Additive Encryption Research Articles

VOTEMAT: A Blockchain Based Voting System

This study aims to show that a secure, trustable and immutable voting system can be established with Blockchain technology. Decentralized structure of the Blockchain excludes the central authority and provides transparency. Moreover, its cryptographic functions enable secure transactions. Therefore, the operation is prevented from potential frauds, such as multiple votes, fake vote attempts, and fraudulent vote counts. The proposed method, VOTEMAT, covers both electronic voting and paper ballot as a complete solution. A mobile application and a Website, connected to Ethereum private Blockchain network, were developed for the voters who prefer to cast their votes remotely. It is also possible to vote in the voting centres via the mobile device or paper ballot placed in the vote boxes; but these votes are also recorded in the same Blockchain and equally secure. For the remote users, a two-step authentication is designed, based on the information on the national identity card and face recognition. An additional encryption based security measure is used to avoid hacking attempts, such as man in the middle attacks. Since the proposed system is more practical than the traditional voting methods, it can increase the participation and be utilized in all kinds of local or national elections.

Decision-based Data Distribution (D³): Enabling Users to Minimize Data Propagation in Privacy-sensitive Scenarios

In many scenarios, users have to communicate sensitive data with third parties such as doctors, lawyers, insurance companies, social workers, or online shops. Handing over personal data is necessary to use those services, but delegating tasks to increase efficiency still poses the risk that personal data might be leaked. To minimize this risk and further enhance the privacy of users, we propose an interaction concept that uses layered encryption of messages to provide a trade-off between privacy and usability. Users can choose which data is additionally encrypted in an inner layer, e.g. only for the eyes of their doctor, and which data is available in an outer (encrypted or unencrypted) layer for all staff members. Another benefit is the hiding of sensitive data from package inspection or crawling algorithms via emails, while less critical parts can still be processed by these systems via the partial access. To investigate this concept, we derive relevant use cases for form-based communication via email from a quantitative pre-study with 1011 participants, showing that general practitioners are the most suitable use case. We developed demonstrators for this use case and evaluated them in a qualitative study with 42 participants. Our results show that the possibility of minimizing the propagation of sensitive data through additional encryption is highly appreciated and the usage of form-based communication is a promising approach for digital transformation.

Qualitative Analysis of Cryptanalysis of Images Encrypted by Border Chaotic Cellular-Automaton-Based Model Using Segmentation Techniques

Data transactions on computers and phones have become increasingly common, with numerous entities exchanging both public and private data across expanding networks. However, for sensitive data, such as private information, transmitting it over public access networks like the Internet may pose security risks. Digital images are a particularly representative and increasingly significant data type in this context. To safeguard such data from leaks and unauthorized alterations during transmission, encryption serves as a crucial measure. Various cryptographic algorithms are available, each with distinct security requirements. Among these, encryption algorithms based on Cellular Automata offer alternative solutions characterized by their highly chaotic evolutionary capabilities, providing a significant degree of obfuscation, a critical aspect for maintaining confidentiality. This study employs image segmentation techniques such as k-means clustering, edge detection, and thresholding as tools for cryptanalysis. These segmentation techniques are applied to digital images generated using the Border Chaotic Cellular Automata (BCCA) cryptographic model. This approach enables the identification of artifacts and the highlighting of original image features within low-quality encryption. Conversely, more robustly encrypted images, achieved through additional encryption steps, remain unaffected by these techniques, underscoring the level of confidentiality inherent in the BCCA model.

An Optimized Encryption Storage Scheme for Blockchain Data Based on Cold and Hot Blocks and Threshold Secret Sharing.

