but some features are more accessible to implement. For instance, security information and event management (SIEM) software can be leveraged to strengthen a company’s IT ecosystem as it enhances visibility across systems to prepare a better incident response in accordance with changing business dynamics. SIEM analyzes applications, devices, and the entire infrastructure, also being able to adhere to compliance.
Other tools include security orchestration, automation, and response (SOAR) that comprise multiple solutions handling threats, security incident responses and automating operations. Based on standard rules, these systems run automatically and independently when it comes to managing risks and forming a proper response to dangers.
Finally, additional measures that automation can achieve include the following:
Scan IT vulnerabilities and classify weaknesses to provide solutions.
Track and monitor endpoints, such as PCs and IoT devices, to protect from attacks.
Automation challenges in cybersecurity
Unfortunately, cybersecurity automation needs much more support and development to be adequately assessed. For instance, marketers, managers, and leaders lack trust in AI for making the right decision regarding securing networks. The latest AI project, ChatGPT, showed that AI can be biased and, with enough effort, make questionable decisions, deepening doubt, and fear over this technology. This issue can be tackled by spreading awareness of explainable AI.
One of the reasons why trust is scarce is given by the false positives that AI offers sometimes, leading to a loss of time and resources. It may happen for AI to flag any suspicious activity despite some being harmless. False positives must be adjusted by developing in time, so this, too, requires human tasks.
However, the skills shortages might pose a severe problem. Both AI and coding skills are necessary to mitigate AI scarcities, but hiring someone unfit for the role might increase the chances of experiencing a data breach due to human mistakes, such as misconfiguration. The right decision in this case is to grow talent from within and train employees with immense potential to become great.
These are not the only challenges, as financial concerns and stressful regulatory compliance must be kept under control.
Still, automation should be prioritized
Technology is developing at a fast pace, and the current cybersecurity measures prove to be inefficient in protecting the end user and companies’ reputation. Hence, more modern solutions should be implemented because they tackle newness.
Current automation techniques focus more on equipment and machinery, but we’re past that moment. If the industrialization period was critical in human history, we now need an automation change at a global scale to tackle all the costs and create efficient measures of operating.
Scalability is an integral part of automation because it can help meet demand regarding sources, costs, and market fluctuations, which are essential to consider for safeguarding a company. Adaptable businesses can better protect their systems and customer data because they’re prepared for changes.
At the same time, introducing automation for cybersecurity is crucial in improving accuracy and quality in the creation of products and delivery of services. That’s because all the focus on maintaining security goes toward other essential parts of the business, while AI models can keep the company’s network safe 24/7.
Final considerations
Cybersecurity automation is the future of company security, as it can leverage AI and ML models to identify potential threats. At the same time, these technologies can work together to form the best risk management response during an attack to minimize the costs and effects of a breach. However, these systems must be maintained by human staff from time to time, too, so introducing them would still require a professional outlook.
Last Updated 1 month ago
