Cloud Computing Engineering Project Ideas that are latest and cold be explored for your projects are given below. We share the notable research gaps in cloud security on your interested area.

In the domain of cloud computing, several topics and ideas have emerged in a gradual manner, which are more suitable for developing projects. Suitable to cloud computing, we recommend a few engineering project topics and plans that are both significant and compelling:

  1. Cloud-Based Load Balancer
  • Outline: Among several servers, incoming network traffic has to be shared by creating a load balancing framework.
  • Important Characteristics: Fault tolerance, dynamic scaling, traffic monitoring, and enhancement.
  • Mechanisms: HAProxy, Nginx, Google Cloud Load Balancing, and AWS Elastic Load Balancing.
  1. Edge Computing Integration with Cloud
  • Outline: A framework must be developed, which processes data nearer to the source by combining edge computing with cloud services.
  • Important Characteristics: Perfect cloud incorporation, actual-time data processing, and minimized latency.
  • Mechanisms: MQTT, Google Cloud IoT Edge, Azure IoT Edge, and AWS Greengrass.
  1. Cloud-Based Microservices Architecture
  • Outline: With a microservices framework that is implemented on the cloud, we plan to build an application.
  • Important Characteristics: Fault isolation, scalability, API gateway, and service discovery.
  • Mechanisms: Azure Kubernetes Service, Google Kubernetes Engine, AWS ECS/EKS, Kubernetes, and Docker.
  1. Cloud-Based AI/ML Model Deployment
  • Outline: In the cloud, machine learning models have to be placed and handled by applying a platform.
  • Important Characteristics: Training of model, deployment, tracking, and versioning.
  • Mechanisms: TensorFlow Serving, Azure ML, Google AI Platform, and AWS SageMaker.
  1. Cloud-Based Blockchain Solution
  • Outline: For improved safety and scalability, a blockchain application must be created, which is established on the cloud.
  • Important Characteristics: Cryptographic security, smart contracts, and decentralized ledger.
  • Mechanisms: Azure Blockchain Service, AWS Managed Blockchain, Hyperledger Fabric, and Ethereum.
  1. Cloud Resource Optimization Tool
  • Outline: Specifically for enhancing effectiveness and minimizing costs, the utilization of cloud resources should be improved by developing a tool.
  • Important Characteristics: Automated scaling, cost assessment, and resource utilization tracking.
  • Mechanisms: Kubernetes Autoscaler, Azure Cost Management, Google Cloud Cost Management, and AWS Cost Explorer.
  1. Cloud-Based Continuous Integration/Continuous Deployment (CI/CD) Pipeline
  • Outline: In the cloud, the software development operations have to be automated by configuring a CI/CD pipeline.
  • Important Characteristics: Automated testing, development, tracking, and placement.
  • Mechanisms: Google Cloud Build, Azure DevOps, AWS CodePipeline, GitLab CI, and Jenkins.
  1. Cloud-Based Disaster Recovery Plan
  • Outline: As a means to assure business endurance, a disaster recovery strategy must be created with cloud services.
  • Important Characteristics: Failover techniques, data replication, automated backups, and recovery testing.
  • Mechanisms: Azure Site Recovery, Google Cloud Disaster Recovery, and AWS Backup.
  1. Serverless Computing Platform
  • Outline: To manage backend operations, an application has to be developed with a serverless framework.
  • Important Characteristics: Auto-scaling, API Gateway incorporation, and event-driven functions.
  • Mechanisms: Serverless Framework, Azure Functions, Google Cloud Functions, and AWS Lambda.
  1. Cloud-Based Internet of Things (IoT) Platform
  • Outline: In IoT devices, we intend to link, handle, and examine data by creating an efficient platform.
  • Important Characteristics: Data gathering, actual-time analytics, device handling, and alerting.
  • Mechanisms: MQTT, Azure IoT Hub, Google Cloud IoT, and AWS IoT Core.
  1. Hybrid Cloud Management System
  • Outline: To combine and handle private and public cloud platforms, a framework must be developed.
  • Important Characteristics: Security handling, workload portability, and unified management console.
  • Mechanisms: Google Anthos, Azure Arc, AWS Outposts, and VMware Cloud.
  1. Cloud-Based Real-Time Analytics Platform
  • Outline: For data analytics and visualization in actual-time, a robust platform should be deployed.
  • Important Characteristics: Dashboards, data ingestion, alerts, and stream processing.
  • Mechanisms: Apache Kafka, Azure Stream Analytics, Google Cloud Dataflow, and AWS Kinesis.
  1. Cloud Security Information and Event Management (SIEM) System
  • Outline: In the cloud platform, track and examine security incidents through creating a SIEM framework.
  • Important Characteristics: Compliance reporting, incident response, and actual-time threat identification.
  • Mechanisms: Google Cloud Security Command Center, Azure Sentinel, AWS Security Hub, and Splunk.
  1. Cloud-Based Big Data Processing Framework
  • Outline: Extensive datasets have to be processed and examined in the cloud by developing a system.
  • Important Characteristics: Machine learning incorporation, data warehousing, and distributed computing.
  • Mechanisms: Azure HDInsight, Google BigQuery, AWS EMR, and Apache Hadoop.
  1. Cloud-Based Application Performance Monitoring (APM) System
  • Outline: To track and enhance the cloud applications’ functionality, we aim to create an APM framework.
  • Important Characteristics: Root cause analysis, anomaly identification, and application tracking.
  • Mechanisms: Google Cloud Operations Suite, Azure Monitor, AWS CloudWatch, Datadog, and New Relic.
  1. Cloud-Based Gaming Platform
  • Outline: For establishing and streaming online games, a cloud-related platform has to be deployed.
  • Important Characteristics: Low-latency functionality, multiplayer support, actual-time streaming, and game establishment.
  • Mechanisms: Azure PlayFab, Google Cloud Game Servers, and AWS GameLift.
  1. Cloud-Based Smart City Infrastructure
  • Outline: To handle smart city framework, a cloud environment must be developed. It is important to consider public services, transportation, and energy.
  • Important Characteristics: Citizen engagement, resource handling, data analytics, and IoT incorporation.
  • Mechanisms: Google Cloud Smart City, Azure Smart City, and AWS Smart City Solutions.

