AES-GCM Research Articles

Evaluations of Crypto-System AES Using Multiple Bloc Ciphering Mode

Cryptography, a scientific field that has existed even before the beginning of computer science. This article looks at the development symmetric crypto-system, which falls within the framework of image security, by Advanced Encryption Standard (AES- Advanced Encryption Standard) algorithms. AES algorithm is not integrity protected. Cryptanalysis could use modified encrypted image of each ciphered bloc for generating oracle and getting the key. A new crypto-system uses hash function named AES-GCM (Advanced Encryption Standard-) for solving this problem. Using Galois Counter Mode (GCM) combined with Secure Hash Algorithm 256 bits (SHA-256) or BLAKE2s hash function, the old mode of ciphering like: Cipher FeedBack (CFB), Output FeedBack (OFB), Cipher Block Chaining (CBC), Electronic Codebook Block (ECB) and CounTeR (CTR) mode encryption, will increase the security level at confidentiality and integrity. In this article, robustness of the crypto-system will be evaluated by multiple criteria, indeed the statistical analysis, sensitivity measurement and performance measurement. For the statistical analysis, the histogram is flat and the correlation between adjacent pixel is not linear for the encrypted image. The relation between clear image and encrypted image doesn’t exist. For the sensitivity analysis, Number of Pixel Changing Rate (NPCR) and Unified Averaged Changed Intensity (UACI) permit to avoid differential attack of the crypto-system. The two values are respectively near 99% and 30%. For performance measurement, the similarity of the decrypted image and original image will be tested. The Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are equals of infinity and zero. The decrypted image and original image are the same. The integrity of the image on the crypto-system will be evaluated by modifying one bit of the encrypted image. The decryption process doesn’t give decrypted image and show that the tag value is incorrect.

Redefining GCM’s resistance to cryptanalysis with offset mechanisms

The research paper proposes an enhancement to the Galois/Counter Mode (GCM) of authenticated encryption by introducing an “offset” mechanism. This modification aims to improve privacy and resist differential cryptanalysis without significantly impacting the mode’s efficiency and simplicity. The improved GCM maintains its original features, such as minimal block cipher invocations, the use of a single cryptographic key, and efficient offset computation. It provides a detailed analysis of the operational framework, including the integration and calculation of offsets in encryption and decryption processes. By complicating the predictability of differential cryptanalysis through unique offsets, the paper asserts this enhancement significantly increases GCM’s security within a concrete security model. The discussion emphasizes the benefits of the offset-enhanced GCM over other modes, highlighting its suitability for high-speed, parallelizable cryptographic applications while bolstering resistance against cryptanalytic attacks.

Security enhancement of cyber-physical system using modified encryption AESGNRSA technique

<span>A cyber-physical system (CPS) is a combination of physical components with computational elements to interact with the physical world. The integration of these two systems has led to an increase in security concerns. Traditional encryption algorithms designed for general-purpose computing environments may not adequately address the distinct challenges of CPS, such as limited processing power, delay, and resource-constrained hardware. Therefore, there is a pressing need to develop an encryption algorithm that is optimized for CPS security without compromising the critical real-time aspects of these systems. This research has designed a modified encryption technique named the advanced encryption standard in galois counter mode with nonce and rivest-shamir-adleman algorithm (AESGNRSA). A smart medical system is designed to monitor the health of remotely located patients. The AESGNRSA algorithm is applied to the three servers of this system. The data of 1.5 lakh patients is fed to this system to verify the effectiveness of the AESGNRSA algorithm. The performance parameters like encryption and decryption time, encryption and decryption throughput, and encrypted file size are calculated for the AESGNRSA algorithm. The comparative analysis proved that AESGNRSA has the highest performance as compared to other algorithms and it can protect CPS against many cyber-attacks.</span>

