Conference information security supervision method and system based on cloud computing

Abstract

The invention discloses a conference information security supervision method and system based on cloud computing, and relates to the technical field of network security, and the method comprises the following steps: conference information security demand analysis; designing a security policy and constructing a model; security management of the conference information life cycle; security threat monitoring and early warning based on artificial intelligence; intelligent implementation of conference information access control is realized; a security mechanism of multi-party cooperation and data sharing; performing virtualization security isolation in the cloud environment; security protection in the conference information transmission process; and auditing and tracing conference information access behaviors. According to the conference information security supervision method and system based on cloud computing, more comprehensive and flexible security supervision can be provided for conference information in a cloud environment by combining technologies of behavior analysis, virtualization security isolation, dynamic access control and the like through a multi-level security protection means based on cloud computing. Through behavior analysis and risk assessment, the user access authority is adjusted in real time, and the access authority of the conference information is accurately controlled.

Description

Technical Field

[0001] The present invention relates to the field of network security technology, and in particular to a conference information security supervision method and system based on cloud computing. Background Art

[0002] With the rapid development of cloud computing technology, more and more organizations and enterprises are migrating their meeting information, data storage, and business processing to cloud platforms. While this transformation has greatly improved resource utilization and flexibility, it also poses significant security risks, particularly regarding the protection of meeting information. Meeting information in cloud computing environments is typically stored in virtual machines or containers, and resource sharing in multi-tenant environments can easily lead to data leaks, malicious tampering, and unauthorized access.

[0003] Most traditional methods for managing conference information security currently rely on basic security measures, such as data encryption, access control, and simple identity authentication. However, with the increasing complexity of conference scenarios and the elastic expansion of cloud platforms, these traditional security models are no longer able to effectively address the multi-layered and multi-dimensional security challenges. For example, role-based access control (RBAC) no longer meets the needs of complex cloud environments and cannot dynamically respond to changes in user behavior. Traditional encryption methods fail to consider the encryption and isolation of data within virtual machines, leading to potential security vulnerabilities. The security isolation measures between virtual machines and containers are also relatively weak, making them vulnerable to "neighbor attacks" or virtual machine escape threats.

[0004] Furthermore, most current security monitoring methods lack the integration of sensitivity analysis, real-time behavior monitoring, and intelligent response for meeting information within cloud platforms. This results in the system being unable to quickly identify and respond to abnormal behavior when security threats arise, increasing the risk of data leakage and business interruption. To address these shortcomings, it is crucial to develop a more intelligent, dynamic, and refined approach to meeting information security monitoring. Summary of the Invention

[0005] In view of the deficiencies in the prior art, the present invention provides a conference information security supervision method and system based on cloud computing to solve the problems raised in the above background technology.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for conference information security supervision based on cloud computing, comprising the following steps:

[0007] S1. Conference information security needs analysis;

[0008] In a cloud computing environment, first conduct a comprehensive analysis of the needs for conference information security;

[0009] S2, security strategy design and model construction;

[0010] After demand analysis, design conference information security strategies suitable for cloud computing platforms, including data encryption, identity authentication, permission control, and access auditing.

[0011] S3. Security management of conference information life cycle;

[0012] Bring the entire lifecycle of conference information under regulatory oversight, and implement targeted security measures for each lifecycle stage;

[0013] S4. Security threat monitoring and early warning based on artificial intelligence;

[0014] Use artificial intelligence (AI) technology to conduct real-time monitoring and early warning of security threats in cloud computing environments;

[0015] S5. Intelligent implementation of conference information access control;

[0016] Design a dynamic access control model based on behavioral analysis. By analyzing the user's historical behavior and preferences, the model dynamically adjusts the user's permissions and immediately revokes access rights when abnormal behavior occurs.

[0017] S6, security mechanism for multi-party collaboration and data sharing;

[0018] In a cloud computing environment, encrypted sharing methods are used to ensure data security during transmission and storage. Blockchain technology is used to verify data integrity. Through a decentralized approach, shared data cannot be tampered with, thereby improving the transparency and security of data sharing.

