Modified ECC for Secure Data Transfer in Multi-Tenant Cloud Computing

Objectives: We want to provide effective integrity verification for encrypted data which is transferred and provide high security. We want to retrieve the results with lesser memory consumption and lesser latency. Methods: The proposed approach combines Attribute Based Cryptography with bilinear mapping to enhance the data security. Simulation model validates the security issues related to the efficient key derivation and Message Authentication Code verification process. We compare our policy with existing techniques on the performance parameters such as encryption time, computational overhead and average lifetime to generate/derive keys. The performance analysis confirms the effectiveness of our policy. Findings: The chief drawbacks of the existing ABE schemes were expensive pairing operations and increase in the complexity and overhead of the admission policy. The time needed to decipher the cipher text was high, due to the great size of the cipher text. Hence, in order to overcome these limitations, this paper proposes an Optimal Integrity Policy for enhanced data security and integrity in the cloud. In secret key generation, we use AND, EXOR and hashing operarations to improve the security. MAC verification process is used to monitor the integrity of the data. An Optimal Integrity Policy confirmed the effectiveness of encryption time over existing CP-ABE methodologies based on the performance measures. The comparative analysis on the parameters such as computational overhead, average life time for generation/derivation of keys shows the better performance in OIP than the EPPDR, subset cover and pseudo random key generators. By enhancing the secret key generation, the data security is also enhanced. The experimental results achieves minimum overhead for both communication and computation. Applications/Improvements: The decryption time is slow for low end devices since it requires modular exponentiation. Hence, the future work shall be extended to speed up the decryption time.

 Abstract—Cloud computing is an emerging technology that is still unclear to many security problems. Ensuring the security ofstored data in cloud servers is one of the most challenging issues in such environments. Accordingly, this schema presents a Hybrid Encryption algorithm that is based on RSA Small-e and Efficient RSA (HE-RSA) for improving the reliability in cloud computing environments. The main aim of this project is to use the cryptography concepts in cloud computing communications and to increase the security of encrypted data in cloud servers with the least consumption of time and cost at the both of encryption and decryption processes.In the proposed model, the number of key generation exponents has been increased in comparison to the original RSA. Moreover,a dual encryption process has been applied in this algorithm to prevent common attacks against RSA algorithm. In addition, this schema also presents the comparison between HE-RSA and original RSA in terms of security and performance. For this purpose, Key Generation, Encryption and Decryption Time in Original RSA and HE-RSA have been compared according to the different size of exponents. Moreover, some of the common attacks against RSA algorithm have been analysed to detect the resistance of the proposed algorithm against possible attacks. Finally, the effects of using HE-RSA on cloud computing environments have been reviewed in more depth and details.

Due to the opportunities provided by the Internet, people are taking advantage of e-learning courses and enormous research efforts have been dedicated to the development of e-learning systems. So far, many e-learning systems are proposed and used practically. However, in these systems the e-learning completion rate is low. One of the reasons is the low study desire and motivation. In this work, we present an IoT-Based E-Learning testbed using Raspberry Pi mounted on Raspbian. We carried out some experiments with a student of our laboratory for brain waves and, encryption and decryption time of cipher algorithms. We used MindWave Mobile (MWM) to get the data. For experimental results, when using our system the concentration is 80 [%] from 0 [s] to 400 [s]. But, for 400 [s] to 1000 [s], concentration is decreased. In the case of not using our system, concentration is almost the same (about 40 [%]) from 0 [s] to 1000 [s]. From simulation results, we found that the decryption time is faster than encryption time, however for 3-DES and Raspberry Pi decryption time is higher than encryption time.

