Enhancing Security of AES Using Key Dependent Dynamic Sbox

Nowadays, a large number of digital data are transmitted worldwide using wireless communications. Therefore, data security is a significant task in communication to prevent cybercrimes and avoid information loss. The Advanced Encryption Standard (AES) is a highly efficient secure mechanism that outperforms other symmetric key cryptographic algorithms using message secrecy. However, AES is efficient in terms of software and hardware implementation, and numerous modifications are done in the conventional AES architecture to improve the performance. This research article proposes a significant modification to the AES architecture’s key expansion section to increase the speed of producing subkeys. The fork–join model of key expansion (FJMKE) architecture is developed to improve the speed of the subkey generation process, whereas the hardware resources of AES are minimized by avoiding the frequent computation of secret keys. The AES-FJMKE architecture generates all of the required subkeys in less than half the time required by the conventional architecture. The proposed AES-FJMKE architecture is designed and simulated using the Xilinx ISE 5.1 software. The Field Programmable Gate Arrays (FPGAs) behaviour of the AES-FJMKE architecture is analysed by means of performance count for hardware resources, delay, and operating frequency. The existing AES architectures such as typical AES, AES-PNSG, AES-AT, AES-BE, ISAES, AES-RS, and AES-MPPRM are used to evaluate the efficiency of AES-FJMKE. The AES-FJMKE implemented using Spartan 6 FPGA used fewer slices (i.e., 76) than the AES-RS.

The Rapid expansion of cloud computing with data-centric services makes the protection of sensitive information via confidentiality, integrity, and availability indeed one of the most critical challenges. This work introduces a unified framework that integrates the advanced encryption standard (AES) with end-to-end encryption (E2EE) to secure data processing and transmission in a cloud environment. The proposal addresses security vulnerabilities that arise from multi-tenancy, third-party management, and remote access by encrypting data at the source and keeping its confidentiality throughout its lifecycle while it exists in the cloud. By using AES-CBC mode and a robust key-management scheme, the system guarantees secure data transmission, storage, and access control. Experimental evaluation indicates that the integrated AES-E2EE model reduces latency in comparison to traditional HTTPS (230 MS) and standalone AES (200 MS) significantly reaching dimensions as small as 175 MS, paving way for use in latency-sensitive applications. The results validate scaling, efficiency, and protection from present cyber threats of the proposed framework development towards building secure and trustworthy cloud computing infrastructures.

Advanced Encryption Standard is a symmetric block cipher which is widely used in encrypting data by different organizations to make secure their data from being hacked.The only nonlinear part of Advanced Encryption Standard (AES) is S-Box (Substitution Box), which provides confusion in the algorithm.But the main limitation of the S-Box in AES is that it is a static one throughout the algorithm, which is the main center of attraction for the cryptanalyst to analysis the weakness for certain attacks.Since 2000 onwards a number of algebraic attacks on AES have been carried out, which challenged the security of AES.But at the same time till date a number of researches have being carried out for making AES more secure by using dynamic S-Boxes to provide more confusion to the cryptanalyst.In present paper we tried to address dynamic S-Box techniques and provide their analysis on the basis of S-Box properties, which are essential for secure S-Box construction like Non-linearity, XOR profile, Strict Avalanche criterion (SAC) and Bit independence criteria (BIC).Also these techniques are compared with the original AES results.

In today's digital landscape, the integration of mobile applications with server systems presents both opportunities and challenges in data management. This symbiotic relationship necessitates seamless synchronization between mobile devices and servers, particularly in scenarios where internet connectivity fluctuates. Strategies such as Data Storage Codification for Enhanced Optimization offer a solution, enabling robust data storage and retrieval processes that remain functional even in offline settings. By leveraging mechanisms such as cloud document servers and unique identifiers, organizations can ensure the secure transmission and tracking of data between mobile apps and servers, enhancing overall efficiency and user experience. Efficient management of server interactions and data storage on mobile devices is crucial for ensuring uninterrupted operation and data integrity. By implementing a meticulous system of request tracking and drafting in both mobile applications and servers, organizations can streamline the transmission of data, even in intermittent internet connectivity scenarios. Leveraging technologies such as pub-sub models facilitates efficient communication between mobile apps and servers, ensuring prompt acknowledgment and processing of requests, thereby enhancing overall system reliability and responsiveness. The seamless integration of mobile applications with server systems necessitates a strategic approach to data management, particularly concerning synchronization and tracking of requests. By adopting comprehensive strategies such as those outlined in the current thread, organizations can navigate the complexities of modern data management effectively. This entails leveraging cloud document servers, unique identifiers, and pub-sub models to facilitate secure and efficient transmission of data between mobile devices and servers, ultimately enhancing operational efficiency and user satisfaction.

