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Background: The technological revolution has allowed users to exchange data and information in various fields, and this is one of the most prevalent uses of computer technologies. However, in a world where third parties are capable of collecting, stealing, and destroying information without authorization, cryptography remains the primary tool that assists users in keeping their information secure using various techniques. Blowfish is an encryption process that is modest, protected, and proficient, with the size of the message and the key size affecting its performance. Aim: the goal of this study is to design a modified Blowfish algorithm by changing the structure of the F function to encrypt and decrypt video data. After which, the performance of the normal and modified Blowfish algorithm will be obtained in terms of time complexity and the avalanche effect. Methods: To compare the encryption time and security, the modified Blowfish algorithm will use only two S-boxes in the F function instead of the four used in Blowfish. Encryption and decryption times were calculated to compare Blowfish to the modified Blowfish algorithm, with the findings indicating that the modified Blowfish algorithm performs better. Results: The Avalanche Effect results reveal that normal Blowfish has a higher security level for all categories of video file size than the modified Blowfish algorithm, with 50.7176% for normal Blowfish and 43.3398% for the modified Blowfish algorithm of 187 kb; hence, it is preferable to secure data and programs that demand a high level of security with Blowfish. Conclusions: From the experimental results, the modified Blowfish algorithm performs faster than normal Blowfish in terms of time complexity with an average execution time of 250.0 ms for normal Blowfish and 248.4 ms for the modified Blowfish algorithm. Therefore, it can be concluded that the modified Blowfish algorithm using the F-structure is time-efficient while normal Blowfish is better in terms of security.

The increasing development of the internet of things (IoT) has made cloud-based storage systems essential for storing, processing, and sharing IoT data. Ensuring cloud security is crucial as it manages a large volume of sensitive and outsourced data vulnerable to unauthorized access. This research proposes an improved blowfish algorithm and modular encryption standard (IBA-MES) for secure and efficient data storage in cloud-based IoT systems. The block cipher structure in IBA enables scaling for different data sizes, ensuring secure data handling across a wide range of IoT devices. Additionally, IBA-MES adaptability helps maintain data integrity, enhancing both the security and efficiency of data storage in cloud-based IoT environments. Modular encryption standard (MES) reduces latency during encryption operations, ensuring quick data transactions between the cloud server and IoT devices. By combining blowfish’s speed and strength with modular encryption’s adaptability, IBA-MES provides robust data protection. Metrics such as execution time, central processing unit (CPU) usage, encryption time, decryption time, runtime, and latency are calculated for the proposed IBA-MES. For 700 blocks, the IBA-MES achieves encryption and decryption times of 270 and 415 ms, respectively, outperforming the triple data encryption standard (TDES).

Nowadays, Internet of Things (IoT) based applications are widely used in different sectors because of their high mobility, low cost, and efficiency. However, the wide usage of these applications leads to various security issues. Several security applications exist for protecting multimedia data, but the appropriate confidential range is not met due to the multi-variant features. Hence, the novel hybrid Elman Neural-based Blowfish Blockchain Model has been developed in this article to secure IoT healthcare multimedia data. Here, the Elman network features provided continuous monitoring for predicting malicious events in the trained multimedia data. In addition, the crypto analysis was performed to enhance the confidentiality rate by hiding the raw data from third parties. The presented model was verified using python software. Furthermore, the robustness of the developed model is validated with a crypt analysis by launching attacks. Finally, the outcomes were estimated and compared with the existing techniques in terms of Encryption time, decryption time, execution time, error rate and confidential rate. Here, the evaluation database is the multimedia data, which is high in data size. Henceforth, the performance of the security model for securing multimedia data depends on time. Considering this, the time evaluation is measured in three classes: encryption, decryption and execution. The comparative analysis proves that the developed model achieved better results than others.

Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item. From ancient times to the present, the security of secret or vital information has always been a significant problem. The development of secure communication methods that keep recipient-only data transmissions secret has always been an area of interest. Therefore, several approaches, including steganography, have been developed by researchers over time to enable safe data transit. In this review, we have discussed image steganography based on Discrete Cosine Transform (DCT) algorithm, etc. We have also discussed image steganography based on multiple hashing algorithms like the Rivest–Shamir–Adleman (RSA) method, the Blowfish technique, and the hash-least significant bit (LSB) approach. In this review, a novel method of hiding information in images has been developed with minimal variance in image bits, making our method secure and effective. A cryptography mechanism was also used in this strategy. Before encoding the data and embedding it into a carry image, this review verifies that it has been encrypted. Usually, embedded text in photos conveys crucial signals about the content. This review employs hash table encryption on the message before hiding it within the picture to provide a more secure method of data transport. If the message is ever intercepted by a third party, there are several ways to stop this operation. A second level of security process implementation involves encrypting and decrypting steganography images using different hashing algorithms.