[0019] S7, virtualization security isolation in cloud environments;

[0020] By encrypting data within virtual machines, strengthening network isolation between virtual machines, and implementing strict virtual machine monitoring and auditing, the security of virtual machine images and container images is strengthened to prevent the injection of malicious code and illegal access;

[0021] S8. Security protection during the transmission of conference information;

[0022] Strengthen encryption measures during the transmission of conference information and use strong encryption protocols such as TLS and IPsec to encrypt all transmitted conference information;

[0023] S9. Audit and traceability of conference information access behavior;

[0024] Audit and trace the access and operation of conference information, deploy a comprehensive logging system in the cloud computing platform, and record all user operations.

[0025] To further optimize this technical solution, in step S1, the characteristics of the cloud computing platform are combined with the impact of virtualization and distributed storage factors on security of conference information, and the sensitivity level of conference information types such as text, audio, video, and documents, as well as the access requirements of users with different permissions to these information, are analyzed;

[0026] The analysis also includes various potential security threats and risks, such as data leakage, illegal access, information tampering, and malware attacks. By defining detailed security goals, comprehensive supervision of subsequent regulatory strategies is ensured.

[0027] To further optimize this technical solution, in step S2, an access control policy is designed in a cloud-based multi-tenant environment to ensure that only authorized users can access and operate specific meeting information through a policy model;

[0028] The policy design selects appropriate encryption algorithms such as AES-256, identity authentication mechanisms such as multi-factor authentication, and log auditing solutions.

[0029] To further optimize this technical solution, the strategy model includes the following processes when being constructed:

[0030] Permission control and dynamic authorization mechanism;

[0031] Meeting information sensitivity assessment model;

[0032] User behavior analysis and real-time risk assessment;

[0033] Encrypted management and conference information transmission security.

[0034] To further optimize this technical solution, in step S4, a machine learning model is used to dynamically analyze access logs, data traffic, and user behavior within the cloud computing platform to promptly identify potential security threats, such as abnormal logins, unauthorized access, and large-scale data downloads.

[0035] Based on the results of data analysis, security warnings are automatically generated to remind administrators to conduct further investigations. Based on historical data training, the detection capabilities are gradually improved, enabling the system to identify more complex and hidden security attacks.

[0036] To further optimize this technical solution, in step S5, the dynamic access control model based on behavior analysis includes:

[0037] User Behavior Analysis (UBA);

[0038] Meeting Information Sensitivity Score (ISS);

[0039] Contextual Environment Score (CES);

[0040] Real-time risk assessment and dynamic adjustment (RDA);

[0041] The model dynamically adjusts access permissions by comprehensively considering user behavior, meeting information sensitivity and contextual environment.

[0042] To further optimize this technical solution, in step S7, virtualization security isolation includes:

[0043] Internal VM encryption: Encrypts sensitive data in VM memory, storage, and swap files. Even if the VM administrator or attacker has access to the VM's file system or memory data, they cannot read the encrypted information.

[0044] Inter-VM network isolation: By implementing strict access control and network isolation at the virtual network level, traffic between different VMs is effectively managed to prevent improper access and data leakage.

[0045] Virtual machine security monitoring and auditing: Through the monitoring and auditing mechanism at the virtual machine layer, virtual machine activities such as access requests and data transmission are detected in real time. When anomalies occur, alarms are immediately issued and corresponding measures are taken.

[0046] To further optimize this technical solution, in step S8, when sensitive data is involved, the transmission link is end-to-end encrypted;

[0047] Monitor network traffic in real time and respond immediately when abnormal traffic is detected to prevent security incidents such as data leaks or DDoS attacks.

[0048] Further optimizing this technical solution, in step S9, the recorded user operations include viewing, editing, sharing, and downloading of conference information;

[0049] The recorded logs include timestamp, operation type, operation content, and user identity information. At the same time, log data is stored in encrypted form to prevent tampering or deletion. Through auditing and tracing, potential security issues can be discovered and timely measures can be taken to address them.