The Data Integrity Based Secure Cloud Data Outsourcing Model involves designing a framework that ensures data outsourced to the cloud remains secure, intact, and authentic. Cloud computing has become an indispensable resource for businesses and individuals alike, providing scalable and cost-effective solutions for data storage and management. However, outsourcing data to external cloud service providers (CSPs) raises serious questions around data security, integrity, and authenticity. It is essential to retain confidence and comply with regulatory criteria to make sure that outsourced data is authentic, obtainable, and unaltered. In this article, the Low-Complexity Elliptic Galois Cryptography based Secure Data Integrity Verification Scheme for Cloud Storage (LCEGC-SDIV-CS) is proposed. Initially, the integration of the advantages in Trusted Execution Environment (TEE) and identity-based encryption using Low-Complexity Elliptic Galois Cryptography (LCEGC) is provided to create a safe data integrity verification scheme. Then, data integrity using Block Access Signature Oriented Merle Hash Tree (BS-MHT) is used for the integrity-preserving structure for encrypted block-oriented storage systems. The random Oracle model's security analysis, depending upon the computational Diffie-Hellman assumption, provides security by preventing attacks when the adversary chooses the messages with targets’ identities. The proposed LCEGC-SDIV-CS model is implemented and the performance metrics like Data uploading with downloading time, Memory usage on data uploading with downloading, Encryption time, Decryption time, and Security levels are examined. The proposed LCEGC-SDIV-CS method attains 21.56%, 23.98%, and 21.19% lower data uploading with downloading time 24.78%, 23.82%, and 23.52% lower encryption time are analyzed with existing methods EDI-SPD-SCS, NSA-SADS-BDEPDP-SDS-RCS respectively.

Information security is major obstacle in different areas like military, network application, bank application. File is forward from one location to another location in the network. Many hackers are illegally access the information. To provide solution to this problem many authors has introduced different algorithms and techniques. The different algorithms like AES, DES and triple DES achieve more security but it takes more time for encryption and decryption files. These algorithm increases the complexity of the algorithm. In our algorithm we have investigate parameters of network security. This algorithm provides more security and takes smallest amount of time for file encryption and decryption. This algorithm can apply on different types of files like text, image, audio, video files. In the Byte Rotation Algorithm involve two techniques. One is random key generation technique is used. And second is parallel encryption and decryption is process using multithreading technique. Key size of random key generation technique is 128 bit.128 bit random key generation is difficult for crack to attacker.

Enabling a security and privacy preservation for the cloud data is one of the demanding and crucial tasks in recent days. Because, the privacy of the sensitive data should be safeguard from the unauthorized access for improving its security. So, various key generation, encryption and decryption mechanisms are developed in the traditional works for privacy preservation in cloud. Still, it remains with the issues such as increased computational complexity, time consumption, and reduced security. Also, the traditional works use the symmetric key cryptography based. Thus, this paper aims to develop a new privacy preservation mechanism by implementing a fully homomorphic–elliptic curve cryptography (FH-ECC) algorithm. The data owner encrypts the original data by converting it into the cipher format with the use of ECC algorithm, and applies the FH operations on the encrypted data before storing it on the cloud. When the user gives the data request to the cloud, the Cloud Service Provider verifies the access control policy of the user for enabling the restricted access on the data. If the access policy is verified, the encrypted data is provided to the user, from that the cipher text is extracted. Then, the ECC decryption and FH operations are applied to generate the original text. Based on the several analysis, the research work is evaluated with the help of different performance measures such as execution time, encryption time, and decryption time. In addition the effectiveness of the novel FHE technique is justified by the comparative analysis made with the traditional techniques.

Medical images contain sensitive and private health information of patients, which is crucial to be safeguarded from unauthorized access. Various encryption schemes are used for improving security; however, they are subject to adversaries associated with higher complexity, ineffective compression ratios, and slower responses in real time. Therefore, to address these limitations as well as to establish stronger security in medical image sharing, the research proposes a Biometric Fused Federated Generative Adversarial Network (BF2GAN) method. The federated learning (FL) concept is included in this research, which provides collaborative training while reducing the risks of gradient inversions. Moreover, the decentralized training strengthens data integrity and reduces the risk of data exposures. The biometric information is included for user verification and key generation, which assists in creating highly secure images that are difficult to decode without the correct keys. The method minimizes the reliance on key management algorithms and establishes a simplified encryption process that strengthens the overall system security. In the LUNA16 database, the BF2GAN achieves a significant performance in terms of 3.08s encryption time, 0.975 structural similarity index measure, 0.82 Feature similarity index, 3.9s decryption time, 58.38 decibels of peak signal-to-noise ratio, and minimum memory usage of 280.87 kilobytes, compared to the state-of-the-art methods.