In recent years, with the rapid development of blockchain technology, the issues of storage load and data security have attracted increasing attention. Due to the immutable nature of data on the blockchain, where data can only be added and not deleted, there is a significant increase in storage pressure on blockchain nodes. In order to alleviate this burden, this paper proposes a blockchain data storage strategy based on a hot and cold block mechanism. It employs a block heat evaluation algorithm to assess the historical and correlation-based heat indicators of blocks, enabling the identification of frequently accessed block data for storage within the blockchain nodes. Conversely, less frequently accessed or "cold" block data are offloaded to cloud storage systems. This approach effectively reduces the overall storage pressure on blockchain nodes. Furthermore, in applications such as healthcare and government services that utilize blockchain technology, it is essential to encrypt stored data to safeguard personal privacy and enforce access control measures. To address this need, we introduce a blockchain data encryption storage mechanism based on threshold secret sharing. Leveraging threshold secret sharing technology, the encryption key for blockchain data is fragmented into multiple segments and distributed across network nodes. These encrypted key segments are further secured through additional encryption using public keys before being stored. This method serves to significantly increase attackers' costs associated with accessing blockchain data. Additionally, our proposed encryption scheme ensures that each block has an associated encryption key that is stored alongside its corresponding block data. This design effectively mitigates vulnerabilities such as weak password attacks. Experimental results demonstrate that our approach achieves efficient encrypted storage of data while concurrently reducing the storage pressure experienced by blockchain nodes.

Jerk Chaotic System: Analysis, Circuit Simulation, Control and Synchronization with Application to Secure Communication

Dynamical behaviors of 3D Jerk system were examined in terms of equilibrium, stability, dissipative, and phase space attractor in this study. The system’s practical applications were demonstrated through circuit realization and synchronization scheme via active backstepping control with its effectiveness demonstrated in secure communication. The viability of the theoretical model of 3D Jerk system was confirmed using electronic circuit workbench designed in MultiSIM enviroment. A nonlinear feedback controller was designed using the recursive backstepping technique to control and track a desire function. For secure communication application, active backstepping method was adopted to synchronize two identical chaotic systems evolving from different initial conditions. It was demonstrated that when the controller was activated, the systems synchronize successfully. The results of the active backstepping designed controllers were numerically applied in the area of secure communication, with the variable of the drive being encrypted information transmitted through a coupling channel. Using an additive encryption masking scheme, the encrypted signal was a superposition of sinusoidal information specified by period function and chaotic carrier generated from a variable of the Jerk system. The transmitted information signal was successfully retrieved from the chaotic response signal using an inverse function decryption algorithm, thereby confirming the effectiveness and robustness of the designed controller.

Ethical Knowledge Sharing Leveraging Blockchain: An Overview

The knowledge that is acquired through a learning process has ethical concerns when shared, as there can be restrictions on the parties who can use the piece of knowledge, redistribution approaches protecting the creator's rights, privacy, and confidentiality concerns, accuracy and trustworthiness, openness and transparency, and informed consent. Blockchain structure encompasses a series of coupled blocks that are intrinsically linked with the conservation of authenticity, ensuring irrefutability, and the semi-anonymity of transactions. As pioneers in reviewing BC-based ethical Knowledge Sharing (KS), we categorize the model into 4 classes and critically evaluate the literature relative to knowledge-associated features, ethical knowledge-sharing aspects, BC-associated features, and network features. We heaped a commencing sample of 69 document references by selecting the literature for eligibility conditions pursued from intellectual resource search platforms, leveraging a profound and overly extended-period technique. We investigate and emphasize that, owing to innate security properties, blockchain can facilitate ethical KS in numerous ways, such as leveraging a dedicated consensus approach for ethical KS (Class 1), leveraging blockchain itself for knowledge storage and sharing due to its mutation-proof, non-tamperable, fault tolerance features (Class 2), ensuring the confidentiality of knowledge by leveraging additional encryption techniques on blockchain (Class 3), and leveraging smart contracts for attribute-based searching, knowledge fusion, access control, reward-driven KS, etc. (Class 4). Critical evaluation unveils that from BC-based ethical KS frameworks, 50% utilize smart contracts with blockchain for knowledge-based activities, 90% leverage progressive BC architecture, 6.7% leverage proof-of-knowledge consensus, 93.4% share propositional knowledge, and 70% share explicit knowledge. Moreover, accuracy, openness and transparency, privacy, trustworthiness, truthfulness, and confidentiality have been the dominant factors in ethical KS principles of interest. Finally, we examine the openings and hurdles of the model of blockchain-based ethical KS, then propose actions to diminish them, and afterward present future directions, implications, and limitations for the concept.