[0050] A cloud computing-based conference information security supervision system is constructed based on the above-mentioned cloud computing-based conference information security supervision method, including:

[0051] User behavior analysis and dynamic access control module;

[0052] Conference information encryption and virtual machine security isolation module;

[0053] Network isolation and traffic monitoring module;

[0054] Virtual machine monitoring and auditing module;

[0055] Sensitive information detection and protection module;

[0056] Identity authentication and access control module;

[0057] Emergency response and incident handling module.

[0058] Compared with the existing technology, the present invention provides a conference information security supervision method and system based on cloud computing, which has the following beneficial effects:

[0059] This cloud-based conference information security monitoring method and system utilizes multi-layered cloud computing security protections, combined with behavioral analysis, virtualized security isolation, and dynamic access control technologies, to provide more comprehensive and flexible security monitoring for conference information in cloud environments. Through dynamic behavioral analysis and risk assessment, the system adjusts user access rights in real time, precisely controlling access to conference information and ensuring that only authorized users can access sensitive data within the appropriate timeframe. Furthermore, internal virtual machine data encryption and virtualized isolation ensure high data security during storage and processing, preventing data leakage and unauthorized access. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 This is a flow chart of a method for conference information security supervision based on cloud computing proposed by the present invention;

[0061] Figure 2 This is a flow chart of a policy model in a cloud computing-based conference information security supervision method proposed by the present invention;

[0062] Figure 3 This is a flow chart of a dynamic access control model in a cloud computing-based conference information security supervision method proposed by the present invention;

[0063] Figure 4 This is a structural diagram of a cloud computing-based conference information security supervision system proposed by the present invention. DETAILED DESCRIPTION

[0064] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described 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 making creative efforts are within the scope of protection of the present invention.

[0065] Example 1:

[0066] See also Figure 1-Figure 3 , a conference information security supervision method based on cloud computing, comprising the following steps:

[0067] S1. Conference Information Security Requirements Analysis

[0068] In a cloud computing environment, a comprehensive analysis of conference information security requirements must be conducted first, which involves not only the confidentiality, integrity, and availability requirements of conference information.

[0069] In this embodiment, in step S1, the characteristics of the cloud computing platform are taken into consideration, and the impact of virtualization and distributed storage on security is considered. The types of conference information, such as text, audio, video, and document, are analyzed, along with the sensitivity levels and access requirements of users with different permissions to these information.

[0070] The analysis also includes various potential security threats and risks, such as data leakage, illegal access, information tampering, and malware attacks. By defining detailed security goals, comprehensive supervision of subsequent regulatory strategies is ensured.

[0071] S2. Security strategy design and model construction

[0072] After demand analysis, a conference information security strategy suitable for the cloud computing platform is designed, including multi-faceted security measures such as data encryption, identity authentication, permission control, and access auditing.

[0073] In this embodiment, in step S2, an access control policy is designed in a cloud-based multi-tenant environment to ensure that only authorized users can access and operate specific meeting information through a policy model;

[0074] The policy design should select appropriate encryption algorithms such as AES-256, identity authentication mechanisms such as multi-factor authentication, and log audit solutions. The designed security policy should be both flexible and scalable to cope with conference scenarios of different sizes.

[0075] Furthermore, when constructing the policy model, the following processes are included:

[0076] Permission control and dynamic authorization mechanism;

[0077] Meeting information sensitivity assessment model;

[0078] User behavior analysis and real-time risk assessment;

[0079] Encrypted management and conference information transmission security.

[0080] S3. Security management of conference information lifecycle

[0081] The entire lifecycle of conference information is regulated, from its creation, storage, and transmission to its final destruction or archiving. Every link could pose a security risk. Targeted security measures are implemented for each lifecycle stage.

[0082] In this embodiment, security measures include encrypted storage, data backup, transmission encryption (e.g., TLS / SSL), and ensuring complete data deletion upon destruction. The core purpose of these measures is to ensure that conference information is not leaked, lost, or tampered with at any stage. In particular, when conference information is stored on multiple cloud nodes or in different geographical regions, data distribution and redundancy security must be considered.

[0083] S4. Security threat monitoring and early warning based on artificial intelligence

[0084] Use artificial intelligence (AI) technology to conduct real-time monitoring and early warning of security threats in cloud computing environments.

