Data security in cloud environment using cryptographic mechanism

Modern technological advances have given rise to the popularity and success of cloud in organizations and industries because it provides data storage facility and computing services at minimal cost. Data security is one of the important requirements for outsourced data in a cloud storage environment. It also brings new security vulnerabilities for assuring the data confidentiality, data integrity and data access control. Data security of a cloud system depends heavily on the cloud service provider, data owner and cloud users. So, there needs to be some methodology to monitor security vulnerabilities and providing data security in cloud environment. Now a day’s providing data security in cloud storage is one of the most critical tasks. For the past few years many works have been done to assure data security but they are failed in providing data security such as information leakage, secret-key management, cloud-user authentication, breach of data confidentiality, because of collusion attack and lots of computational activities (because of large number of secret keys).In this paper, we used threshold cryptography technique for providing data security in cloud storage system. Proposed approach addresses the data security issues in cloud system more efficiently. In this Threshold cryptography technique data owner create users in groups based on place or location, project, and department, data owner allocates single secret key to each group of users for decryption of data and every users in the group shares parts or pieces of the secret key. Proposed methodology also uses data access control list to control the data access. Proposed approach provides data security more efficiently, it also increases the performance of the system and also it minimizes the number of secret keys.

The security issues in the cloud have been well studied. The data security has much importance in point of data owner. There are number of approaches presented earlier towards performance in data security in cloud. To overcome the issues, a class based multi stage encryption algorithm is presented in this paper. The method classifies the data into number of classes and different encryption scheme is used for different classes in different levels. Similarly, the user has been authenticated for their access and they have been classified into different categories. According to the user profile, the method restricts the access of user and based on the same, the method defines security measures. A system defined encryption methodology is used for encrypting the data. Moreover, the user has been returned with other encryption methods which can be decrypted by the user using their own key provided by the system. The proposed algorithm improves the performance of security and improves the data security.

Cloud computing is one of the emerging technologies in last decade; this technology provides a service model to organizations and public users. Organization users and developers, they start and maintain their organization without any hardware and software infrastructure they can develop their company with the help of cloud technology. Cloud deployment is categorized into three types, private, public and hybrid cloud environment and here public and private cloud more secure comparatively hybrid cloud because when data is moving from private to public cloud security problem is occur. Data communication is most important task in a network environment so the proposed model is focus on data security in hybrid cloud environment. In a hybrid cloud the participation of private cloud and its nodes very important after that the data transmission is depends on active node, In this node selection is based on genetic algorithm. The result of proposed model is going to compare with private and public cloud security parameters.

Cloud security is a branch of cyber security that focuses on securing cloud computing systems. It is a method for enterprises to use the internet to access storage and virtual services while saving money on infrastructure, considered as the next-generation architecture since it combines application software and databases into big data centers. However, difficulties with confidentiality, protection, integrity, and compliance may surface when the information is not kept, examined, or computed locally. A wide range of data security-related topics are covered by cloud-based data security. For securing an organization's data across the network, data encryption is a common and effective security strategy that is a great alternative. The most vulnerable data is financial and payment systems, and medical data, which can expose customers or clients critical information. Several academics have also offered a range of approaches to safeguards to maintain data privacy and security while it is being transmitted, but there are still a lot of obstacles to the safety of data that is being stored in the cloud. In this paper, several research papers that have been authored and published in this topic are thoroughly examined and analysed. This study gives a review of the literature on different methods for establishing data security in cloud environment.

In the modern era of the computing world, the data producing and using it is becoming large and instant at various places. For availing the data at different locations for processing we need to store it in the global platform. Cloud environment provides a best and easy way for this. Cloud computing is becoming as the essential thing for high-quality data services. However there are some potential problems with respect to data security. Here encryption techniques can be used for providing security, but with restricted efficiency. In this paper we propose a new encryption mechanism for providing data security in cloud environment. We propose a two round searchable encryption which supports multi keyword retrieval. Here we adapted a vector space model for improving search accuracy; the elgamal encryption technique allows users to involve in the ranking, while the essential key part of encryption will be done at the source itself. The proposed improves the data security and reduces data leakage.