Cryptographic algorithms are at the core of IT network protection through data confidentiality, integrity, and authentication. This study explores the computational efficiency and complexity of four cryptographic algorithms: Advanced Encryption Standard (AES), Rivest-Shamir-Adleman (RSA), Lattice-Based Cryptography (LBC), and Hyperelliptic Curve Cryptography (HECC). The investigation compares these algorithms using encryption time, decryption time, key generation time, and security strength. Experiment outcome shows that AES has the optimal encryption time of 2.3 ms for real-time applicability and that RSA has the maximum encryption time of 15.7 ms, emphasizing computational overhead. LBC, which is a promising post-quantum cryptographic method, offers strong security with an average encryption time of 8.9 ms, while HECC offers balance between security and efficiency with an encryption time of 5.4 ms. A comparative analysis shows that lattice-based encryption is most fitting for future quantum-resistant security use and that AES is best used for high-speed encryption. The research emphasizes the need for choosing proper cryptographic algorithms in accordance with security needs and computational efficiency. Research in the future should also be aimed at hybrid cryptographic models and AI-based encryption methods to improve security in the future IT infrastructure.

Most cloud users and officialdoms have a great interest in adoption and use cloud services like cloud storage to store their data on cloud environment. With the speedy growing in cloud computing technology, user's data security and privacy in cloud computing technology is the utmost dangerous issues because data owner stores their sensitive data onto remote cloud storage. However, successful retrieval of confidential data and computation on confidential data is hard to succeed by traditional cryptographic algorithm. Hence, to warrant the cloud security we are using the cryptographic algorithms that supports for computation over encrypted data. In this, Homomorphic cryptographic algorithm is one such technique that has interested homomorphic cryptographic algorithm used to secure user data in cloud server. It performs computation on cipher texts data can be operated directly without affecting the confidentiality of the encryption algorithms. We have established a framework for security of data on a cloud storage by using fully homomorphic cryptographic algorithm. Indeed, In this study, we have evaluated complexity of three homomorphic cryptographic algorithm those are SDC FHE, Paillier and RSA with encryption time, decryption time, throughput and memory usage

Shamir’s encryption method is to share a secret image by n number of shadow images and then r shadow images can be used to obtain the original secret image. In proposed method, the size of secret image is greater than the size of the shadow image used for the encryption. Such shadow image is beneficial to process in image hiding, transmission, or storage. For this purpose Shamir’s encryption technique is used in this proposed work. In Shamir’s encryption technique, author used the equation to encrypt the data into multiple parts. In the equation, time required for the multiplication and division of the input components of the data is more than addition and subtraction. Hence, the encryption time is little bit high. To reduce this encryption and decryption time, Shamir’s equation is modified by converting all the multiplication part into addition and division parts into subtraction in this proposed work.

With its scalable and cost-effective solutions, cloud computing has taken center stage in modern data management. Nevertheless, this fast growth of cloud services comes with urgent data security and privacy-related dilemmas. In this paper, three novel algorithms are proposed to deal with the above-mentioned problem in the cloud environment, namely Improved Privacy- Preserved Data Security Approach (IPP-DSA), Multi-Authority Scheme Based Privacy Preserving Algorithm (MASPPA) and Anonymous Access-Based Privacy Preserving Algorithm (AABPPA). Key management efficiency is advocated by the new IPP-DSA with small key generating times which are expected to be short enough to run in steadily update phase. The MASPPA uses the multi-authority attribute-based encryption to realize fine-grained access control, and the encryption times are commensurate to its extensive security guarantee. The second is the AABPPA which is appropriate for situations where user anonymity is required, however is slower in computation times than the AABM but does really well in preserving privacy. This section presents the performance metrics, specifically the time taken for key generation, encryption, and decryption and collectively analyse the advantages and disadvantages of each algorithm. Our results show that the algorithms proposed, when compared to FT-RSA, provide very high security and privacy for applications ranging from low to high computational demands. We recommend additional optimizations to make them more effective in real-world applications.