[0085] In this embodiment, in step S4, a machine learning model is used to dynamically analyze access logs, data traffic, and user behavior within the cloud computing platform to promptly identify potential security threats, such as abnormal logins, unauthorized access, and large-scale data downloads.

[0086] Based on the results of data analysis, security warnings are automatically generated to remind administrators to conduct further investigations. Based on historical data training, the detection capabilities are gradually improved, enabling the system to identify more complex and hidden security attacks.

[0087] S5. Intelligent implementation of conference information access control

[0088] With the development of cloud computing technology, traditional role-based access control (RBAC) is increasingly unable to meet the security requirements of complex conference information. A dynamic access control model based on behavioral analysis analyzes user history and preferences, dynamically adjusts user permissions, and instantly revokes access rights when abnormal behavior occurs. Furthermore, the system incorporates the sensitivity of conference information and time constraints to implement fine-grained access control, ensuring that only the right users have access to the right information at the right time, thereby reducing security risks.

[0089] In this embodiment, in step S5, the dynamic access control model based on behavior analysis includes:

[0090] User Behavior Analysis (UBA);

[0091] Meeting Information Sensitivity Score (ISS);

[0092] Contextual Environment Score (CES);

[0093] Real-time risk assessment and dynamic adjustment (RDA);

[0094] The model dynamically adjusts access permissions by comprehensively considering user behavior, meeting information sensitivity and contextual environment.

[0095] S6. Security mechanism for multi-party collaboration and data sharing

[0096] In a cloud computing environment, an encrypted sharing method is adopted to ensure the security of data during transmission and storage, and blockchain technology is used to verify the integrity of data. Through a decentralized approach, it is ensured that shared data cannot be tampered with, thereby improving the transparency and security of data sharing.

[0097] In this embodiment, in a cloud computing environment, conference information often involves multiple participants, and information sharing and collaboration are commonplace. However, data sharing between different parties can lead to the risk of data leakage or misuse. A secure data sharing mechanism, using encrypted sharing methods, is designed to ensure that during multi-party collaboration, each participant can only access the data they are authorized to view.

[0098] S7. Virtualization security isolation in cloud environments

[0099] Virtualization technology in cloud computing environments provides flexibility and efficiency, but it also introduces security risks. In cloud platforms, meeting information may be stored and processed in different virtual machines and containers. Therefore, ensuring secure isolation between virtual machines is crucial to prevent risks such as "neighbor attacks" and virtual machine escape. To achieve this, we encrypt data within virtual machines, strengthen network isolation between virtual machines, and implement strict virtual machine monitoring and auditing, strengthening the security of virtual machine and container images to prevent malicious code insertion and unauthorized access.

[0100] In this embodiment, in step S7, virtualization security isolation includes:

[0101] Internal VM encryption: Encrypts sensitive data in VM memory, storage, and swap files. Even if the VM administrator or attacker has access to the VM's file system or memory data, they cannot read the encrypted information.

[0102] Inter-VM network isolation: By implementing strict access control and network isolation at the virtual network level, traffic between different VMs is effectively managed to prevent improper access and data leakage.

[0103] Virtual machine security monitoring and auditing: Through the monitoring and auditing mechanism at the virtual machine layer, virtual machine activities such as access requests and data transmission are detected in real time. When anomalies occur, alarms are immediately issued and corresponding measures are taken.

[0104] S8. Security protection during the transmission of conference information

[0105] In cloud computing environments, conference information is typically transmitted over the network, a vulnerable link in information security. Therefore, encryption must be strengthened during the transmission of conference information to prevent it from being stolen or tampered with. This is done by using strong encryption protocols such as TLS and IPsec to encrypt all transmitted conference information.

[0106] In this embodiment, in step S8, when sensitive data is involved, the transmission link is end-to-end encrypted;

[0107] Monitor network traffic in real time and respond immediately when abnormal traffic is detected to prevent security incidents such as data leaks or DDoS attacks.

[0108] S9. Audit and tracing of conference information access behavior

[0109] Audit and trace the access and operation of conference information, deploy a comprehensive logging system in the cloud computing platform, and record all user operations.