Since medical images include sensitive patient information, security is the top priority during transmission. In addition to protecting patient data from potential criminals, security helps to confirm the field staff’s identity. However, many medical institutions still need to adopt advanced security measures. In this paper, a new dual encryption method is proposed that implements blowfish and signcryption in a certificateless generalized form. The proposed method has an advantage over other methods due to its computational cost-effectiveness and speed. The performance measurements used to assess a proposed strategy’s effectiveness are PSNR, entropy, MSE, correlation coefficient (CC), and time taken. We obtain a high PSNR value of 57.72 and a low time requirement of 42 seconds on average. Combining blowfish and certificateless signcryption iTqnto one double encryption scheme that is computationally secure, fast, and easy to implement. It would help push hospitals toward a cost-effective image security environment.

Cloud computing is currently playing an important role in the information technology industry because of its improved efficiency, wide access, low cost, and many benefits. It also provides more space for storing data and transmitting data from one location to another faster for different users on the Internet. Due to large storage, cloud customers can save huge capital investment on IT infrastructure and focus on their own core business. Therefore, many companies or organizations are moving their business to the cloud. However, many customers are reluctant to use the cloud due to security and privacy concerns. To tackle this problem, in this paper, efficient secure data retrieval is developed with the help of multi-stage authentication (MSA) and optimized blowfish algorithm (OBA). The proposed system consists of three modules namely, MSA, data security, and data retrieval. Initially, the cloud users register their information on cloud based on a multi-authentication procedure. After the registration process, the data are encrypted with the help of OBA. To increase the security of the system, the key value is optimally selected with the help of a binary crow search algorithm. After the encryption process, MSA based data retrieval process is performed. This will avoid, un-authorized person to attack the data. The performance of the proposed methodology is implemented in JAVA and performances are analyzed in terms of different metrics.

Studies previously attempted to replace these two states with four (0, 1, 2, 3) for increasing key space, which is not perfect works for making algorithm more strong against attcks [11], as described in the following section. [...]in this study, we focus on the weak points of XOR by replacing it with a new # operation with variable block bit sizes (n): (1 or 2 or 4 or 8) instead of one block size. [...]the evaluation computations for every round also includes only five operations. In 2009 [11], researchers combined the curve security methods using the B-spline curve with quantum cryptography concepts to increase security and key space. [...]this modification on the base protocol focused on the manipulation of the bits in the message by replacing the original XOR operation with a new hash operation. In 2011, a new modification was introduced in [19] to increase the security and key space of Blowfish by replacing the predefined XOR operation applied in each round of the standard Feistel algorithm with a modified bit process of a new hash operation based on two keys.

Storing data in a third party cloud system causes serious problems on data confidentiality. Generally, encryption techniques provide data confidentiality but with limited functionality, which occurs due to unsupported actions of encryption operation in cloud storage space. Hence, developing a decentralized secure storage system with multiple support functions like encryption, encoding, and forwarding tends to get complicated, when the storage system spreads. This paper aims mainly on hiding image information using specialized steganographic image authentication (SSIA) algorithm in clustered cloud systems. The SSIA algorithm is applied to virtual elastic clusters in a public cloud platform. Here, the SSIA algorithm embeds the image information using blowfish algorithm and genetic operators. Initially, the blowfish symmetric block encryption is applied over the image and then the genetic operator is applied to re-encrypt the image information. The proposed algorithm provides an improved security than conventional blowfish algorithm in a clustered cloud system.

With the rapid proliferation of digital images on the internet, the task of preserving image ownership and ensuring the detection of unauthorized alterations has become increasingly challenging. This study introduces a robust algorithm, leveraging Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), and Blowfish encryption techniques, designed to maintain copyright integrity and detect image tampering. The proposed algorithm operates on a given RGB host image, first isolating it into its constituent red, green, and blue components. For the purpose of copyright protection, the algorithm applies DWT and DCT to the green component, embedding a watermark logo within it. The blue component is subjected to Blowfish encryption, generating a ciphered blue component that aids in tampering detection. Subsequently, the least significant bits of this ciphered blue component are interchanged with those of the host image's red component, producing a novel red component. This process results in the creation of a watermarked green component, an original blue component, and a newly formed red component. These are then amalgamated to produce the final watermarked image. The proposed method is evaluated using five standard images, with simulation results demonstrating its resilience to various attacks. Importantly, the algorithm exhibits a capacity to detect any unauthorized modifications up to a granularity of 2 x 2 pixels.