Network security risk assessment system and method

Abstract

The invention provides a network security risk assessment system and method, and relates to the technical field of network security. The network security risk assessment system comprises a data acquisition layer, the data acquisition layer is connected with an analysis processing layer, the analysis processing layer is connected with an assessment decision-making layer, the assessment decision-making layer is connected with a display interaction layer, and the data acquisition layer acquires business scene data, network topology data, user behavior logs and social network conditions. According to the system, through highly integrated module design, 'information isolated island 'between traditional security tools is broken, comprehensive security situation awareness is realized, novel and unknown threats are dealt with by utilizing situational analysis and dynamic adjustment capability, false alarms and missing alarms are remarkably reduced, and the system is based on machine learning and behavior analysis. Intelligent priority ordering and automatic response can be realized, and the speed and accuracy of risk identification and response are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of network security, and in particular to a network security risk assessment system and method. Background Art

[0002] Cybersecurity is a method of protecting network systems and their data from attacks, damage or unauthorized access by taking technical measures, policies and systems. Its goal is to protect the confidentiality, integrity and availability of information (the CIA three elements of information security) and to ensure that all types of digital information and communication infrastructure are protected from threats and intrusions. With the widespread application of the Internet and information technology, the importance of cybersecurity is increasing, because security threats such as data theft, malware, and cyber attacks not only lead to economic losses, but also have a serious impact on the reputation and compliance of organizations. The main purpose of conducting a cybersecurity risk assessment is to identify, analyze and prioritize potential threats and vulnerabilities brought by the network environment in order to develop effective security strategies and protective measures. Risk assessment can help organizations understand the current security status, identify key assets and the risks they may suffer, and assess the severity and likelihood of risks. Through regular risk assessment, organizations can better plan resource allocation, ensure timely response when security incidents occur, and minimize the negative impact on business operations.

[0003] Existing network security technologies are mainly implemented through multi-level protection mechanisms, including firewalls, intrusion detection and prevention systems (IDS / IPS), security information and event management (SIEM) systems, anti-virus software, data encryption, access control, and vulnerability scanning. Each technology plays a role in a specific security layer. For example, firewalls are used to filter network traffic and prevent unauthorized access. IDS / IPS systems are responsible for monitoring abnormal network behavior and implementing countermeasures. SIEM systems are responsible for integrating and analyzing security logs and events from multiple channels to provide support for comprehensive security management. However, these traditional security technologies have certain deficiencies in flexibility, integration, and intelligence. Usually, these tools and systems work independently, lacking effective integration and coordination between systems, resulting in the formation of so-called information islands, and unable to achieve comprehensive and unified security situation awareness and management. Traditional security technologies also rely on predefined rules and signature libraries to identify and respond to threats. They are often powerless against new and unknown attack methods and are prone to false positives and false negatives. In addition, they are inefficient in generating reports and providing decision support. They usually take a long time to manually analyze and interpret, making it difficult to quickly respond to the dynamic needs of enterprises and the rapidly changing security situation. This relatively isolated and static protection method limits the organization's ability to quickly adjust and optimize strategies based on actual conditions, making the overall security protection effect less than ideal. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a network security risk assessment system and method, which solves the problem of low security protection effect.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a network security risk assessment system, comprising a data acquisition layer, the data acquisition layer is connected to an analysis and processing layer, the analysis and processing layer is connected to an assessment and decision layer, and the assessment and decision layer is connected to a display and interaction layer;

[0006] The data collection layer includes collecting business scenario data, network topology data, user behavior logs, and social network conditions. The analysis and processing layer includes a situational risk assessment module, a dynamic network topology analysis module, a behavior-driven priority sorting module, and a social intelligence analysis module. The display and interaction layer includes a real-time monitoring panel, an alarm and response system, and a policy adjustment interface.

[0007] Preferably, the collected business scenario data includes: the network topology data includes office mode, device access, geographic location related information nodes, routing, and device connection status information; the user behavior log includes operation log, access record, and identity authentication data; and the social network situation includes industry information and social media hot spot information.

[0008] Preferably, the situational risk assessment module triggers policy adjustments based on scenario changes, the dynamic network topology analysis module updates the network topology map and identifies potential risk nodes, the behavior-driven prioritization module analyzes user behavior and predicts high-risk behavior patterns, and the social intelligence analysis module extracts public opinion trends and threats from external data.