[0110] In this embodiment, in step S9, the recorded user operations include viewing, editing, sharing, and downloading of conference information;

[0111] The recorded logs include timestamp, operation type, operation content, and user identity information. At the same time, log data is stored in encrypted form to prevent tampering or deletion. Through auditing and tracing, potential security issues can be discovered and timely measures can be taken to address them.

[0112] Example 2:

[0113] See also Figure 2 In step S2, when constructing the policy model, the following process is further included:

[0114] Permission control and dynamic authorization mechanism:

[0115] Role-based access control (RBAC) is combined with attribute-based access control (ABAC) to expand and add dynamic attribute adjustment, so that access control of conference information is not only based on the user's role, but can also be dynamically adjusted according to the current user's behavior and environmental context.

[0116] In dynamic authorization control, we calculate user access rights based on the following formula:

[0117]

[0118] in,

[0119] It is the user's access rights to conference information. A larger value indicates a higher level of access rights.

[0120] Represents a user role (such as moderator, participant, observer, etc.).

[0121] Represents user attributes (such as organization, access history, authentication level, etc.).

[0122] Represents the environmental context (such as the user's current geographic location, time, etc.).

[0123] Represents the user's behavior history (such as whether there are any abnormal behavior records).

[0124] Represents the sensitivity score of the meeting information, with higher values ​​indicating more sensitive information.

[0125] Users' access rights are not just based on fixed roles, but are adjusted based on real-time context and behavior, ensuring dynamic and real-time access control.

[0126] Meeting information sensitivity assessment model:

[0127] Design a meeting information sensitivity scoring (ISS) mechanism to assign a sensitivity score to each meeting message based on factors such as the meeting content, the identities of the meeting participants, and the history of information sharing. This score is used to determine encryption strength, data storage location, and access control policy priorities.

[0128] To evaluate the sensitivity of meeting information, we introduce the following weighted scoring formula:

[0129]

[0130] in,

[0131] The sensitivity score of the representative meeting information content (such as whether it involves company secrets, personal privacy, etc.).

[0132] The sensitivity rating of the participants (e.g., whether senior management, external partners, etc. are involved).

[0133] Indicates the sharing scope of meeting information (for example, whether the information is public or only visible to specific people).

[0134] Security event records representing historical information sharing (such as a meeting where information leakage occurred).

[0135] Weight The sensitivity score is set based on organizational needs to reflect the importance of different factors to information sensitivity. For example, the content of a meeting may be highly sensitive, but the identities of the participants may be relatively common, so the sensitivity score is still high.

[0136] User behavior analysis and real-time risk assessment:

[0137] A machine learning-based abnormal behavior detection system monitors user behavioral deviations when accessing meeting information. For example, if a user suddenly accesses unauthorized information or abnormally requests excessive data, the system immediately identifies it through AI algorithms, generates a real-time risk assessment report, and triggers a security response mechanism.

[0138] Adopt an anomaly detection mechanism based on machine learning, the formula is as follows:

[0139]

[0140] in,

[0141] It is the risk assessment value of the current user behavior.

[0142] It is the weight of each behavior type, reflecting the impact of a certain behavior on security (such as access history, permission violation, etc.).

[0143] It is the deviation between the current behavior and the user's historical behavior. The greater the deviation, the higher the risk.

[0144] if If the preset threshold is exceeded, the system will automatically trigger an alarm or restrict the user's access rights.

[0145] Encryption management and conference information transmission security:

[0146] Encryption strategies are introduced based on the sensitivity score of meeting information and dynamic adjustment of user permissions. Strong encryption algorithms such as AES-256 are used for data storage and transmission. Encryption key management is managed by the cloud platform's security module, ensuring periodic key rotation and lifecycle management. Different encryption strategies are used for the transmission and storage of sensitive information to address data isolation issues in multi-tenant environments.

[0147] Sensitive information uses a stronger encryption algorithm, while ordinary information can use a lighter encryption method, thereby improving system efficiency and maintaining higher security.

[0148] It can achieve comprehensive security supervision of conference information, ensuring that information security is protected to the greatest extent while maintaining the flexibility and scalability of the system.