Description, Implementation and Performance/Security Analysis of ASCON128

The aim of the report is to introduce detailed description of the functioning of and to provide an efficient implementation (using bit-sliced implementation of S-Box) in C of encryption, decryption and authentication of the lightweight authenticated encryption algorithm ASCON 128 (sponge based SPN network based on Keccak like operations) as per the v 1.2 submitted to NIST. This is achieved using a sponge construction by setting up initialization state and performing 12 rounds of permutations, XORing consecutively the plaintext blocks (encryption) or ciphertext blocks (decryption) with first 64 bits of the state (after 6 rounds of sponge permutations) and after all consecutive operations on ciphertext/plaintext blocks, XORing the last 128 bits of the resultant state with the secret Key (after 12 rounds of final permutation operations) to produce/re-create the tag. Discussions on Key Features, Performance Analysis (comparison of ASCON 128 v/s AES 128 in GCM mode on our own PC), Performance Comparisons with other NIST lightweight cryptography contest finalists on ARM Cortex M3, and discussions on the Security Analysis (side channel attacks: fault injection and power analysis) of ASCON are included in this report.

Integration of an RSA-2048-bit public key cryptography solution in the development of secure voice recognition processing applications

The authors initially employs the fast Fourier transform (FFT) approach to transforming voice inputs into digital signals before integrating a speech recognition solution (which includes two models: the hidden Markov model (HMM) and the artificial neural network (ANN)). To achieve standard-tone identification of voice signals and digitally store speech, the authors then incorporated a 2048-bit Rivest-Shamir-Adleman (RSA) encryption method to encrypt and decrypt digital speech. The authors’ building team constructed the program using a 256-bit advanced encryption standard - Galois counter mode (AES-GCM) encryption method to assure the application’s effectiveness. The authors successfully created a voice recognition application according to the HMM of ANN. The collected findings suggest that the authors’ secure speech recognition program (named soft voice - RSA) has improved in terms of safety, keeping speech material secret, and speed. It takes roughly 0.2 s to generate a 2048-bit RSA key pair that exceeds the National Institute of Standards and Technology (NIST) standard, 700-1070 ms to process speech, 1-4 ms to encrypt 2048-bit RSA, 6-8 ms to decrypt 2048-bit RSA.

A Secure Deduplication Technique for Data in the Cloud

The tremendous growth of digital data in cloud storage systems is a critical issue, as many duplicate data in storage systems cause extra load. Cloud Service Providers (CSPs) often employ Data Deduplication techniques to eliminate redundant data and store only one copy of data to save storage space and reduce transmission costs. Data Deduplication is mostly effective when multiple clients outsource the same data to cloud storage, but it raises security and ownership issues. This paper proposes a secure, Proof of Ownership (PoW)-based Data Deduplication scheme that has a low communication overhead and ensures that only valid cloud clients can download and decrypt ciphertext from cloud storage. The Advanced Encryption Standard (AES) is used as the encryption algorithm in the proposed scheme. It utilizes two modes of AES encryption, namely, Cipher Block Chaining (CBC) and Galois Counter Mode (GCM), with single-threading and multi-threading to upload and download ciphertext between the client and the server to measure the effect of upload and download times. We present a new approach for PoW to reduce communication overhead. PoW enables owners of the same data to prove to the cloud server that they own the data in a robust way. The comparison between CBC and GCM is implemented in a Java environment with two scenarios: single-threading and multi-threading. The simulation results show that AES-GCM with multi-threading is better during the uploading and downloading times

Lightweight and flexible hardware implementation of authenticated encryption algorithm SIMON‐Galois/Counter Mode

SummaryThis brief proposes a new lightweight authenticated encryption algorithm SIMON‐GCM for Internet of Things (IoT) security, which realizes the combination of SIMON block cipher and Galois/Counter Mode (GCM). The designed SIMON circuit supports 128/192/256‐bit key size, which improves the flexibility and enlarges the range of applications. Moreover, the scheme of 32‐cycle Galois field (GF) multiplier in GF(2128) is adopted to effectively reduce the hardware cost of the Galois Hash (GHASH) function in GCM. At the same time, a finite state machine (FSM) is used to run the SIMON and GHASH modules in parallel, thus shortening the authenticated encryption time. The whole circuit is designed and implemented in field programmable gate array (FPGA) platforms. It is measured to yield a throughput of 32.4 Gbps when consuming 331 slices in Artix‐7. Compared with the existing authenticated encryption algorithms, the proposed algorithm achieves lower resource consumption and better flexibility.