[0009] Preferably, the assessment decision layer dynamically adjusts risk priorities, identifies high-risk events, and generates specific countermeasure recommendations and response strategies.

[0010] Preferably, the real-time monitoring panel displays the current risk status and network topology changes, the alarm and response system pushes high-risk alarms and provides response suggestions, and the strategy adjustment interface supports users to manually or automatically adjust strategies based on analysis results.

[0011] A network security risk assessment method specifically comprises the following steps:

[0012] S1. Real-time data monitoring

[0013] First, enter the real-time monitoring panel to check the current network status, confirm that all nodes, including servers, user terminals, and network devices, are in a normal connection state, and check whether the network topology diagram shows abnormal connections. Then, check the user behavior log in real time and pay attention to abnormal access patterns. These behavior data include login frequency, sensitive data access, and geographic location changes.

[0014] S2. Data analysis and risk detection

[0015] Start or schedule automated risk assessment tasks. The contextual risk assessment module, dynamic network topology analysis module, and behavior-driven analysis module process the collected data respectively, use machine learning algorithms to identify potential threats and abnormal behaviors, automatically adjust risk scores, and automatically update the priority list of various risk events based on the latest data analysis results to ensure that high-risk events can attract attention in a timely manner;

[0016] S3. Alarm and response

[0017] When high-risk events are detected, such as abnormal traffic, abuse of permissions, and signs of network attacks, alarm notifications will be automatically sent to relevant personnel. Users can set the way to receive alarms, such as SMS, email, and internal system messages. Based on the alarm information, predefined response measures can be directly applied through the policy adjustment interface, such as isolating infected devices and blocking specific ports. If an automated response system is used, the system will take action directly according to the policy without manual intervention.

[0018] The present invention provides a network security risk assessment system and method. It has the following beneficial effects:

[0019] The present invention provides a network security risk assessment system and method. First, the system realizes a high degree of integration of various security modules, breaking the "information islands" between traditional systems, and realizes comprehensive and unified security situation awareness and management through seamless system interconnection. Secondly, based on situational analysis and dynamic adjustment, the system can adapt to changing threat situations instead of relying on static predefined rules and signature libraries. Therefore, when facing new and unknown threats, false positives and missed positives are greatly reduced. Through machine learning and behavioral analysis, the system can intelligently identify risks and automatically respond based on priorities, thereby improving response speed and accuracy. In addition, report generation and decision support are highly automated, providing real-time security visualization, helping enterprises to make data-driven decisions quickly, and adapting to changing security needs and business environments. Combined with social intelligence and external threat analysis, the system further enhances foresight and can proactively prevent potential security incidents. Therefore, the system has greatly improved flexibility, intelligence, integration and adaptability, meeting the needs of modern enterprises for efficient and secure protection in a dynamic network environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Example 1

[0023] like Figure 1 As shown, an embodiment of the present invention provides a network security risk assessment system, including a data collection layer, the data collection layer is connected to an analysis and processing layer, the analysis and processing layer is connected to an assessment decision layer, and the assessment decision layer is connected to a display interaction layer;

[0024] The data collection layer includes collecting business scenario data, network topology data, user behavior logs, and social network conditions. The analysis and processing layer includes a situational risk assessment module, a dynamic network topology analysis module, a behavior-driven priority sorting module, and a social intelligence analysis module. The display and interaction layer includes a real-time monitoring panel, an alarm and response system, and a policy adjustment interface.

[0025] The collected business scenario data includes: the network topology data includes office mode, device access, geographic location related information nodes, routing, and device connection status information; the user behavior log includes operation logs, access records, and identity authentication data; and the social network situation includes industry information and social media hot spot information.

[0026] The contextualized risk assessment module triggers policy adjustments based on scenario changes, the dynamic network topology analysis module updates the network topology map and identifies potential risk nodes, the behavior-driven prioritization module analyzes user behavior and predicts high-risk behavior patterns, and the social intelligence analysis module extracts public opinion trends and threats from external data.

[0027] The assessment decision layer dynamically adjusts risk priorities, identifies high-risk events, and generates specific countermeasure suggestions and response strategies. The real-time monitoring panel displays the current risk status and network topology changes, the alarm and response system pushes high-risk alerts and provides response suggestions, and the strategy adjustment interface supports users to manually or automatically adjust strategies based on analysis results.