[0149] See also Figure 3In step S5, the dynamic access control model based on behavior analysis further includes:

[0150] User Behavior Analysis (UBA):

[0151] By continuously monitoring and learning from users' behavioral history, the system identifies normal and abnormal behavior patterns. By analyzing the frequency, type, content, and historical access history of users' meetings, the system predicts their future access needs and potential risks.

[0152] First, by monitoring and analyzing user behavior, we calculate the user's "normal behavior" score. We can use the following formula to calculate the deviation value (Anomaly Score, AS) of the user's behavior and then evaluate the current user's access rights:

[0153]

[0154] in,

[0155] The current user's behavioral indicators (such as access frequency, meeting content viewing time, number of visits, etc.).

[0156] It is an indicator of the user's historical behavior.

[0157] It is the weight of the behavior indicator, which indicates the impact of the behavior on security.

[0158] If a user's current behavior deviates significantly from their historical behavior (i.e., the AS value is large), the system will mark it as "abnormal behavior" and reduce their access rights.

[0159] Meeting Information Sensitivity Score (ISS):

[0160] Conduct a sensitivity assessment of the content of each meeting. Sensitive information requires stricter access controls. The sensitivity score of information will influence the dynamic adjustment of access policies, such as encryption strength, audit frequency, and participant permissions.

[0161] The higher the ISS score, the more sensitive the meeting information is. The system will automatically strengthen access control to the meeting, such as encrypting sensitive information and restricting access by unauthorized users.

[0162] Contextual Environment Score (CES):

[0163] The context includes the user's current location, access time, device information, etc. If the user accesses the meeting from a common device during normal working hours, access rights will be more relaxed; if the user accesses during non-working hours or from an unknown device, the system will automatically strengthen security verification.

[0164] If a user's current location or access time does not match their historical behavior, the CES score will be lowered and the system will reduce potential risks by increasing authentication or restricting access rights.

[0165] Real-time risk assessment and dynamic adjustment (RDA):

[0166] The system dynamically assesses real-time risks based on user behavior analysis and meeting information sensitivity, and dynamically adjusts user access rights according to risk levels.

[0167] Taking into account the user behavior score, meeting information sensitivity score, and context score, the system calculates the final dynamic adjustment value of access rights using the following formula:

[0168]

[0169] in,

[0170] These are the adjusted access permissions.

[0171] It is the raw permission value calculated based on the user role and basic access rights.

[0172] It is a weighting factor that regulates the impact of behavioral bias, information sensitivity, and contextual environment on permission adjustment.

[0173] The maximum values ​​of the behavior score, sensitivity score, and contextual environment score are used to normalize each scoring dimension.

[0174] If a user's behavior deviates significantly (i.e., a high AS value), the meeting information is sensitive (i.e., a high ISS value), or the context does not meet normal conditions (i.e., a low CES value), the system will automatically reduce the user's access rights. For example, if a user's behavior is abnormal, the system may reduce access to certain sensitive content; if the meeting information is highly sensitive, the system may require additional authentication.

[0175] Example 3:

[0176] See also Figure 4 A cloud computing-based conference information security supervision system is constructed based on the cloud computing-based conference information security supervision method described in embodiments 1 and 2, and includes:

[0177] User behavior analysis and dynamic access control module:

[0178] By analyzing user behavior history (such as login habits, meeting attendance frequency, information access paths, etc.), a user behavior model is constructed. The system can detect potential abnormal behaviors (such as sudden privilege escalation, logins at unusual times, etc.).

[0179] Based on real-time behavioral analysis, the system can dynamically adjust user access rights. For example, when abnormal behavior is detected, unnecessary access rights can be automatically revoked or higher authentication requirements can be triggered.

[0180] Conference information encryption and virtual machine security isolation module:

[0181] Meeting information is encrypted to ensure security during storage and transmission. The encryption strength is automatically adjusted based on factors such as data sensitivity, VM configuration, and access permissions, ensuring that sensitive data cannot be read even if the VM memory or disk is exposed.

