Secure your digital future: how AI puts data security to the next level

Data is new or digital era. Consequently, cybersecurity is becoming more and more important for companies. Artificial intelligence (AI) plays a central role in this context because it offers proactive and reactive solutions. The cybersecurity tools supported by AI analyze enormous amounts of data at the speed of light and recognize the potential models and risks that human employees often neglect. The use of AI simplifies not only the detection of security risks, but also considerably shortens the response time, which considerably increases the safety of your systems.

Conventional approaches in cybersecurity are mainly based on the recognition of threats which are already known. This is made by signatures if called – clear models that indicate certain viruses, malware or other cyber attacks. These signatures are stored in databases, and if a threat is discovered, it is compared to these known models.

The drawback is that these traditional methods can only follow well -known threats. New or unknown attacks for which no signature can remain slightly not detected by such approaches. The AI, on the other hand, also recognizes the new and unknown threats to the recognition of models and automatic learning without the necessary information.

Data leaks may have massive consequences – financial loss to damage the company's call. Fortunately, AI also offers solutions here. Thanks to highly developed technologies and the use of various tools, it prevents data leaks and ensures a robust defense.

According to an IBM report from 2023, the average costs of a data leak is around $ 4.45 million worldwide. A leading incident is the loss of Equifax data in 2017, in which more than 147 million customer data were stolen. In order to better protect our data, for example, natural language processing (PNL) can be used to automatically identify and protect sensitive information such as credit card numbers or personal data in emails or documents before being accidentally released.

Imagine that you could predict cyber attacks – this would increase your safety strategy to a completely new level! AI uses analytical predictions to determine the probability of potential attacks. Past data is analyzed to recognize models and predict future risks. Threats are proactively distant before becoming serious security risks.

Financial service provider JPMorgan Chase prevented an attack using AI and analytical forecasts in 2020 by recognizing unusual registration attempts in their networks.

Automatic learning algorithms act as digital detection dogs that constantly follow anomalies as well as unusual models and behaviors. Over time and growing experience, these algorithms become more and more precise and intelligent, which allows early detection and a defense against dangers.

Examples of this are, for example, automatic detection of phishing attacks. Automatic learning algorithms are used to automatically block harmful emails.

AI can observe and analyze user behavior in real time. As soon as the normal behavior is established, AI recognizes any gap which could be a potential security risk. This allows you to take immediate measures to avoid data loss and protect your digital resources. Behavioral analysis can be used, for example, to analyze user activities in real time. When an employee suddenly accesss a business network from a whole new location, the system acquires an alarm.

From 2021, this technology proved to be extremely useful for a leading company in the financial sector. Thanks to a behavioral analysis supported by AI, the company was able to prevent an attack on its internal systems, in which the pirates tried to abuse access data by imitating the normal behavior of an employee.

Looking towards the future is speculative, but one thing is certain: the role of AI in cybersecurity will continue to grow. Here are some exciting forecasts on the influence of AI on security protocols:

The more AI and automatic learning technologies progress, the more faster the detection of threats becomes. AI systems will be able to predict and neutralize the dangers before being able to do damage. Your business will always be one step ahead of cybercriminals.

Imagine that AI would automatically manage security incidents and without human intervention. Your response times would be considerably shortened and you could ensure coherent and reliable risk management.

Network that can repair the attack yourself – without any human intervention? With the rapid development of AI and autonomous systems, this concept becomes a reality. A current Darpa research project (Defense Advanced Research Projects Agency) called “resilient networking protocols” examines how networks can be repaired and restored in real time. These self-eating networks use automatic learning and autonomous systems to identify attacks and limit damage. You can rebuild lost data by finding alternative routes without the need for human intervention.

AI will allow the development of the ability to learn security measures that adapt to the current threat situation in real time. This dynamic approach guarantees that your defense mechanisms always have one step ahead of cybercriminals.

Mayo Clinic Ki already uses dynamically to adapt its cybersecurity measures. Your systems analyze the current situation of threats and adapt the security protocols in real time to react to new threats. This is particularly important because hospitals are increasingly targeting cyber attacks, in particular during the scanning of health data.