The Consultative Committee for Space Data Systems (CCSDS) recommends AES algorithm as a cryptographic algorithm to maintain confidentiality and data security between spacecraft and ground systems. In implementation, there are several AES algorithm operating modes including Cipher-Block Chaining (CBC), Electronic Codebook (EBC), Cipher Feedback (CFB), Output Feedback (OFB), and counter mode (CTR). One of the operating modes of AES algorithm recommended by CCSDS is CTR because it has advantages in terms of efficiency of implementation and offers a high level of data security. LAPAN-A4 as the next generation of LAPAN satellites also uses CCSDS standard in terms of data exchange between satellites and ground stations including telemetry and telecommand (TTC) data and satellite payload data. In order to protect LAPAN-A4 satellite data, especially TTC data, in this paper AES algorithm was implemented in CTR operating mode on the FPGA which will then be implemented on LAPAN-A4 satellite onboard data handling (OBDH) as one of LAPAN-A4 satellite data security systems. To overcome the limited resource of FPGA, optimization is also done using basic iterative AES hardware reused method, which is to reuse hardware that has been designed n times for same operation for AES algorithm. From the results of implementation and optimization, efficiency of logic gates used is increasing almost a quarter less than the previous research.

The integration of Internet of Things (IoT) technology into agriculture has revolutionized farming practices by using connected devices and sensors to optimize processes and facilitate sustainable execution. Because most IoT devices have limited resources, the vital requirement to efficiently manage data traffic while ensuring data security in agricultural IoT solutions creates several challenges. Therefore, it is important to study the data amount that IoT protocols generate for resource-constrained devices, as it has a direct impact on the device performance and overall usability of the IoT solution. In this paper, we present a comprehensive study that focuses on optimizing data transmission in agricultural IoT solutions with the use of compression algorithms and secure technologies. Through experimentation and analysis, we evaluate different approaches to minimize data traffic while protecting sensitive agricultural data. Our results highlight the effectiveness of compression algorithms, especially Huffman coding, in reducing data size and optimizing resource usage. In addition, the integration of encryption techniques, such as AES, provides the security of the transmitted data without incurring significant overhead. By assessing different communication scenarios, we identify the most efficient approach, a combination of Huffman encoding and AES encryption, to strike a balance between data security and transmission efficiency.

Security has been a primary concern for each type of network to provide secure communication among the users of different types of network. Presently, many techniques are present for providing security in networks but Advanced Encryption Standard (AES) has been proved to be the most prominent, keeping the data security as the major factor in data transmission. In the presented exposition, a modified variant of AES algorithm named as Modified Advanced Encryption Standard (MAES) has been introduced for secure data transmission in wired and various wireless networks namely, MANET, VANET, and FANET. The proposed technique focuses on both prevention and detection of the security attacks on the network. Theoretically, it is difficult to break the security or crack the key in the assumed network. The proposed protocol takes 2256 computations as compared to the basic AES standard which take 232 in case of differential fault analysis. The simulation results show that the proposed MAES outperformed AES in terms of security against attacks such as side channel attacks.

Nowadays, with the development of Internet communication, multipath transfer technology has been widely used in heterogeneous network communication. Multipath transfer technology enables efficient data transmission through multiple transmission paths to achieve the effect of aggregated bandwidth. However, traditional anonymous communication networks, such as Tor, I2P, etc., are single streams of data transmission. In the process of data transmission, it is easy to become the target of attacker’s listening, which makes the data easy to be damaged or even intercepted by the attacker, and cannot realize the requirement of secure, efficient and reliable data transmission. Therefore, this paper proposes an anonymous multipath transfer method based on data network coding. First, in the paper we propose a mathematical model for coding based on a circulant matrix. This model is about 80% more efficient in coding flexibility and coding/decoding efficiency compared with Galois Field (GF), and the redundant coding can tolerate 50% of packet loss. Second, a new multipath transfer mechanism is proposed in combination with data network coding, which can effectively avoid anonymity attacks. Finally, through simulation experimental tests, the results show that the method can effectively improve the reliability of data transmission in anonymous communication networks.