Application Of Super Encryption Using Rot 13 Algorithm Method and Algorithm Beaufort Cipher For Image Security Digital

Digital image security is becoming increasingly critical in today's digital era, where sensitive information and data are often stored in image form. Therefore, an effective and secure encryption method is needed to protect the integrity and confidentiality of digital images. This study aims to implement a stronger security approach by combining classic encryption methods, namely the ROT13 algorithm and the Beaufort Cipher algorithm which produces an encryption called "Super Encryption". In this study, first of all, the ROT13 encryption method will be applied to randomize digital image text by shifting characters as far as 13 positions in the alphabet. Then, the Beaufort Cipher algorithm will be used to apply additional encryption to the digital image, which involves using the key as input in the encryption process. The results of this study indicate that the Super Encryption method which combines the ROT13 and Beaufort Cipher algorithms provides a higher level of security compared to using each method separately. Security testing and vulnerability analysis show that the combination of these two algorithms produces digital images that are more difficult to decrypt by commonly used decryption attacks.

Generating Encrypted Document Index Structure Using Tree Browser

Generating Encrypted Document Index Structure Using Tree Browser

Analysis of the encryption penalty in a QAM-based quantum noise stream cipher.

Quantum noise stream cipher based on quadrature-amplitude-modulation (QAM/QNSC) is a kind of physical layer encryption technology. However, the additional encryption penalty will significantly affect the practical deployment of QNSC, especially in the high capacity and long-haul transmission system. With our research, the encryption process of QAM/QNSC degrades the transmission performance of plaintext information. In this paper, we quantitatively analyze the encryption penalty of QAM/QNSC based on the proposed concept of effective minimum Euclidean distance. We calculate the theoretical signal-to-noise ratio sensitivity and encryption penalty of QAM/QNSC signals. A modified feedforward pilot-aided two-stage carrier phase recovery scheme is used to reduce the effect of laser phase noise and the encryption penalty. Experimental results achieve single-channel 205.9 Gbit/s 640km transmission with single carrier polarization-diversity-multiplexing 16-QAM/QNSC signal.

56 Gb/s PAM4 physical secure communication based on electro-optic self-feedback hardware temporal phase encryption and decryption.

To guarantee information security from the lowest level of optical networks, it is essential to provide physical layer security in fiber-optic communication systems. However, it is challenging to realize high speed physical secure optical communication based on advanced optical modulation formats and pure commercial hardware components. In this work, we report an experimental demonstration of a high-speed 56 Gb/s PAM4 physical-layer secure optical communication system by employing an electro-optic self-feedback hardware module for temporal self-phase encryption and decryption without consuming any additional encryption channel. An encrypted 56 Gb/s PAM4 confidential signal is successfully decrypted after transmitting over 60 km single-mode fiber. The demonstrated scheme can not only be integrated with existing optical communication networks, but can also be used as a pluggable module, which may provide a promising solution for ultra-high speed physical secure optical communication by combining with advanced multiplexing technology in future.

Lightweight compression with encryption based on asymmetric numeral systems

Data compression combined with effective encryption is a common requirement of data storage and transmission. Low cost of these operations is often a high priority in order to increase transmission speed and reduce power usage. This requirement is crucial for battery-powered devices with limited resources, such as autonomous remote sensors or implants. Well-known and popular encryption techniques are frequently too expensive. This problem is on the increase as machine-to-machine communication and the Internet of Things are becoming a reality. Therefore, there is growing demand for finding trade-offs between security, cost and performance in lightweight cryptography. This article discusses Asymmetric Numeral Systems -- an innovative approach to entropy coding which can be used for compression with encryption. It provides compression ratio comparable with arithmetic coding at similar speed as Huffman coding, hence, this coding is starting to replace them in new compressors. Additionally, by perturbing its coding tables, the Asymmetric Numeral System makes it possible to simultaneously encrypt the encoded message at nearly no additional cost. The article introduces this approach and analyzes its security level. The basic application is reducing the number of rounds of some cipher used on ANS-compressed data, or completely removing additional encryption layer if reaching a satisfactory protection level.