With the fast development of cloud computing and its wide application, data security plays an important role in cloud computing. This paper brought up a novel data security strategy based on artificial immune algorithm on architecture of HDFS for cloud computing. Firstly, we explained the main factors influence data security in cloud environment. Then we introduce HDFS architecture, data security model and put forward an improved security model for cloud computing. In the third section, artificial immune algorithm related with negative selection and dynamic selection algorithm that adopted in our system and how they applied to cloud computing are depicted in detail. Finally simulations are taken by two steps. Former simulations are carried out to prove the performance of artificial immune algorithm brought up in this paper, the latter simulation are running on Cloudsim platform to testify that data security strategy based on artificial immune algorithm for cloud computing is efficient.

Hybrid encryption techniques are gaining popularity in the cloud platform due to their ability to address security concerns and data storage challenges. In order to ensure confidentiality at every stage of processing, this article presents an innovative strategy that merges fully homomorphic encryption (FHE) and secure hash algorithm 3 (SHA-3), offering robust protection against cyber threats. FHE and SHA-3 offer a solution to this problem. We conducted experiments using different datasets to test the performance and security strength of this hybrid approach. Our method takes into account factors such as computational overheads, complexity requirements, key management challenges, and limited support from vendors/providers offering specialized hardware/software capable of supporting complex mathematical functions required by each technique separately before combined into a hybrid form suitable enough scaled-out horizontally across different nodes within clouds themselves today globally among end-users relying upon them heavily day-to-day tasks involving mission-critical workloads running inside virtualized machines hosted on public/private clouds ecosystems worldwide. The results show that implementing FHE together with SHA-3 can significantly improve an organization's overall cyber security posture when operating critical infrastructure components residing within cloud environments. According to the results, it performs better than other methods that are currently in used complexity of encryption and decoding, including homomorphic encryption and RSA, AES & DSA, and AES & RSA. The hybrid algorithm we are proposed using fully homomorphic & SHA3 with 2048 bits 0.789 seconds of encryption time and decryption time with 0.001 seconds and execution time with 4.25 seconds. Therefore, we conclude that our proposed hybrid encryption technique is the best approach to address cyber security risks associated with storing sensitive data in cloud computing environments.

ABSTRACTCloud computing is a multifarious computing paradigm incorporating the benefits of service-oriented architecture and utility computing through virtualization. Hybrid cloud, an amalgamation of two or more public and/or private clouds, is gaining high popularity between users due to various reasons involving improved performance, flexible business operations, capacity expansion, optimized costs, and enhanced security. The efficient execution of fine-grained parallel applications onto hybrid cloud system becomes limited due to a number of factors. From the application point of view, it ranges from the dynamicity of the applications to their precedence and communication constraints while for the computational resources, it includes heterogeneity of processors and participating clouds with their interconnection topology. This work proposes a compile time hybrid cloud-based task duplication strategy to execute the fine-grained applications represented as directed acyclic graph (DAG) onto the hybrid cloud environment. The proposed strategy schedules the tasks based on a degree relative to the critical path in the DAG and tries to achieve lower bound of the DAG. Furthermore, it makes an effort to avoid redundant duplication by duplicating only the required parent tasks considering the available idle slots to minimize the execution time of the application. The experimental study reveals that the proposed strategy performs better than its peers in terms of achieving the lower bound more efficiently with lesser degree of duplication for fine-grained jobs. The strategy is highly useful for cloud environment as it results in lower cost of usage of resources with enhanced system utilization.

With the development of cloud computing, hybrid cloud has attracted extensive attention. It is a flexible collaboration of private clouds and public clouds, which can meet the increasing demands of energy consumption while reduce overhead. However, the clouds in hybrid clouds have to share data with each other. Therefore, hybrid connection mechanism remains a big issue. VPN is a common solution used as a bridge for connecting private clouds and public clouds. Using VPN to construct a direct connected network is a simple solution to implement where all the clients in hybrid cloud connect to a specified OpenVPN server residing in public cloud. Unfortunately, it will result in many problems impacting the efficiency of network. In this paper, we propose a proxy based virtual network solution. To compare the network QoS of the proxy based virtual network solution to the direct connected virtual network solution, we designed three controlled experiments measuring the bandwidth and delay time of the intra-cloud and inter-cloud communication. Then we compare the network performance of direct connected virtual network solution and proxy based virtual network with a Hadoop application on a hybrid cloud environment. The experiment result indicates that the proxy based virtual network solution outperforms the direct connected virtual network solution.