The Internet of Medical Things (IoMT) is reforming healthcare by enabling interconnected medical devices and systems to facilitate efficient data collection, transmission, and analysis. While IoMT has significantly improved real-time monitoring and personalized care, the transmission of high-resolution medical images remains a challenge due to bandwidth constraints, latency issues, data loss, and computational overhead. Efficient and secure medical image transmission is critical to ensuring reliable diagnostics and timely patient care in this ecosystem. This research presents an optimized Deep Learning (DL) architecture developed to overcome the limitations of medical image transmission in IoMT environments. The proposed solution incorporates Convolutional Neural Networks (CNNs) for spatial feature extraction and dimensionality reduction while preserving diagnostic-critical information, and Long Short-Term Memory (LSTM) networks to manage sequential data and mitigate transmission issues such as packet loss and latency. The framework incorporates robust encryption mechanisms to ensure data security without significantly increasing computational overhead. Once predictions are made, the data is securely transferred to the cloud for further analysis and storage. Furthermore, Hippopotamus Optimization is utilised to enhance the model's performance and fine-tune hyperparameters, improving both efficiency and accuracy. Performance evaluations were conducted using real-world medical image datasets under varying IoMT network conditions. The results demonstrate that the proposed CNN-LSTM framework delivers superior performance across key metrics, like Peak Signal-to-Noise Ratio (PSNR), accuracy, F1 score, specificity, and sensitivity. Additionally, the framework optimizes encryption and decryption times and reduces bandwidth consumption, ensuring efficient and secure data transmission. This approach showcases a significant advancement in IoMT-based medical imaging, paving the way for enhanced reliability and efficiency in healthcare delivery systems.

The wide acceptability of Advanced Encryption Standard (AES) as the most efficient of all of the symmetric cryptographic techniques has further opened it up to more attacks. Efforts that were aimed at securing information while using AES is still being undermined by the activities of attackers This has further necessitated the need for researchers to come up with ways of enhancing the strength of AES. This article presents an enhanced AES algorithm that was achieved by modifying its SubBytes and ShiftRows transformations. The SubBytes transformation is modified to be round key dependent, while the ShiftRows transformation is randomized. The rationale behind the modification is to make the two transformations round key dependent, so that a single bit change in the key will produce a significant change in the cipher text. The conventional and modified AES algorithms are both implemented and evaluated in terms avalanche effect and execution time. The modified AES algorithm achieved an avalanche effect of 57.81% as compared to 50.78 recorded with the conventional AES. However, with 16, 32, 64, and 128 plain text bytes, the modified AES recorded an execution time of 0.18, 0.31, 0.46, and 0.59 ms, respectively. This is slightly higher than the results obtained with the conventional AES. Though a slightly higher execution time in milliseconds was recorded with the modified AES, the improved encryption and decryption strength via the avalanche effects measured is a desirable feat.

Security is major concern in data handling, communication, message transmission and electronic transaction on public network. Cryptography (secret writing) is the encryption process of transformation of messages to make information secure and resistant to attack. AES is symmetric encryption standard recommended by NIST. AES is proved to be highly secure, faster and strong encryption algorithm. AES is used commonly because of its great competence and easiness. But in recent years cyber-attacks are continuously developing, therefore security specialists must stay busy in the lab inventing new schemes to keep attackers at bay. Possible attacks on symmetric algorithm can be Brute-force Attack, Differential Attack, Algebraic Attack and Linear Attack. So to provide strong security in message transmission, AES algorithm with hybrid approach of Dynamic Key Generation and Dynamic S-box Generation is proposed. In hybrid approach first we will add more complexity in data to increase Confusion and Diffusion in Cipher text by using Dynamic Key Generation and then by using Dynamic S-Box Generation we will make it difficult for attacker to do any down study of static set of S-box.