A Single-Pass and One-Round Message Authentication Encryption for Limited IoT Devices

In this work, we propose three efficient variants of a message authentication encryption (MAE) algorithm, which is based on the dynamic key-dependent concept and dynamic operation mode to reach a high level of security. These variants consist of a single pass and a single round, in addition to the use of common operations for the encryption and authentication processes to reduce the required execution time and resources. Accordingly, the proposed scheme outperforms the existing solutions that are based on the static approach with multiple rounds. Furthermore, to reduce the overhead associated with the regeneration of the dynamic key and the corresponding cryptographic primitives, we propose a simple, yet effective update process. In such a scheme, even when the same plaintext is processed, it will be encrypted and authenticated using different cryptographic primitives (substitution and permutation tables in addition to round keys), which guards against the existing cryptanalysis techniques. The experimental results show that the proposed MAE variants are more efficient than the counter with cipher block chaining message authentication code (CCM), Galois message authentication code (GMAC), offset codebook mode (OCB), and the Chacha20-poly1305. The best performance is achieved with the third MAE variant that presents a high throughput with an enhancement of at least 373% compared to CCM, 90% compared to GCM, 23% compared to OCB, and 22% compared to Chacha20-poly1305.

A Novel Secure End-to-End IoT Communication Scheme Using Lightweight Cryptography Based on Block Cipher

Personal data security is a cybersecurity trend that has captured the world’s attention. Governments, practitioners and academics are jointly building personal data security in various communication systems, including IoT. The protocol that is widely used in IoT implementation is MQTT. By default, MQTT does not provide data security features in the form of data encryption. Therefore, this research was carried out on the design of Secure End-to-End Encryption MQTT with Block Cipher-Based Lightweight Cryptography. The protocol is designed by utilizing the Galantucci secret sharing scheme and a lightweight cryptographic algorithm based on a block cipher. The algorithms used include AES-128 GCM mode, GIFT-COFB, Romulus N1, and Tiny JAMBU. We tested the Secure End-to-End for MQTT protocol on the ARM M4 and ESP8266 processors. Our testing results on NodeMCU board, Tiny JAMBU have an average encryption time of 313 μs and an average decryption time of 327 μs. AES-128 GCM mode has an average encryption time of 572 μs and an average decryption time of 584 μs. GIFT-COFB has an average encryption time of 1094 μs and an average decryption time of 1110 μs. Meanwhile, Romulus N1 has an average encryption time of 2157 μs and an average decryption time of 2180 μs. On STM32L4 discovery, Tiny JAMBU had average encryption of 82 μs and an average decryption time of 85 μs. AES-128 GCM mode has an average encryption time of 163 μs and an average decryption time of 164 μs. GIFT-COFB has an average encryption time of 164 μs and an average decryption time of 165 μs. Meanwhile, Romulus N1 has an average encryption time of 605 μs and an average decryption time of 607 μs. Our experiment shows that the fastest performance is produced by Tiny JAMBU, followed by AES-128 Mode GCM, GIFT-COFB and Romulus N1.

An Ultra-Fast Authenticated Encryption Scheme with Associated Data Using AES-OTR

Applications relying on the Ethernet IEEE 802.3ba and IEEE802.3b standards require secure data encryption and authentication at extremely high speeds (at least 100 Gbit/s). The Galois/Counter Mode (GCM) is currently considered the de facto standard for hardware high-speed authenticated encryption, although other algorithms have been proposed in the literature such as the Offset Codebook Mode (OCB). The challenge in terms of providing security for high-speed applications is to achieve implementations that explore the parallelism of these algorithms; however, this translates into area cost. In this work, we propose an alternative to GCM and OCB. We show that a combination of the Offset Two-Round authenticated-encryption scheme with the AES block cipher (known as AES-OTR) is exceptionally well suited for exploiting fine-grained parallelism, and can therefore be used to achieve ultra-high-speed data encryption rates. The experiments reported in this paper show that our pipeline-parallel implementation of AES-OTR outperforms the GCM and OCB schemes in terms of throughput per area while using almost half of the logic resources. Our implementation used a Stratix 4 FPGA device as well as several devices from the Virtex family. Implementations of AES-OTR on Stratix 4 used 11kALMs and achieved a throughput of 143.65 Gbit/s. On the Virtex Ultrascale, our design used 31,859 LUTs with a throughput of 204.92 Gbit/s.

