Project Topics For Cloud Computing that offer major contributions to the domain and scopes for detailed study are listed below. Stay in touch with cloudcomputingprojects.net for best cloud computing projects help., send us a message we will guide you immediately at an affordable cost. Particular issues in cloud computing are also considered in these topics:
- Enhancing Cloud Security and Privacy in Multi-Tenant Environments
Explanation: In multi-tenant cloud platforms, enhance confidentiality and security by investigating methods. It is essential to consider preventing illegal access and data violations.
Research Issues:
- Among tenants, the effective isolation technologies have to be applied.
- For processing, transmission, and inactive data, we plan to improve the encryption methods.
- Access control and innovative authentication technologies should be created.
- Dynamic Resource Allocation and Management in Cloud Data Centers
Explanation: To improve the cost-effectiveness and functionality of cloud data centers, dynamic resource allocation methods should be explored.
Research Issues:
- By employing machine learning models, resource requirements have to be forecasted in a precise way.
- Among several servers and data centers, balancing load in a dynamic manner.
- In addition to preserving functionality, the energy usage must be reduced.
- Improving Cloud-Based Big Data Analytics Performance
Explanation: On cloud infrastructure, the scalability and functionality of big data analytics environments should be improved by exploring techniques.
Research Issues:
- For cloud platforms, the data processing frameworks such as Spark and Hadoop have to be improved.
- In actual-time data analytics, throughput should be enhanced and latency must be minimized.
- In shared systems, data consistency and transparency have to be assured.
- Integrating Edge and Cloud Computing for Real-Time Applications
Explanation: To assist actual-time applications like smart cities and IoT, the combination of edge and cloud computing has to be explored.
Research Issues:
- To involve cloud and edge, effective data processing and storage approaches must be created.
- To align with actual-time needs, we aim to solve latency challenges.
- Among heterogeneous platforms, confidentiality and security should be assured.
- Energy-Efficient Cloud Computing
Explanation: While preserving service quality, the energy usage of cloud data centers must be minimized by creating methods.
Research Issues:
- For resource handling, the energy-effective algorithms have to be applied.
- Renewable energy sources should be utilized. In data centers, their application has to be enhanced.
- Among energy efficiency and functionality, the trade-offs must be assessed.
- Enhancing Disaster Recovery and Business Continuity in Cloud Computing
Explanation: In cloud environments, disaster recovery and business continuity ideas have to be enhanced by exploring policies.
Research Issues:
- Efficient multi-cloud disaster recovery approaches should be modeled.
- At the time of disasters, downtime and data loss has to be reduced.
- Focus on disaster recovery ideas and assure their scalability and cost-efficiency.
- Blockchain Integration with Cloud Computing
Explanation: To improve data reliability, morality, and security, the possibility of blockchain mechanism combination with cloud computing has to be examined.
Research Issues:
- For cloud platforms, we intend to create effective and scalable blockchain solutions.
- Adherence to rules and data confidentiality has to be assured.
- In the cloud, functionality and scalability challenges of blockchain should be solved.
- Serverless Computing: Opportunities and Challenges
Explanation: For serverless computing architectures, the advantages and shortcomings have to be analyzed. To solve current issues, policies should be created.
Research Issues:
- In serverless functions, cold start latency must be reduced.
- For random workloads, resource allocation and scaling should be handled.
- In serverless platforms, security and adherence has to be assured.
- Optimizing Cloud-Based Machine Learning Workflows
Explanation: In cloud platforms, enhance machine learning workflows by exploring techniques. Scalability, cost, and functionality must be considered.
Research Issues:
- For machine learning models, the placement and scaling has to be automated.
- In cloud-related ML systems, the cost of training and inference must be minimized.
- In machine learning pipelines, data confidentiality and security should be assured.
- Comparative Analysis of Cloud Service Providers
Explanation: For important cloud service providers (instance: Microsoft Azure, Google Cloud, AWS), an extensive comparative analysis has to be carried out. It is important to consider service contributions, cost, and functionality.
Research Issues:
- For comparison, the principles and assessment metrics have to be created.
- Among various types of workloads, the cost and functionality should be examined.
- Focus on every provider’s services and tools, and evaluate their advantages and shortcomings.
What are the key threats to cloud security?
In the field of cloud security, several threats have emerged which focus on accessing data in an illegal manner. Relevant to cloud security, we specify the major threats, including concise explanations of each threat:
- Data Breaches
Outline: Data violations can be caused by illegal access to confidential data, which is stored in the cloud. It can result in major financial and reputational harm and reveal sensitive detail.
Instances:
- Accessing databases through misuse of vulnerabilities.
- Another instance is insider threats, where data access is exploited by workers.
- Data Loss
Outline: Accidental destruction or erasure of data is considered as data loss. Major functional disruptions can be caused by data loss.
Instances:
- Managers or users delete the data unintentionally.
- As a result of hardware faults or software errors, data can be corrupted.
- Consider the inadequate disaster recovery and backup techniques.
- Insufficient Identity, Credential, and Access Management
Outline: Illegal access to cloud resources can be caused by ineffective handling of credentials, weak authentication technologies, and insufficient access controls.
