• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.7
• /
• pp.3794-3820
• /
• 2019

In recent years, a cloud environment with the ability to detect illegal behaviours along with a secured data storage capability is much needed. This study presents a cloud storage framework, wherein a 128-bit encryption key has been generated by combining deoxyribonucleic acid (DNA) cryptography and the Hill Cipher algorithm to make the framework unbreakable and ensure a better and secured distributed cloud storage environment. Moreover, the study proposes a DNA-based encryption technique, followed by a 256-bit secure socket layer (SSL) to secure data storage. The 256-bit SSL provides secured connections during data transmission. The data herein are classified based on different qualitative security parameters obtained using a specialized fuzzy-based classification technique. The model also has an additional advantage of being able to decide on selecting suitable storage servers from an existing pool of storage servers. A fuzzy-based technique for order of preference by similarity to ideal solution (TOPSIS) multi-criteria decision-making (MCDM) model has been employed for this, which can decide on the set of suitable storage servers on which the data must be stored and results in a reduction in execution time by keeping up the level of security to an improved grade.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.11
• /
• pp.3182-3203
• /
• 2023

With the growing adoption of cloud-based technologies, maintaining the privacy and security of cloud data has become a pressing issue. Privacy-preserving encryption schemes are a promising approach for achieving cloud data security, but they require careful design and implementation to be effective. The integrated approach to cloud data security that we suggest in this work uses CogniGate: the orchestrated permissions protocol, index trees, blockchain key management, and unique Opacus encryption. Opacus encryption is a novel homomorphic encryption scheme that enables computation on encrypted data, making it a powerful tool for cloud data security. CogniGate Protocol enables more flexibility and control over access to cloud data by allowing for fine-grained limitations on access depending on user parameters. Index trees provide an efficient data structure for storing and retrieving encrypted data, while blockchain key management ensures the secure and decentralized storage of encryption keys. Performance evaluation focuses on key aspects, including computation cost for the data owner, computation cost for data sharers, the average time cost of index construction, query consumption for data providers, and time cost in key generation. The results highlight that the integrated approach safeguards cloud data while preserving privacy, maintaining usability, and demonstrating high performance. In addition, we explore the role of differential privacy in our integrated approach, showing how it can be used to further enhance privacy protection without compromising performance. We also discuss the key management challenges associated with our approach and propose a novel blockchain-based key management system that leverages smart contracts and consensus mechanisms to ensure the secure and decentralized storage of encryption keys.

• Electronics and Telecommunications Trends
• /
• v.37 no.5
• /
• pp.62-69
• /
• 2022

In a situation where applications determine business competitiveness, they cannot respond to varying customer requirements without the cloud's flexibility and scalability. Companies have begun seeking ways to enjoy the advantages of the cloud fully, and the concept of "Cloud Native" is emerging as a solution to the problem. Cloud Native is now a target of interest in the market. Microservice and serverless functions can play a vital role in cloud-native architecture. Microservice arranges applications into various independent services, each offering certain functionality through mutual networking. eBPF is attracting attention as a cloud-native networking solution that quickly supports microservice features that repeat creation/deletion. This study identifies the characteristics of eBPF-based networking and evaluates cloud-native networking and secure networking using eBPF.

• International Journal of Computer Science & Network Security
• /
• v.23 no.2
• /
• pp.89-95
• /
• 2023

Cloud computing today provides huge computational resources, storage capacity, and many kinds of data services. Data sharing in the cloud is the practice of exchanging files between various users via cloud technology. The main difficulty with file sharing in the public cloud is maintaining privacy and integrity through data encryption. To address this issue, this paper proposes an Enhanced RSA encryption schema (ERSA) for data sharing in the public cloud that protects privacy and strengthens data integrity. The data owners store their files in the cloud after encrypting the data using the ERSA which combines the RSA algorithm, XOR operation, and SHA-512. This approach can preserve the confidentiality and integrity of a file in any cloud system while data owners are authorized with their unique identities for data access. Furthermore, analysis and experimental results are presented to verify the efficiency and security of the proposed schema.

• Journal of the Korea Convergence Society
• /
• v.7 no.1
• /
• pp.1-8
• /
• 2016

Cloud computing technology offers function that share each other computer resource, software and infra structure based on network. Virtualization is a very useful technology for operation efficiency of enterprise's server and reducing cost, but it can be target of new security threat when it is used without considering security. This paper proposes access control mechanism based on MAC(Mandatory Access Control) for cloud convergence that solve various problem that can occur in cloud environment. This mechanism is composed of set of state rules, security characteristics and algorithm. Also, we prove that the machine system with access control mechanism and an initial secure state is a secure system. This policy module of mechanism is expected to not only provide the maintenance but also provide secure resource sharing between virtual machines.