VLSI Design of Advanced-Features AES Cryptoprocessor in the Framework of the European Processor Initiative

This article presents a cryptographic hardware (HW) accelerator supporting multiple advanced encryption standard (AES)-based block cipher modes, including the more advanced cipher-based MAC (CMAC), counter with CBC-MAC (CCM), Galois counter mode (GCM), and XOR-encrypt-XOR-based tweaked-codebook mode with ciphertext stealing (XTS) modes. The proposed design implements advanced and innovative features in HW, such as AES key secure management, on-chip clock randomization, and access privilege mechanisms. The system has been tested in a RISC-V-based system-on-chip (SoC), specifically designed for this purpose, on an Ultrascale + Xilinx FPGA, analyzing resource and power consumption, together with system performances. The cryptoprocessor has been then synthesized on a 7-nm CMOS standard-cells technology; performances, complexity, and power consumption information are analyzed and compared with the state of the art. The proposed cryptoprocessor is ready to be embedded within the innovative European Processor Initiative (EPI) chip.

A Novel NFC-Based Secure Protocol for Merchant Transactions

The unprecedented growth of mobile applications promoted the usage of these mobile applications for payments. The current research works in mobile payments and commerce are prone to reverse-engineering attacks and lacked transport layer protection, so these research works do not ensure security. Therefore, such attacks on Mobile Payment Applications (MPA) will be successful, which leads to severe financial loss. To address these issues, we propose a secure framework incorporating a defense-in-depth approach for Near Field Communication (NFC) based mobile payment frameworks. Our defense-in-depth approach has three levels, i.e., Defense at hardware, mobile application, and communication level. We have proposed a NFC based Secure Protocol for Mobile Transaction (NSPMT) protocol and successfully verified a mobile payment protocol with BAN (Burrows, Abadi, and Needham) logic and Scyther tool, and our proposed protocol overcome multi-protocol attack, RAM (Random Access Memory) scrapping attack, DOS (Denial Of Service), DDOS (Distributed Denial Of Service), and Phlashing attacks. Our proposed mobile Payment system overcomes the known mobile application vulnerabilities, including Heartbleed and ROBOT (Return Of Bleichenbacher’s Oracle Threat). Our proposed protocol ensures all the security properties and the energy and communication cost and computational cost are far less than the existing works in the literature. Finally, we have successfully implemented our protocol using kotlin language in Android Studio, with two Mobile Payment Applications (MPA) and POS Payment Application (PPA), Elliptic Curve Digital Signature Algorithm (ECDSA) is used and Advanced Encryption Standard (AES) with GCM (Galois/Counter Mode) mode is used for encryption and decryption of Customer Payment Data at MPA and PPA.

A Secure and Robust Architecture based on Mobile Healthcare Applications for Patient Monitoring Environments

The recent outbreak of COVID-19 pandemic realized the importance of patient monitoring environments, Mobile Healthcare Applications (MHA) plays very crucial role in the successful implementation of patient monitoring environments. Existing MHA’s in the realm of patient monitoring environments are prone to repackaging attacks; do not ensure security, application security and communication security. This paper proposes a secure and robust architecture for mobile healthcare applications in patient monitoring environments ensuring end to end security ensuring all the security properties by overcoming repackaging attacks which are very vital for success of mobile healthcare applications. We implemented our proposed protocol in Android Studio, Kotlin is designed to interoperate fully with Java. ECDH Key exchange algorithm is used for key exchange between MHA in patient’s smart phone and MHA in the hospital TPM. We created an EC key pairs (NIST P-256 aka secp256r1) at patient’s MHA and MHA of hospital TPM by using ECDH and we created a shared AES secret key. AES with GCM mode used for encryption and decryption of patient data.