In the rapidly growing domain of wireless communication, data security has emerged as a critical requirement, especially in resource-constrained embedded systems. This paper proposes a secure wireless communication system based on ZigBee technology and Advanced Encryption Standard (AES), implemented using Arduino microcontrollers. The system comprises a transmitter that accepts data via a keyboard, encrypts it using AES-128, and transmits it wirelessly via ZigBee. The receiver decrypts the data and displays it on an LCD. Leveraging ZigBee’s low-power and low-data-rate characteristics, the design ensures secure, efficient, and scalable communication suitable for applications such as home automation, military systems, and industrial control. The integration of AES encryption ensures end-to-end data confidentiality without significantly impacting transmission speed or energy consumption. Performance evaluation confirms the system’s viability for Internet of Things (IoT) applications demanding both security and efficiency. Keywords: Wireless Communication, ZigBee Protocol, AES-128 Encryption, Arduino Microcontroller, Secure Data Transmission, End-to-End Encryption.

A modified XXTEA “M-XXTEA” symmetric block cipher that has a simple construction compared to the advanced encryption standard (AES) is proposed. It is efficient for protecting limited-resource devices such as IoT smart devices. The M-XXTEA will be able to achieve confidentiality during transmission of data over the internet. Since the original XXTEA was vulnerable against key-related and chosen-plaintext attacks. Therefore, this paper introduces a new and robust version of the original XXTEA by employing an improved S-box to enhance security to overcome such types of attacks. Besides, the M-XXTEA is coupled with a chaotic key generator system adding a layer of security achieving the idea behind the one-time pad. The cipher keys are dynamically changing for each block of plaintext when encrypted. Thus, it provides a more robust security mechanism than the original XXTEA and the AES. Besides enhancing data security, the M-XXTEA can function with different sizes of text blocks and with different key sizes. Several experiments are implemented to compare the performance of the M-XXTEA with the original XXTEA and with the AES. Results show that the M-XXTEA encryption and decryption time efficiencies outperform AES by 60%. Besides, the M-XXTEA achieves speed efficiency 57% better than the AES. It can be used efficiently for protecting IoT smart devices in the industry, and e-health systems, and smart cities.

Serverless computing has gained widespread popularity due to its rapid deployment, elastic scaling, and pay-as-you-go advantages. Large-scale pipeline applications designed for big data processing, video analytics, and machine learning are gradually evolving toward the serverless architecture. However, the inefficiency of large data transmission among functions has limited the further adoption of the serverless paradigm in these applications. With the emergence of capability Instruction Set Architecture (ISA), the multi-tenant security isolation model and data transmission methods in the cloud have ushered in new opportunities. This paper proposes Hummer, an efficient communication and data transmission scheme based on the capability ISA. The capability ISA allows multiple functions to run in separate isolation domains in a single address space. Function instances can efficiently share memory by directly passing hardware capabilities. This paper extends the CHERI capability ISA, introducing the novel shared capability and shared capability store tracking (SCST) mechanism to manage the shared memory access rights, enabling a zero-copy communication mechanism. We compare Hummer with existing communication mechanisms and show that it improves data transmission rate by 6 – 40 ×. Redis implemented with Hummer APIs doubles its throughput.

The secure transmission of large-scale data has attracted more and more attention. In the widely recognized security protocol TLSv1.3, the only algorithms that support large-scale data en-/decryption are ChaCha20 and the Advanced Encryption Standard (AES). Although AES has a higher usage rate, ChaCha20 still has the advantage of speed and security on many platforms, and has a better performance against post-quantum attacks. However, for a CPU/GPU platform, compared to the AES algorithm, no work has fully described the application scheme of ChaCha. This paper proposes an optimization scheme to optimize the performance of the ChaCha20 algorithm on a CPU/GPU platform. On a CPU platform, we provide a parallelization implementation that is better than that of OpenSSL. On a single GPU, our implementation of ChaCha20 achieves peak throughput of 211.41GB/s, which is better than any previous implementation of ChaCha20 and AES algorithms on GPU. More importantly, we are the first to detail the optimization of ChaCha on GPU. When considering the interconnection between CPU and GPU, we use the 87.76% peak bidirectional bandwidth of a PCIe channel. Finally, we also provide a scheme for the application of ChaCha20 on a CPU/GPU platform.