• Convergence Security Journal
• /
• v.15 no.5
• /
• pp.3-8
• /
• 2015

Most mobile cloud computing system use public key cryptography to provide data security and mutual authentication. A variant of traditional public key technologies called Identity-Based Cryptography(IBC) has recently received considerable attention. The certificate-free approach of IBC may well match the dynamic qualities of cloud environment. But, there is a need for a lightweight secure framework that provides security with minimum processing overhead on mobile devices. In this paper, we propose to use hierarchical ID-Based Encryption in mobile cloud computing. It is suitable for a mobile network since it can reduce the workload of root Public Key Generators by delegating the privilege of user authentication and private key generation. The Identity-Based Encryption and Identity-Based Signature are also proposed and an ID-Based Authentication scheme is presented to secure data processing. The proposed scheme is designed by one-way hash functions and XOR operations, thus has low computation costs for mobile users.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.3
• /
• pp.29-36
• /
• 2016

In cloud storages, as security of stored files and privacy of users become regarded as important concerns, secure cloud storages have been proposed, where stored files are encrypted with file owner's password and even the cloud service provider can not open the file contents. However, if the file owner forgets one's password, one can no longer access the file. To solve this problem, we propose a scheme for changing password for the secure cloud based on proxy re-encryption, which make the file owner enable to change password even when one forgets it. With the proposed scheme, only the file owner can change the password and re-encrypt the files securely because other user and even the service provider can not see the file contents.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.12
• /
• pp.4345-4363
• /
• 2021

Deep Learning as a Service (DLaaS), utilizing the cloud-based deep neural network models to provide customer prediction services, has been widely deployed on mobile cloud computing (MCC). Such services raise privacy concerns since customers need to send private data to untrusted service providers. In this paper, we devote ourselves to building an efficient protocol to classify users' images using the convolutional neural network (CNN) model trained and held by the server, while keeping both parties' data secure. Most previous solutions commonly employ homomorphic encryption schemes based on Ring Learning with Errors (RLWE) hardness or two-party secure computation protocols to achieve it. However, they have limitations on large communication overheads and costs in MCC. To address this issue, we present LeHE4SCNN, a scalable privacy-preserving and communication-efficient framework for CNN-based DLaaS. Firstly, we design a novel low-expansion rate homomorphic encryption scheme with packing and unpacking methods (LeHE). It supports fast homomorphic operations such as vector-matrix multiplication and addition. Then we propose a secure prediction framework for CNN. It employs the LeHE scheme to compute linear layers while exploiting the data shuffling technique to perform non-linear operations. Finally, we implement and evaluate LeHE4SCNN with various CNN models on a real-world dataset. Experimental results demonstrate the effectiveness and superiority of the LeHE4SCNN framework in terms of response time, usage cost, and communication overhead compared to the state-of-the-art methods in the mobile cloud computing environment.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.4
• /
• pp.2219-2236
• /
• 2017

With cloud storage services, users can handle an enormous amount of data in an efficient manner. However, due to the widespread popularization of cloud storage, users have raised concerns about the integrity of outsourced data, since they no longer possess the data locally. To address these concerns, many auditing schemes have been proposed that allow users to check the integrity of their outsourced data without retrieving it in full. Yuan and Yu proposed a public auditing scheme with a deduplication property where the cloud server does not store the duplicated data between users. In this paper, we analyze the weakness of the Yuan and Yu's scheme as well as present modifications which could improve the security of the scheme. We also define two types of adversaries and prove that our proposed scheme is secure against these adversaries under formal security models.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.5
• /
• pp.1450-1470
• /
• 2023

In a Vehicular Cloud (VC) network, an announcement protocol plays a critical role in promoting safety and efficiency by enabling vehicles to disseminate safety-related messages. The reliability of message exchange is essential for improving traffic safety and road conditions. However, verifying the message authenticity could lead to the potential compromise of vehicle privacy, presenting a significant security challenge in the VC network. In contrast, if any misbehavior occurs, the accountable vehicle must be identifiable and removed from the network to ensure public safety. Addressing this conflict between message reliability and privacy requires a secure protocol that satisfies accountability properties while preserving user privacy. This paper presents a novel announcement protocol for secure communication in VC networks that utilizes group signature to achieve seemingly contradictory goals of reliability, privacy, and accountability. We have developed the first comprehensive announcement protocol for VC using group signature, which has been shown to improve the performance efficiency and feasibility of the VC network through performance analysis and simulation results.