A Secure Encrypted Classified Electronic Healthcare Data for Public Cloud Environment

The major operation of the blood bank supply chain is to estimate the demand, perform inventory management and distribute adequate blood for the needs. The proliferation of big data in the blood bank supply chain and data management needs an intelligent, automated system to classify the essential data so that the requests can be handled easily with less human intervention. Big data in the blood bank domain refers to the collection, organization, and analysis of large volumes of data to obtain useful information. For this purpose, in this research work we have employed machine learning techniques to find a better classification model for blood bank data. At the same time, it is vital to manage data storage requirements. The Cloud offers wide benefits for data storage and the simple, efficient technology is adapted in various domains. However, the data to be stored in the cloud should be secured in order to avoid data breaches. For this, a data encryption module has been incorporated into this research work. The combined model provides secure encrypted classified data to be stored in the cloud, which reduces human intervention and analysis time. Machine learning models such as Support Vector Machine (SVM), Multinomial Naive Bayes (MNB), Decision Tree (DT), Random Forest (RF), Gradient Boosting (GB), K-Nearest Neighbor (KNN) are used for classification. For data security, the Advanced Encryption Standard with Galois/Counter Mode (AES–GCM) encryption model is employed, which provides maximum security with minimum encryption time. Experimental results demonstrate the performance of machine learning and encryption techniques by processing blood bank data.

Encrypted e-Voting System using IoT

Abstract: Elections make a fundamental contribution to democratic governance but a lack of trust among citizens on their electoral system is a hindrance to satisfy the legal requirements of legislators. Even the world’s largest democratic countries suffer from issues like vote rigging, election manipulation and hacking of the electronic voting machines in the current voting system. To provide data security for e-Voting systems, the advanced encryption standard (AES) algorithm has been proposed, but traditional AES gives the same ciphertext for every similar pair of key and plaintext. So, to eliminate these disadvantages, AES in Galois-counter mode (GCM) has been used to obtain different ciphertexts all the time by using Initialization Vector. The fingerprint data from each user is verified using Internet of Things (IoT) based Biometric system which also helps to avoid Plural Voting. The whole data is encrypted and stored in the cloud, and it can be decrypted by authorized personnel to obtain the final vote count. So, the proposed model will enhance transparency and maintain anonymity of the voters alongside providing an easily accessible secured voting system. Keywords: Advanced encryption standard, initialization vector, additional authenticated data, galois-counter mode, biometrics, security, ciphertext, authtag

Security Provisioning and Compression of Diverse Genomic Data based on Advanced Encryption Standard (AES) Algorithm

Compression of genomic data has gained enormous momentum in recent years because of advances in technology, exponentially growing health concerns, and government funding for research. Such advances have driven us to personalize public health and medical care. These pose a considerable challenge for ubiquitous computing in data storage. One of the main issues faced by genomic laboratories is the 'cost of storage' due to the large data file of the human genome (ranging from 30 GB to 200 GB). Data preservation is a set of actions meant to protect data from unauthorized access or changes. There are several methods used to protect data, and encryption is one of them. Protecting genomic data is a critical concern in genomics as it includes personal data. We suggest a secure encryption and decryption technique for diverse genomic data (FASTA / FASTQ format) in this article. Since we know the sequenced data is massive in bulk, the raw sequenced file is broken into sections and compressed. The Advanced Encryption Standard (AES) algorithm is used for encryption, and the Galois / Counter Mode (GCM) algorithm, is used to decode the encrypted data. This approach reduces the amount of storage space used for the data disc while preserving the data. This condition necessitates the use of a modern data compression strategy. That not only reduces storage but also improves process efficiency by using a k-th order Markov chain. In this regard, no efforts have been made to address this problem separately, from both the hardware and software realms. In this analysis, we support the need for a tailor-made hardware and software ecosystem that will take full advantage of the current stand-alone solutions. The paper discusses sequenced DNA, which may take the form of raw data obtained from sequencing. Inappropriate use of genomic data presents unique risks because it can be used to classify any individual; thus, the study focuses on the security provisioning and compression of diverse genomic data using the Advanced Encryption Standard (AES) Algorithm.