Instances:
- Focus on utilization of default or ineffective passwords.
- Consider the inadequate multi-factor authentication (MFA).
- Ineffective access control strategies.
- Insecure Interfaces and APIs
Outline: APIs and interfaces are highly dependent on cloud services. Illegal access to cloud resources can be resulted by misusing APIs and interfaces, if they are unprotected.
Instances:
- In APIs, consider lack of input verification.
- Inadequate reviews for appropriate authentication and authorization.
- By means of unsafe APIs, confidential data can be revealed.
- Misconfiguration and Inadequate Change Control
Outline: To illegal access, sensitive data and services can be revealed in the case of disarranged cloud resources. Accidental security gaps can be resulted by insufficient change control.
Instances:
- Involving confidential data, consider storage buckets which are openly accessible.
- Focus on the disarranged databases or virtual machines.
- For setup modifications, concentrate on inadequate auditing and tracking.
- Denial of Service (DoS) Attacks
Outline: For legal users, cloud services can be inaccessible if they are overloaded by DoS assaults. Business processes are also disturbed through these assaults.
Instances:
- To drain the capability, cloud resources are overloaded with enormous requests.
- As a means to crash services, vulnerabilities are misused.
- Insider Threats
Outline: Cloud security can be damaged through accidental errors by insiders or harmful activities. Some of the potential insiders are contractors or workers.
Instances:
- Accessing sensitive data by insider, and the access exploitation.
- Data loss or revelation can be resulted through accidental errors.
- Advanced Persistent Threats (APTs)
Outline: To steal data or interrupt operations, permanent access to cloud platforms are obtained by assaulters in APTs, which are considered as advanced and focused assaults.
Instances:
- Concentrate on state-sponsored cyber espionage.
- On particular firms or industries, consider the more focused assaults.
- Shared Technology Vulnerabilities
Outline: In the major distributed infrastructure of cloud platforms, several tenants can be harmed by misusing vulnerabilities.
Instances:
- Cross-tenant assaults can be caused through misuse in virtualization mechanisms.
- In distributed services such as network infrastructure or DNS, consider shortcomings.
- Compliance and Legal Risks
Outline: Legal actions, loss of business, and penalties can be caused in the case of not adhering to legal rules and regulatory needs.
Instances:
- For data security rules such as GDPR, CCPA or HIPAA, consider non-obedience.
- From jurisdictional changes and data sovereignty, legal challenges can be raised.
- Lack of Visibility and Control
Outline: Across cloud infrastructure, rapid threat response and efficient security management are intricate because of reduced visibility and control.
Instances:
- Inadequate abilities for logging and tracking.
- Consider complexity in cloud resource monitoring and handling.
- Shadow IT
Outline: Security risks can be presented through the utilization of cloud services and applications, especially if they are employed without the consent or acknowledgment of the IT department.
Instances:
- With unfamiliar security practices, consider unexplored applications.
- Illegal cloud services can lead to data leakage.
In terms of the cloud computing domain, several interesting topics are suggested by us, along with major issues. For cloud security, we listed out the major threats, encompassing some instances.
Dissertation Topics for Cloud Computing
Dissertation Topics for Cloud Computing across all areas are carried out by us, we will provide you with instant guidance .Get Cloud Computing simulation done by our developers we provide you with detailed explanation.
- Review and analysis of secure energy efficient resource optimization approaches for virtual machine migration in cloud computing
- A heuristic-based task scheduling algorithm for scientific workflows in heterogeneous cloud computing platforms
- Design of smart inventory management system for construction sector based on IoT and cloud computing
- A deep learning method for lithium-ion battery remaining useful life prediction based on sparse segment data via cloud computing system
- Secure information processing for multimedia forensics using zero-trust security model for large scale data analytics in SaaS cloud computing environment
- Cloud computing model for big data processing and performance optimization of multimedia communication
- Face comparison analysis of patients with orthognathic surgery treatment using cloud computing–based face recognition application programming interfaces
- A cloud computing-based approach using the visible near-infrared spectrum to classify greenhouse tomato plants under water stress
- Cloud computing-enabled IIOT system for neurosurgical simulation using augmented reality data access
- A multi-faceted optimization scheduling framework based on the particle swarm optimization algorithm in cloud computing
- A novel hybrid heuristic-based list scheduling algorithm in heterogeneous cloud computing environment for makespan optimization
- Construction of a smart management system for physical health based on IoT and cloud computing with big data
- An improved forensic-by-design framework for cloud computing with systems engineering standard compliance
- Survey on cross virtual machine side channel attack detection and properties of cloud computing as sustainable material
- An intrusion identification and prevention for cloud computing: From the perspective of deep learning
- Voting extreme learning machine based distributed denial of service attack detection in cloud computing
- IoT enabled cancer prediction system to enhance the authentication and security using cloud computing
- A QoS-guaranteed online user data deployment method in edge cloud computing environment
- Cost-based Energy Efficient Scheduling Technique for Dynamic Voltage and Frequency Scaling System in cloud computing
- Intelligent prediction method for power generation based on deep learning and cloud computing in big data networks
