Thanks to modern artificial intelligence training algorithms, neural networks are considered a safe technology. They are applied in fields such as medicine, finance, security, and others, which will be discussed in this article.
Why Neural Networks Are Safe
It is impossible to externally intervene in the training of a neural network. They undergo several years of training.
Reasons for the safety of neural networks:
- Presence of reliability verification algorithms.
- Neural networks are trained on correct databases with information validated by research.
- Experienced developers with 5-10 years of experience and solid portfolios are involved in the development of well-known neural networks.
- Neural networks are regularly checked for data leaks and protection.
They are also protected against DoS and DDoS attacks, yet full security cannot be guaranteed.
One cannot provide a 100 percent guarantee for the reliability of a neural network. However, for internet users, artificial intelligence does not pose a danger.
Where Neural Networks Are Used
The technology is used in robotics, industry, text processing, mathematical data, analytical processing of incoming information, and generating responses based on results.
There are many more fields where artificial intelligence can be applied. The technology is also being introduced into other areas of life, such as:
- For diagnosing diseases, analyzing medical indicators, images, automatic calculation of insurance costs based on medical data, and predicting treatment outcomes.
- For predicting and regulating traffic. Neural networks are integrated into traffic management systems and also used in analyzing data from logistical systems to optimize delivery routes.
- In finance, artificial intelligence is required for market forecasting, fraud detection, creating virtual assistants (automating business processes).
- On the internet, it is used for recommending products in online stores, automatic translation of texts into other languages, analyzing the sentiment of textual reviews on products and services, and analyzing text messages to identify thematic groups, automatic creation, and optimization of advertising campaigns.
Technology’s application is even found in music, gaming, sports, and art.
Neural Networks in Information Security
The technology automates processes of analysis, threat detection, and also detecting anomalies in the behavior of security systems and users. Therefore, neural networks are used in information security.
For example: intrusion detection systems (IDS) or user authentication.
The former technology is trained based on data about the normal behavior of a user and system and compares it with the current one. It is designed to detect anomalies in real-time, facilitating response to threats and preventing potential attacks.
A user identification system is trained based on specific user actions, such as login time, applications used, geolocation, and device characteristics. It verifies the authenticity of logins based on this data. It might suspect a login by another person or a hack and will subsequently request additional verifications.
The analysis of internet user and system logs is also conducted using artificial intelligence. This reveals hidden threats and issues in the device’s operation, often unidentifiable through manual analysis.
The use of neural networks in information security has already increased the speed of threat detection by 67%. However, they are not a “magic pill” and should be used alongside other security methods.
Neural Networks in Economic Security
In this domain, they analyze financial data, detect fraud, and predict economic crises. Protecting against potential threats relating to monetary transactions also rests on the shoulders of artificial intelligence.
The implementation of neural networks in the economy has reduced the risk of operations by 2-3 times and also increased the speed of operations by 81%.
A shortage of programmers skilled in working with financial neural networks remains a pressing problem. The work of developers who work with artificial intelligence in the banking sector is paid more highly than in other areas.
Neural Networks in Security Systems
Analyzing video footage from surveillance cameras helps to identify suspicious objects and individuals, facilitating the work of law enforcement in various countries. For example, the technology is highly demanded in South Korea and the UAE.
Monitoring fire hazards using smoke and heat detection systems is another area. Artificial intelligence identifies the risk of ignition and sends requests to emergency services. Neural networks in fire safety may independently activate fire extinguishing systems, depending on the level of danger.
In industry, safety is monitored using surveillance systems and by analyzing the behavior of workers.
In ensuring state security, neural networks are applied to control access to information and resources in government institutions, using, for example, password systems and encryption.
Artificial intelligence is actively used in everyday life. The safety of the world largely depends on its proper functioning. Leading countries are already employing it in state institutions, protection systems, and beyond. However, the full potential of neural networks is still to be explored.