[0182] Network isolation and traffic monitoring module:

[0183] Responsible for strictly isolating and controlling network traffic between virtual machines in the cloud computing platform. Through precise network policies and deep packet inspection, it ensures that virtual machines can only communicate according to security policies, preventing traffic interference or illegal access between different tenants.

[0184] Virtual machine monitoring and auditing module:

[0185] Real-time monitoring of virtual machine operations, user operations, data access, and other activities ensures that virtual machine behavior meets security requirements. The system can capture any abnormal operations within the virtual machine (e.g., illegal data access, abnormal resource consumption, etc.).

[0186] It also provides detailed audit logs to record security events, user behavior, and data operations for each virtual machine and container for post-analysis and forensics.

[0187] Sensitive information detection and protection module:

[0188] Use sensitive data recognition technology to automatically scan and mark sensitive data in meeting information, such as personally identifiable information (PII) and confidential business data, and encrypt or restrict access to this information based on preset protection policies.

[0189] Combining artificial intelligence and machine learning algorithms, the system can identify potential risks of sensitive data leakage and automatically take protective measures, such as encrypted storage, access control, and automatic shielding of sensitive information.

[0190] Identity authentication and access control module:

[0191] In cloud computing environments, strong authentication mechanisms are crucial. This module uses multi-factor authentication (MFA), single sign-on (SSO), biometrics, and other technologies to ensure that only authorized users can access sensitive meeting information.

[0192] The system dynamically adjusts user access rights based on roles and risks, avoiding over-authorization and limiting user rights based on the sensitivity and risk level of the meeting.

[0193] Emergency response and incident handling module:

[0194] Responsible for responding quickly and taking appropriate measures when the system detects a security incident, such as isolating the affected virtual machine, restricting access rights, enabling emergency backup, etc.

[0195] By automating the incident handling process, we can reduce the delay of manual intervention and ensure the rapid restoration of normal system operations.

[0196] The beneficial effects of the present invention are:

[0197] This cloud-based conference information security monitoring method and system utilizes multi-layered cloud computing security protections, combined with behavioral analysis, virtualized security isolation, and dynamic access control technologies, to provide more comprehensive and flexible security monitoring for conference information in cloud environments. Through dynamic behavioral analysis and risk assessment, the system adjusts user access rights in real time, precisely controlling access to conference information and ensuring that only authorized users can access sensitive data within the appropriate timeframe. Furthermore, internal virtual machine data encryption and virtualized isolation ensure high data security during storage and processing, preventing data leakage and unauthorized access.

[0198] In the description of this specification, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0199] While 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 these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for conference information security supervision based on cloud computing, characterized in that: The following steps are involved: S1. Conference information security needs analysis; In a cloud computing environment, first conduct a comprehensive analysis of the needs for conference information security; S2, security strategy design and model construction; After demand analysis, design conference information security strategies suitable for cloud computing platforms, including data encryption, identity authentication, permission control, and access auditing. S3. Security management of conference information life cycle; Bring the entire lifecycle of conference information under regulatory oversight, and implement targeted security measures for each lifecycle stage; S4. Security threat monitoring and early warning based on artificial intelligence; Use artificial intelligence (AI) technology to conduct real-time monitoring and early warning of security threats in cloud computing environments; S5. Intelligent implementation of conference information access control; Design a dynamic access control model based on behavioral analysis. By analyzing the user's historical behavior and preferences, the model dynamically adjusts the user's permissions and immediately revokes access rights when abnormal behavior occurs. S6, security mechanism for multi-party collaboration and data sharing; In a cloud computing environment, encrypted sharing methods are used to ensure data security during transmission and storage. Blockchain technology is used to verify data integrity. Through a decentralized approach, shared data cannot be tampered with, thereby improving the transparency and security of data sharing. S7, virtualization security isolation in cloud environments; By encrypting data within virtual machines, strengthening network isolation between virtual machines, and implementing strict virtual machine monitoring and auditing, the security of virtual machine images and container images is strengthened to prevent the injection of malicious code and illegal access; S8. Security protection during the transmission of conference information; Strengthen encryption measures during the transmission of conference information and use strong encryption protocols such as TLS and IPsec to encrypt all transmitted conference information; S9. Audit and traceability of conference information access behavior; Audit and trace the access and operation of conference information, deploy a comprehensive logging system in the cloud computing platform, and record all user operations.

