Revolution on the Internet of Things: New IDS protects against cyber attacks!

Revolution on the Internet of Things: New IDS protects against cyber attacks!

In today's, digitized world in which everything is networked, cyber security and the protection of our systems play a crucial role. A new approach is the development of a lightweight decision-and-old intrusion detection system (IDS) for IoT networks, which aims to recognize real threats in real time and to ensure a high level of operating efficiency. Nature reports on a system that is specially designed for environments with low complexity and minimal system effort.

The heart of this system is a decision tree that is known for its hardware efficiency and comprehensibility. This means that compared to more complex models, such as deep neuronal networks, it requires much less computing and storage. This has the advantage that the performance of the IoT devices is not affected, while the system classifies threats quickly and precisely.

Security on the Internet of Things

The background for these developments is more than just a technical nature: The Internet of Things (IoT) has proven indispensable in many industries, but also entails considerable security risks. According to pmc, intrusion detection systems are crucial for the protection of these vulnerable ecosystems. A new model that stands out as particularly interesting here is the Deep Neural Decision Forest-Based IDS (DNDF-IDS) that combines elements from decision-making tree models and neural networks. This leads to an improvement in accuracy and recognition of network anomalies.

The evaluation of this model takes place on several data records and shows impressive accuracy of between 94.09% and 98.84%. The forecast time is extremely short, with only 0.1 ms per data record. So it is no wonder that these new technologies are becoming increasingly attractive! They manage to make efficient predictions with a lower number of characteristics, which at the same time saves resources.

optimization strategies and functions

A central point in the development of the lightweight IDS is the use of various optimization strategies . Among other things, the system uses methods such as the Pruning of features to accelerate processing and reduce complexity. In addition, techniques such as Leaf-cut optimization are used to eliminate unnecessary branches and minimize the depth of the decision-making tree.

The cloud-edge integration of the system is particularly exciting. This enables continuous adjustments to new threats from cloud databases that store important information on attack patterns. With the implementation of secure transmission protocols such as MQTT, it is ensured that the data will flow safely between the devices.