5 results about "Port scan" patented technology

This invention proposes an intelligent method for detecting abnormal network behavior, including acquiring target network traffic data, constructing a multi-dimensional feature fusion model based on an attention mechanism, and building an abnormal behavior classification model based on deep learning. By automatically allocating attention to different network traffic features through the attention mechanism, it solves the problems of unreasonable feature weight allocation and insufficient feature fusion in traditional methods, significantly improving the detection capability for low-frequency and covert abnormal behaviors and effectively reducing false positive and false negative rates. The classification model employs a hybrid CNN and LSTM structure, taking into account both the local spatial and temporal features of network traffic, and can accurately identify various types of abnormal network behaviors such as DDoS attacks, port scanning, SQL injection, and malicious code propagation, adapting to diverse attack scenarios with high classification accuracy.

Embodiments of the present application provide a port scanning method and device, electronic equipment and storage medium. The port scanning method comprises: sending a port scanning task request to a scheduling node; receiving task element information and task actual parameters fed back by the scheduling node, wherein the scheduling node has previously constructed an LFSR based on a plurality of scanning targets in scanning information, a plurality of pseudo-random sequences generated by the LFSR have a one-to-one mapping relationship with the plurality of scanning targets, the task element information is used to restore the LFSR, and the task actual parameters include a current state of the LFSR; determining a scanning target set based on the task element information and the task actual parameters, the scanning target set comprising at least one scanning target. Embodiments of the present application can improve the randomness of the distribution of an Internet port scanning task, reduce the risk of scanning behavior being intercepted, and also improve the calculation and transmission efficiency of scanning targets, having the advantage of high execution efficiency of port scanning.

The application discloses a port scanning detection method and system, an electronic device and a storage medium. The method comprises the following steps: loading an eBPF program and creating a first eBPF Map for storing a whitelist; hooking a first eBPF program related to a first kernel function of port listening, dynamically constructing the whitelist during port listening; hooking a second eBPF program related to a second kernel function of network connection establishment, extracting a destination port number and querying the whitelist when receiving a network connection request; if the query is not hit, determining an abnormal scanning event, and collecting connection information and reporting to the user state. The application can detect port scanning behavior in real time and accurately in the kernel state with low performance overhead, and the detection mechanism is difficult to bypass, solving the problems of poor real-time performance, high performance overhead and easy bypassing in the prior art.

Systems, computer program products, and methods are described herein for determining readiness for managed runtime application program interface (API) applications via artificial intelligence. The present disclosure is configured to scan a set of API applications and their associated custom port hosted within a managed runtime environment using a custom port probe embedded within the managed runtime environment, where the custom port probe is operably coupled to a load balancer, where user traffic within the managed runtime environment is processed by the set of API applications and the custom port; initialize a set of components within the custom port for operation; verify readiness of the set of API application and the custom port probe using an artificial intelligence system; and transmit a notification to the load balancer indicating readiness of the set of API applications.