2. A method for monitoring conference information security based on cloud computing according to claim 1, characterized in that: In step S1, the characteristics of the cloud computing platform are taken into consideration, such as the impact of virtualization and distributed storage on security, on conference information security. The types of conference information, such as text, audio, video, and document sensitivity levels, as well as the access requirements of users with different permissions to these information are analyzed. The analysis also includes various potential security threats and risks, such as data leakage, illegal access, information tampering, and malware attacks. By defining detailed security goals, comprehensive supervision of subsequent regulatory strategies is ensured.

3. The method for conference information security supervision based on cloud computing according to claim 1, characterized in that: In step S2, an access control policy is designed in a cloud-based multi-tenant environment to ensure that only authorized users can access and operate specific meeting information through a policy model; The policy design selects appropriate encryption algorithms such as AES-256, identity authentication mechanisms such as multi-factor authentication, and log auditing solutions.

4. A method for monitoring conference information security based on cloud computing according to claim 3, characterized in that: The strategy model is constructed by including the following processes: Permission control and dynamic authorization mechanism; Meeting information sensitivity assessment model; User behavior analysis and real-time risk assessment; Encrypted management and conference information transmission security.

5. The method for conference information security supervision based on cloud computing according to claim 1, characterized in that: In step S4, a machine learning model is used to dynamically analyze access logs, data traffic, and user behavior within the cloud computing platform to promptly identify potential security threats, such as abnormal logins, unauthorized access, and large-scale data downloads. Based on the results of data analysis, security warnings are automatically generated to remind administrators to conduct further investigations. Based on historical data training, the detection capabilities are gradually improved, enabling the system to identify more complex and hidden security attacks.

6. The method for conference information security supervision based on cloud computing according to claim 1, characterized in that: In step S5, the dynamic access control model based on behavior analysis includes: User Behavior Analysis (UBA); Meeting Information Sensitivity Score (ISS); Contextual Environment Score (CES); Real-time risk assessment and dynamic adjustment (RDA); The model dynamically adjusts access permissions by comprehensively considering user behavior, meeting information sensitivity and contextual environment.

7. The method for conference information security supervision based on cloud computing according to claim 1, characterized in that: In step S7, virtualization security isolation includes: Internal VM encryption: Encrypts sensitive data in VM memory, storage, and swap files. Even if the VM administrator or attacker has access to the VM's file system or memory data, they cannot read the encrypted information. Inter-VM network isolation: By implementing strict access control and network isolation at the virtual network level, traffic between different VMs is effectively managed to prevent improper access and data leakage. Virtual machine security monitoring and auditing: Through the monitoring and auditing mechanism at the virtual machine layer, virtual machine activities such as access requests and data transmission are detected in real time. When anomalies occur, alarms are immediately issued and corresponding measures are taken.

8. The method for conference information security supervision based on cloud computing according to claim 1, characterized in that: In step S8, when sensitive data is involved, the transmission link is encrypted end-to-end; Monitor network traffic in real time and respond immediately when abnormal traffic is detected to prevent security incidents such as data leaks or DDoS attacks.

9. The method for conference information security supervision based on cloud computing according to claim 1, characterized in that: In step S9, the recorded user operations include viewing, editing, sharing, and downloading of conference information; The recorded logs include timestamp, operation type, operation content, and user identity information. At the same time, log data is stored in encrypted form to prevent tampering or deletion. Through auditing and tracing, potential security issues can be discovered and timely measures can be taken to address them.

10. A conference information security supervision system based on cloud computing, constructed based on the conference information security supervision method based on cloud computing according to any one of claims 1 to 9, characterized in that: include: User behavior analysis and dynamic access control module; Conference information encryption and virtual machine security isolation module; Network isolation and traffic monitoring module; Virtual machine monitoring and auditing module; Sensitive information detection and protection module; Identity authentication and access control module; Emergency response and incident handling module.

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