[0028] Specifically, the system of the present invention can monitor and respond dynamically in real time, quickly identify potential risks, and take timely measures through automated response mechanisms, such as isolating threat devices and closing high-risk ports, significantly shortening response time and improving security. Secondly, the system integrates multi-dimensional data, including network topology, user behavior logs and social network intelligence, providing a comprehensive risk view, combined with contextual analysis, to make security assessment more accurate. In addition, the system relies on machine learning algorithms for intelligent risk assessment and prediction, and enhances the accuracy of detection through continuous learning and optimization. In addition, the system can also adaptively update risk priorities to ensure that high-risk events are handled in a timely manner. The user interface is intuitively designed, and through visualization tools such as network topology maps and risk status maps, it helps users quickly understand risk distribution and changes, and the custom policy and rule functions enable it to flexibly adapt to the specific needs of the enterprise. The system supports access to external threat intelligence platforms, such as MITREATT&CK, which enables network security operations to update risk models in real time and conduct collaborative defense. The report generation automation function provides detailed and easy-to-interpret risk reports, helping management and decision-making teams to better understand risk situations and formulate action plans. At the same time, the modular design allows the system to be expanded according to enterprise needs and seamlessly integrated with existing IT and security infrastructure, making it highly compatible. By reducing manual operations, the system not only improves operational efficiency, but also reduces false alarm rates and operation and maintenance costs, further demonstrating its value. Considering data security, the system uses SSL encryption and data desensitization measures during data processing to ensure data privacy and security, and assist in meeting the compliance requirements of GDPR regulations. The system's self-learning and self-optimization capabilities enable it to continuously analyze historical data and behavior patterns, dynamically adjust strategies to respond to emerging security threats, and provide enterprises with a reliable protection barrier.

[0029] Example 2

[0030] like Figure 1 As shown, an embodiment of the present invention provides a network security risk assessment method, which specifically includes the following steps:

[0031] S1. Real-time data monitoring

[0032] First, enter the real-time monitoring panel to check the current network status, confirm that all nodes, including servers, user terminals, and network devices, are in a normal connection state, and check whether the network topology diagram shows abnormal connections. Then, check the user behavior log in real time and pay attention to abnormal access patterns. These behavior data include login frequency, sensitive data access, and geographic location changes.

[0033] S2. Data analysis and risk detection

[0034] Start or schedule automated risk assessment tasks. The contextual risk assessment module, dynamic network topology analysis module, and behavior-driven analysis module process the collected data respectively, use machine learning algorithms to identify potential threats and abnormal behaviors, automatically adjust risk scores, and automatically update the priority list of various risk events based on the latest data analysis results to ensure that high-risk events can attract attention in a timely manner;

[0035] S3. Alarm and response

[0036] When high-risk events are detected, such as abnormal traffic, abuse of permissions, and signs of network attacks, alarm notifications will be automatically sent to relevant personnel. Users can set the way to receive alarms, such as SMS, email, and internal system messages. Based on the alarm information, predefined response measures can be directly applied through the policy adjustment interface, such as isolating infected devices and blocking specific ports. If an automated response system is used, the system will take action directly according to the policy without manual intervention.

[0037] In detail, the present invention uses Python or R language for data analysis and modeling, uses Spark or Hadoop for big data processing, and utilizes high concurrency and high performance data computing, and uses Scikit-learn and TensorFlow machine learning frameworks to build behavior analysis models.

[0038] In the evaluation decision layer, a decision engine (Drools or JRules) is used to conduct risk assessment based on the analysis results provided by different modules and give a dynamic risk level. Multi-level decision logic is defined to automatically increase the priority when high risks are analyzed based on network topology, abnormal behavior, and social network intelligence.

[0039] Utilize the preset template system to generate detailed risk assessment reports containing risk levels, key nodes, potential threats, response suggestions, etc. Provide specific response suggestions (such as isolating nodes, modifying access rights, and strengthening user verification) based on different business scenarios.

[0040] Through the integration of the automated response system SOAR platform, ensure that the system can automatically take countermeasures (close high-risk ports, block traffic). Implement a configurable response strategy library so that the system can automatically adjust the security policies of firewalls and intrusion detection systems (IDS). The rule engine and decision system use Drools or IBM ODM. The report generator uses JasperReports or BIRT. The automated response platform uses Splunk Phantom or Demisto.

[0041] The interactive display layer is a web-based visual dashboard that displays the current network topology, risk status, and abnormal behavior. Use tools such as Grafana or Kibana to display data. Update the analysis results of each module in real time, and set up graphical displays that support network node status and behavior patterns. In the alarm mechanism, when the system detects high-risk behavior or attacks, it automatically pushes real-time alarms. It can be sent via email, SMS, or system notification. Users can customize alarm thresholds, such as triggering alarms when specific patterns are detected in user behavior analysis.

