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Network Information Security Is A Comprehensive Subject That Is Not Only Highly Theoretical But Also Highly Practical. Many Basic Security Technologies And Methods Need To Be Learned And Applied In A Practical Environment. However, Real Network Systems Are Unlikely To Be Used For On-site Teaching In Colleges And Universities. This Requires Combining Course Design With A Realistic Network Environment And Building A Simulation And Exercise Platform For Systematic Practice In Order To Provide The Society With Technical Talents With Rich Theoretical Knowledge And Good Practical Skills.
The Big Data Experimental Teaching System Is Based On The Cloud Platform Architecture And Provides Users With A Big Data Experimental Environment, Which Is Very Suitable For The Experimental Teaching Needs Of Colleges And Universities. The Experimental Content Covers Professional Basic Content Such As Hadoop, Hive, Hdfs, Spark, Etc., And Also Includes Data Collection And Log Analysis Applications, Data Migration, Data Statistical Analysis, Data Mining And Data Visualization And Other Data Processing Application Related Technical Experimental Operations, Providing Students With The Entire Core Technology Experimental Teaching Process From Big Data Environment Construction To Data Processing, Which Can Support The Development Of Experimental Content Of Courses At All Stages Of Big Data Professional Talent Training.
The Information Security Cloud Experiment System Adopts A B/s Network Architecture, And The User End Accesses The Web Browser Through The Browser To Learn. The System Is Structurally Divided Into Five Levels: Basic Environment Layer, Cloud Management Platform Layer, Business Application Layer, Course Resource Layer, And User Role Layer. Based On Cloud Technology And With Course Content As The Core, It Has Developed A Set Of Practical Training Teaching Systems That Combine Theory And Practice, Integrating Knowledge Training, Skill Training, Simulation Exercises, And Management Assessment. It Can Be Used To Continuously And Systematically Cultivate Network Security Talents And Meet Users’ Needs For Cultivating Information Security Talents.
The Information Security Cloud Experiment System Provides The School With A Complete Teaching System, Including 9 Technical Directions: System Security, Database Security, Data Security, Network Security, Web Security, Mobile Security, Application Programming, Software Security, And Cryptography. It Can Cover The Professional Technical Courses Currently Taught In The School’s Information Security Major.
Product Roles Are Divided Into Administrators, Teachers, And Students. Administrators Mainly Manage The System’s Own Resources; Teachers Mainly Arrange Teaching Experiment Courses; Students Mainly Complete The Specific Experiment Content Arranged By Teachers. It Mainly Includes System Management Functions, Course Management Functions, Examination Management Functions, Experiment Management Functions, Environment Management Functions, Etc.
Based On The Information Security Talent Needs Of Enterprises And The Professional Basic Capabilities Of College Students, We Design A Professional Course System For Information Security Majors. The Course Resources Include Experimental Documents And Supporting Environmental Resources Required For Experimental Operations, Which Can Guide Users To Complete Course Experiments Independently. We Work Backwards From Enterprise Needs To Course Design To Ensure That The Knowledge And Skills Students Learn In School Can Be Recognized By Enterprises.
• It Adopts A Distributed Storage Architecture And Provides A Multi-copy Data Protection Mechanism To Ensure The High Reliability Of The Customer’s Private Cloud Management Platform Data.
• The Solution Integrates The Local Large-capacity Hard Disks Of The Hyper-converged Computing Nodes To Build A Common Shared Storage Resource Pool For Storing General Business Data And Virtual Machine Files.
• Build A High-speed Shared Storage Resource Pool Through The Local Ssd Hard Disks Of The Hyper-converged Computing Nodes To Store Database Files.
It Has Multiple Talent Training Systems Including Teaching Training System, Competition Training System And Job Training System. Colleges And Universities Can Choose According To Their Needs To Cultivate Professional Talents That Meet The Needs Of Society And The Market.
The Teaching Scheduling Function Matches The Normal Teaching Schedule. Within The Specified Time Range, Student Users Who Are Not Included In The Scheduling Plan Will Be Automatically Kicked Out By The System To Ensure That The Scheduling Users Are Not Affected.
The System Supports Teachers' Lesson Preparation Activities And Helps Them Familiarize Themselves With The Teaching Content In Advance. It Also Supports Teachers To Preview The Teaching Resources Of The Experiment, To Practice The Experiment, And To Reasonably Arrange The Class Time Allocation And Teaching Rhythm.
The System Supports Teachers To Pre-start The Experimental Environment, And Give Priority To Assigning The Environment Created By Teachers To Students. For Experimental Environments That Are Not Used Within A Specified Time, The System Automatically Identifies And Shuts Down Or Deletes Them.
Teachers Are Supported To Create Their Own Private Master Copies And Experimental Environments. The System Has Built-in Commonly Used Basic Master Copies For Users To Choose From.
When Studying Resource-intensive Experimental Courses In A Team, The System Will Automatically Group Students Based On The Number Of Maximum Startup Environments. No Teacher Intervention Is Required, And Student Users Can Freely Choose Groups To Study.
After The Teacher User Completes The Exam Reservation Operation On The System, The System Resources Will Give Priority To Supporting The Normal Progress Of The Exam During The Reserved Time Period, And Multiple Anti-cheating Mechanisms Are Built In.
Display System Statistical Data, Including Statistical Information Of The System's Built-in Course Resources, Content Resources, Teaching Data Statistics, Course Popularity List Information, Etc.