Contribution to the Improvement of Cryptographic Protection Methods for Medical Images in DICOM Format through a Combination of Encryption Method

This paper proposes a method for storing and securing medical images in DICOM format. Other methods offered affect the quality of the image. The solution proposed here is based on the AES256 algorithm in Galois/Counter Mode (GCM) which already integrates authentication and signature processes to ensure the integrity of the images manipulated. This solution is implemented by using the Phyton programming language under the DJANGO framework, libraries such as NUMPHY, PYDICOM, MYSQLCLIENT, and PYCRYPTODOME. The results obtained after experimental tests give us a good average encryption and decryption time. The difference in the mean value of time between encryption and decryption is quite small in view of the tests carried out. We obtain saving on storage space owing to the fact that the proposed solution directly stores the encrypted image. The manipulated image is not altered.

English

The Internet of Things (IoT) expects to improve human lives with the rapid development of resource-constrained devices and with the increased connectivity of physical embedded devices that make use of current Internet infrastructure to communicate. The major challenging in such an interconnected world of resource-constrained devices and sensors are security and privacy features. IoT is demand new approaches to security like a secure lightweight authentication technique, scalable approaches to continuous monitoring and threat mitigation, and new ways of detecting and blocking active threats. This paper presents the proposed security framework for IoT network. A detail understanding of the existing solutions leads to the development of security framework for IoT network. The framework was developed using cost effective design approach. Two components are used in developing the protocol. The components are Capability Design (mainly a ticket, token or key that provides authorization to access a device) and Advanced Encryption Standard (AES)-Galois Counter Mode (GCM) (a-security protocol for constrained IoT devices). AES-GCM is an encryption process that is based on authentication and well suitable IoT.

A practical key agreement scheme for videoconferencing

Recently, videoconferencing is becoming more and more pervasive as a consequence of new concerns about privacy and security. The media should be encrypted through the utilization of actual encryption algorithms and group key agreement schemes. In this study, a new key agreement scheme based on Java smart cards is proposed and applied on Web-based real-time communication (WebRTC)-based videoconferencing. In WebRTC, symmetric keys are generated using pseudorandom number generators and shared by two standard protocols, namely, Source Description RTCP Packet (SDES) and Datagram Transport Layer Security (DTLS), through a signaling server. In both methods, the key exchange is open to cryptanalytic attacks, and the administrator of the signaling server can compromise media. This qualitative study aims to investigate privacy during WebRTC-based videoconferencing with respect to symmetric encryption algorithm, randomness of the encryption key, overall security strength, key agreement scheme, and time required to start a conversation. Herein, a new key agreement scheme based on Java smart cards is proposed. The scheme utilizes AES-256 algorithm in GCM mode for media encryption. By means of this approach, the set-up time of a conference is reduced to 562 ms (compared to 1754 ms for the RSA-based approach) for 367 users, and the security strength is increased to 256-bit (as against 112-bit for RSA 2048-bit). A secure random key generator for smart cards is utilized for a key generation instead of pseudorandom number generators. The proposed approach also includes a safety mechanism for smart card failures. We utilize the AVISPA (The Automated Validation of Internet Security Protocols and Applications) tool to test the safety of the proposed scheme.

PAGE—Practical AES-GCM Encryption for Low-End Microcontrollers

An optimized AES (Advanced Encryption Standard) implementation of Galois Counter Mode of operation (GCM) on low-end microcontrollers is presented in this paper. Two optimization methods are applied to proposed implementations. First, the AES counter (CTR) mode of operation is speed-optimized and ensures constant timing. The main idea is replacing expensive AES operations, including AddRound Key, SubBytes, ShiftRows, and MixColumns, into simple look-up table access. Unlike previous works, the look-up table does not require look-up table updates during the entire encryption life-cycle. Second, the core operation of Galois Counter Mode (GCM) is optimized further by using Karatsuba algorithm, compact register utilization, and pre-computed operands. With above optimization techniques, proposed AES-GCM on 8-bit AVR (Alf and Vegard’s RISC processor) architecture from short-term, middle-term to long-term security levels achieved 415, 466, and 477 clock cycles per byte, respectively.