What are the Research Gaps in cloud security?

In terms of cloud security, research gaps can be identified by analyzing related existing studies. Relevant to cloud security, we list out a few research gaps which are important to fulfill in an appropriate manner:

  1. Data Security and Privacy
  • Homomorphic Encryption: For data processing in the cloud, effective and realistic applications of homomorphic encryption are insufficient, even though it is advantageous.
  • Differential Privacy: In addition to preserving data efficiency, the differential privacy methods have to be combined efficiently with cloud frameworks. For that, further exploration is essential.
  • Secure Multi-Party Computation: For secure multi-party computation in cloud platforms, it is difficult to create protocols in a scalable and effective manner.
  1. Identity and Access Management (IAM)
  • Fine-Grained Access Control: To adjust to varying user activities and scenarios, highly advanced and dynamic access control techniques are required.
  • Identity Federation: Among hybrid platforms and several cloud providers, safer and perfect identity management must be assured. To accomplish this objective, even more research is needed.
  1. Cloud Infrastructure Security
  • Virtualization Security: Consider the major research areas such as assuring the isolation among virtual machines and solving potential risks in hypervisors.
  • Container Security: Specifically in multi-tenant contexts, protecting containerized platforms requires highly efficient solutions, which is still considered as an existing issue.
  1. Incident Response and Forensics
  • Cloud Forensics: In cloud platforms, accomplishing efficient forensic analysis through creating standardized tools and methods remains an emerging area.
  • Automated Threat Detection: For precise and actual-time identification of hazards in cloud platforms, machine learning and AI should be utilized. To attain this mission, highly complex exploration is important.
  1. Compliance and Legal Issues
  • Regulatory Compliance: In various jurisdictions, adhering to different and emerging rules must be assured. But, it requires highly focused study, and also remains an intricate issue.
  • Data Sovereignty: In a worldwide cloud platform, one of the unsolved research queries is handling problems relevant to data storage and sovereignty.
  1. Trust and Assurance
  • Third-Party Audits: For cloud services, consider external security reviews and improve their efficiency and reliability. However, more effective approaches are required in this area.
  • Trust Models: Specifically for assessing the security of cloud service providers, extensive trust models have to be created, which can be utilized worldwide. This area remains a gap that should be fulfilled effectively.
  1. Security Management and Policy Enforcement
  • Policy Automation: In dynamic cloud platforms, the development, implementation, and analysis of security strategies must be automated. This research area offers greater opportunity to conduct exploration.
  • Cross-Cloud Policy Management: Among several cloud services and environments, continuous security policy implementation has to be assured. But, further research is required to fulfill this gap.
  1. Secure Cloud Migration
  • Migration Frameworks: For transferring data and applications to the cloud in a safer manner, ideal approaches and standardized frameworks have to be created, which is currently an emerging field.
  • Hybrid Cloud Security: Among cloud services and on-site infrastructure, it is difficult to assure safer and consistent incorporation.
  1. Cloud Security Automation
  • DevSecOps Integration: Across the software development lifecycle, assure consistent security by perfectly combining security into the DevOps pipeline (DevSecOps). But, this area requires further exploration.
  • Automated Compliance Checks: In actual-time, check adherence to security principles in an automatic manner by creating frameworks and tools. This area remains a gap that must be addressed.
  1. Emerging Technologies and Threats
  • Quantum Computing: One of the major research gaps is planning for quantum computing’s security aspects. The process of creating quantum-resistant encryption algorithms could be encompassed.
  • AI/ML Security: In the cloud platform, machine learning and AI frameworks have to be secured against data poisoning and harmful assaults. Higher concentration is required for addressing this area.
  • Zero Trust Architecture: A current research area relevant to cloud platforms is applying and enhancing zero trust standards.
  1. Secure Collaboration and Data Sharing
  • Collaborative Security: For combined work in cloud platforms, effective and safer techniques must be created for confidential information. However, further study is essential for this area.
  • Secure Data Sharing: In addition to preserving morality and privacy, data should be distributed among various cloud environments and services in a safer manner. But, assuring this aspect is an ongoing problem.
  1. User Awareness and Training
  • Security Awareness Programs: To minimize human fault, users have to be trained regarding possible hazards and cloud security ideal approaches, and this area requires highly efficient techniques.
  • User-Centric Security: In cloud platforms, support users to interpret and handle their security vulnerabilities and configurations by creating interfaces and tools. But, more exploration is needed by this area.