[0042] A role-based permission management system allows administrators to modify security policies on the system and apply them to the network in real time. It provides a policy simulation function, allowing administrators to simulate the potential impact of changing policies on the entire network before changing them. The front-end development framework can be used to build dynamic interactive interfaces through React, Angular, or Vue.js. The back-end technology can be used to interact with the analysis engine and database through Node.js or Java. Alarm push technology can be implemented through Pushover or Twilio.

[0043] Since the amount of network security data is huge and has a high degree of real-time requirements, the system of the present invention needs to have efficient real-time processing capabilities. The system can use distributed computing frameworks such as Apache Spark or Apache Flink to ensure the real-time performance of data analysis and processing.

[0044] Since the system involves a large amount of sensitive data, such as user behavior logs and business scenario information, the security of data during collection, transmission and storage must be ensured. Technologies such as SSL encryption, data desensitization and access control can be used to ensure data security.

[0045] Coordination between modules (such as contextualized risk assessment and dynamic network topology analysis) is key to the success of the system. The modules need to be synchronized, especially in the decision-making layer, where multiple data sources and analysis results need to be integrated. This can be achieved through a microservices architecture, where each module runs independently and interacts through APIs.

[0046] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A network security risk assessment system, comprising a data collection layer, characterized in that: The data collection layer is connected to the analysis and processing layer, the analysis and processing layer is connected to the evaluation and decision-making layer, and the evaluation and decision-making layer is connected to the display and interaction layer; The data collection layer includes collecting business scenario data, network topology data, user behavior logs, and social network conditions. The analysis and processing layer includes a situational risk assessment module, a dynamic network topology analysis module, a behavior-driven priority sorting module, and a social intelligence analysis module. The display and interaction layer includes a real-time monitoring panel, an alarm and response system, and a policy adjustment interface.

2. A network security risk assessment system according to claim 1, characterized in that: The collected business scenario data includes: the network topology data includes office mode, device access, geographic location related information nodes, routing, and device connection status information; the user behavior log includes operation logs, access records, and identity authentication data; and the social network situation includes industry information and social media hot spot information.

3. A network security risk assessment system according to claim 1, characterized in that: The contextualized risk assessment module triggers policy adjustments based on scenario changes, the dynamic network topology analysis module updates the network topology map and identifies potential risk nodes, the behavior-driven prioritization module analyzes user behavior and predicts high-risk behavior patterns, and the social intelligence analysis module extracts public opinion trends and threats from external data.

4. A network security risk assessment system according to claim 1, characterized in that: The assessment decision layer dynamically adjusts risk priorities, identifies high-risk events, and generates specific countermeasure recommendations and response strategies.

5. A network security risk assessment system according to claim 1, characterized in that: The real-time monitoring panel displays the current risk status and network topology changes, the alarm and response system pushes high-risk alerts and provides response suggestions, and the strategy adjustment interface supports users to manually or automatically adjust strategies based on analysis results.

6. A network security risk assessment method according to any one of claims 1 to 5, characterized in that: The specific steps include: S1. Real-time data monitoring First, enter the real-time monitoring panel to check the current network status, confirm that all nodes, including servers, user terminals, and network devices, are in a normal connection state, and check whether the network topology diagram shows abnormal connections. Then, check the user behavior log in real time and pay attention to abnormal access patterns. These behavior data include login frequency, sensitive data access, and geographic location changes. S2. Data analysis and risk detection Start or schedule automated risk assessment tasks. The contextual risk assessment module, dynamic network topology analysis module, and behavior-driven analysis module process the collected data respectively, use machine learning algorithms to identify potential threats and abnormal behaviors, automatically adjust risk scores, and automatically update the priority list of various risk events based on the latest data analysis results to ensure that high-risk events can attract attention in a timely manner; S3. Alarm and response When high-risk events are detected, such as abnormal traffic, abuse of permissions, and signs of network attacks, alarm notifications will be automatically sent to relevant personnel. Users can set the way to receive alarms, such as SMS, email, and internal system messages. Based on the alarm information, predefined response measures can be directly applied through the policy adjustment interface, such as isolating infected devices and blocking specific ports. If an automated response system is used, the system will take action directly according to the policy without manual intervention.

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