Smart grid is an advanced electrical infrastructure that incorporates communication and information technologies to enable power firms and consumers to exchange data in bidirectional. However, there are serious security risks associated with relying on an unsecured open network. To overcome the drawbacks, an efficient HEAAN-PUF based IoT device authentication with SWO-QBFT for smart grid infrastructure has been proposed. Initially IoT device is registered and authenticated using Physical Unclonable Function (PUF) authentication, which provides a unique response for each device with an Interplanetary File System (IPFS). Homomorphic Encryption for Arithmetic of Approximate Numbers (HEAAN) cryptography algorithm was then utilized to generate the key for encrypting the data and stored in IPFS. Blockchain based on consensus algorithm as Spider Wasp Optimization (SWO) with Quorum Byzantine Fault Tolerance Protocol (SWO-QBFT) utilized to choose the best validators for secure data transmission and stored an IPFS hash address. Performance metrics-based analysis and comparison of the proposed HEAAN-OQBFT technique with existing approaches are conducted. Performance metrics like encryption and decryption times, key and block generation times, throughput, Packet Delivery Ratio (PDR), and Packet Loss (PL) are acquired in order to determine the performance of the proposed method. Time required for Block creation, encryption, decryption, and key generation takes up 0.19 ms, 0.013 ms, 0.023 ms and 0.93 ms with is 497 Kbps throughput, 1% packet loss, and 99% PDR. The metrics therefore clearly show that the proposed method successfully stores and secures smart grid data by integrating OQBFT with an effective HEAAN cryptography.

WITHDRAWN: Efficient Secure Aware Scheduling Model for Enhancing Security and Workflow Model in Cloud Computing

The Electronic Medical Documentations have gained vitality and are stated as the pillar of digital healthcare. It is the main platform to store and retrieve the information of patients. It possesses numerous benefits like cost minimization, few medical errors with better healthcare access and tracking. Though the advantages and adoption of EMD have been extensively stated, the challenges entangled with their usage persist, particularly with the safety and integrity of the patient’s data that are stored in the cloud. Conventional data sharing methods have been centralized and encountered problems of sole point-of-failure. Thus, a decentralized system is required where the blockchain concept comes into play. Moreover, protecting personal details from unauthorized entrée by guaranteeing data integrity is vital where cryptography gains its significance. Though traditional methods have used algorithms based on these concepts for secured EMD sharing, they lacked with regard for privacy and security. To rectify this problem, the objective of the present study proposes Modified-Advanced Encryption Standard based on the chaos random key generation. In a traditional AES system, a static key finds applicability which must be swapped in advance and assured to be maintained safely. Nevertheless, in the proposed model, a chaotic system’s synchronization technology is introduced wherein the static key turns random and dynamic which avoids the need to be maintained or transferred in any open channels. Besides, a Modified Digest hashing algorithm is also used with M-AES for feeding the encrypted text and hash into data blocks. Performance of the proposed merging technique encompassing a hybrid pattern from both patient ID and medical records is assessed about significant metrics for determining its efficiency. The overall model performance are estimated using various estimation parameters such as the execution time, decryption time, encryption time, memory consumption and usage rates and the time required for key generation. Findings of the proposed work deliberates that higher level of security are ensured, whereby a long-term protection are used, which intends to prevents adversaries from gaining a static target for prolonged attacks. Additionally, the security level of the proposed system performs better in terms of integrity, privacy, authentication, access control, and cryptographic function.

The development of digital world created advancement of technology, by which the data services are electronically transacted. Electronic voting is used to improve the election system in several ways. But technical issues associated with protection of data, is considered as a major concern leading to illegal activities and threats. Some of the conventional methods used in securing e-votes are matching finger prints of individual, control unit accessibility, which provides decreased capability of attaining proper authenticity and security. Even several cryptographic methods are used for data security, but produced limited accuracy. So, to improve the reliability and accuracy of data protection in e-voting, combination of AES (Advanced Encryption System) and RSA (Rivest, Shamir, Adleman) combined with blockchain technology is implemented. AES uses larger key size which makes the data privacy robust. But encryption and decryption time produces decreases computational speed. So, AES is combined with RSA, as it uses shorter key length and easy to implement with block-chain algorithm, it is deployed to decrease encryption and decryption time, thus producing highly sensitive data security. The performance of the system is validated by calculating the encryption and decryption time, block size and verification time of original data with output data.