Relevant to cloud computing, numerous engineering project topics and plans are suggested by us, along with concise outlines, important characteristics, and mechanisms. By highlighting the cloud security field, we specified several major research gaps to fulfill efficiently.

Cloud Computing Engineering Projects Topics & Ideas

Get to know the Cloud Computing Engineering Projects Topics & Ideas which are innovative and worked by our professionals. By our constant updation of advanced technology we give 100% customer satisfaction.

  1. THEMIS: Towards Mutually Verifiable Billing Transactions in the Cloud Computing Environment
  2. Building an intelligent provisioning engine for IaaS cloud computing services
  3. GD2SA: Geo detection and digital signature authorization for secure accessing to cloud computing environments
  4. A Fair Resource Allocation Approach in Cloud Computing Environments
  5. Detecting software aging in a cloud computing framework by comparing development versions
  6. A Method of Real listing stratified psychiatry for Multidimensional Signatures and Trajectories on Big Data Platform & Cloud Computing
  7. Cloud Computing Methods for Leaking Detection of Halogen Pipeline Based On Distributed Terminals
  8. Analysis on Convergence of Stochastic Processes in Cloud Computing Models
  9. Multi-dimensional SLA-Based Resource Allocation for Multi-tier Cloud Computing Systems
  10. Deployment of application on Cloud and enhanced data security in Cloud computing using ECC algorithm
  11. Parallel Simulation of High-speed Trains Using Ray-based Cloud Computing
  12. Optimal Multiserver Configuration for Profit Maximization in Cloud Computing
  13. Customer-aware resource overallocation to improve energy efficiency in realtime Cloud Computing data centers
  14. An Anomaly Intrusion Detection Method Based on Improved K-Means of Cloud Computing
  15. Multi-authority based weighted attribute encryption scheme in cloud computing
  16. Analysis on Cloud Computing-based Logistics Information Network Mode
  17. A Dynamic Dispatching Method of Resource Based on Particle Swarm Optimization for Cloud Computing Environment
  18. DDSS: Dynamic dedicated servers scheduling for multi priority level classes in cloud computing
  19. Framework design of cloud computing technology application in power system transient simulation
  20. Research on the Model and Application of E-commerce Based on Cloud Computing