Comparative Study of Security Algorithms in Cloud Computing

Ensuring Data Security in Cloud Environment Through Availability

Cyber laboratory for FPGA design experiments combines the actual laboratory and the remote laboratory in a seamless way in a hybrid cloud environment. The hybrid cloud consists of on premise private cloud to support device dependent services and a public cloud to support rest of the laboratory services. The on premise private cloud allows concurrent use of device dependent tasks, such as FPGA run services, by making use of the Web services. The elastic nature of the public cloud is suitable for coping with dynamically changing student experimental usages. The number of servers in the public cloud can be scale out or shrink according to the number of simultaneous students accesses. Expensive license CAD tools, such as Verilog-HDL synthesis tools, are allocated for a limited number of the servers in the public cloud and the private cloud, where Verilog-HDL synthesis Web services are realized to achieve remote sharing of these tools. For remote laboratory case, student virtual machines are allocated in the public cloud and remotely issue the FPGA run services and the Verilog-HDL Synthesis services. The existing faculty file/database and education support system serves as an adhesive agent to combine the on premise cloud and the public cloud to minimize the data transfer among them and to perform student VM migrations between remote and actual laboratories. The Cyber Laboratory achieves an efficient use of laboratory platforms and can reduce TCO (total cost of ownership), as the public cloud can cope with the dynamically changing experimental loads.

Cloud computing relies on sharing computing resources. With high availability and accessibility of resources, cloud computing is under the threat of major cyber-attacks. To detect attacks and preserve security in cloud environment, having an efficient intrusion detection system (IDS) is required. In this article, an effective and efficient IDS is proposed to maintain high level security of data in cloud. The authors have incorporated Reinforcement Learning Automata with their proposed IDS while detecting and classifying attacks. Using learning automata an effective rule set is generated with the proposed algorithm from vast training set to improve the learning process at reduced computation cost and time. After which, the proposed reinforcement learning algorithm helps in classification of attacks accurately using the reinforcement signal. This proposed model was experimented with NSL-KDD as well as KDD 10% dataset and have proved its robustness by detecting attacks more accurately being an IDS.

Cloud computing is a key technology for online service providers. However, current online service systems experience performance degradation due to the heterogeneous and time-variant incoming of user requests. To address this kind of diversity, we propose a hierarchical approach for resource management in hybrid clouds, where local private clouds handle routine requests and a powerful third-party public cloud is responsible for the burst of sudden incoming requests. Our goal is to answer (1) from the online service provider’s perspective, how to decide the local private cloud resource allocation, and how to distribute the incoming requests to private and/or public clouds; and (2) from the public cloud provider’s perspective, how to decide the optimal prices for these public cloud resources so as to maximize its profit. We use a Stackelberg game model to capture the complex interactions between users, online service providers and public cloud providers, based on which we analyze the resource allocation in private clouds and pricing strategy in public cloud. Furthermore, we design efficient online algorithms to determine the public cloud provider’s and the online service provider’s optimal decisions. Simulation results validate the effectiveness and efficiency of our proposed approach.

Although some cloud providers look at the hybrid cloud as blasphemy, there are strong reasons for them to adopt it. Hybrid clouds offer the cost and scale benefits of public clouds while also offering the security and control of private clouds. Task scheduling, one of the most famous combinational optimization problems, plays a key role in the hybrid cloud environment. We propose a graph-based task scheduling algorithm. In order to achieve minimum cost, our algorithm takes into account not only the private resources but also the public resources. This paper also presents an extensive evaluation study and demonstrates that our proposed algorithms minimize the user's cost in a hybrid cloud environment.