Fast colored video encryption using block scrambling and multi-key generation

Multimedia information usage is increasing with new technologies such as the Internet of things (IoT), cloud computing, and big data processing. Video is one of the most widely used types of multimedia. Videos are played and transmitted over different networks in many IoT applications. Consequently, securing videos during transmission over various networks is necessary to prevent unauthorized access to the video's content. The existing securing schemes have limitations in terms of high resource consumption and high processing time, which are not liable to IoT devices with limited resources in terms of processor size, memory, time, and power consumption. This paper proposed a new encryption scheme for securing the colored videos. The video frames are extracted, and then, the frame components (red, green, and blue) are separated and padded by zero. Then, every frame component (channel) is split into blocks of different sizes. Then, the scrambled blocks of a component are obtained by applying a zigzag scan, rotating the blocks, and randomly changing the blocks' arrangements. Finally, a secret key produced from a chaotic logistic map is used to encrypt the scrambled frame component. Security analysis and time complexity are used to evaluate the efficiency of the proposed scheme in encrypting the colored videos. The results reveal that the proposed scheme has high-level security and encryption efficiency. Finally, a comparison between the proposed scheme and existing schemes is performed. The results confirmed that the proposed scheme has additional encryption efficiency.

Multi-responsive graphene quantum dots hybrid self-healing structural color hydrogel for information encoding and encryption

Information security plays an important role in the era of big data. Attempts to improve security often require giving them more additional encryption strategies. Herein, a specially designed multi-responsive graphene quantum dots hybrid self-healing structural color hydrogel system was proposed. Firstly, monomers such as N-isopropyl acrylamide (NIPAM), and dimethylamino ethyl methacrylate (DMAEMA) were filled into the photonic crystal templates and then photo-cured. After hydrofluoric (HF) etching, the graphene quantum dots (GQDs) and the precursor solution containing dithiothreitol (DTT) and borax were filled into the inverse opal holes. Finally, the hybrid hydrogel integrating quantum dots and photonic crystals was prepared by curing at room temperature. The hybrid hydrogel exhibited excellent pH, temperature, and angle-responsive color-changing characteristics. Besides, it had fluorescent properties under ultraviolet (UV) light irradiation and had photothermal conversion ability under near-infrared (NIR) light irradiation. Furthermore, the hybrid hydrogel color matrix was prepared by utilizing its excellent quantum dots fluorescent properties, dynamically adjustable structural color, multi-responsive, and self-healing properties. Therefore, the color matrix formed by the hybrid hydrogel had strong information storage capacity and encoding capacity, which could perform various information encryption and decryption modes step-by-step. Furthermore, we developed a simple mini-program for the step-by-step identification and decryption process of the matrix, indicating that it had great practical value in the field of information security.

Dynamic Deduplication Algorithm for Cross-User Duplicate Data in Hybrid Cloud Storage

The escalating growth of distributed big data in hybrid cloud storage architecture introduces a new set of challenges. Constantly, content enrichment puts pressure on capacity. Nonetheless, the explosion of user data places a significant strain on broadband and storage capacity. Consequently, many cloud storage providers will implement deduplication to compress data, reduce transfer bandwidth, and reduce cloud storage space. In cloud storage systems, it is a data compression and storage optimization method. By locating and removing redundant data, it can save storage space and bandwidth. An MTHDedup deduplication strategy based on the Merkle hash tree is presented in a hybrid cloud environment to address the issue of convergent encryption algorithms being susceptible to brute-force attacks and ciphertext computation time overhead. Merkle hash trees are constructed using additional encryption algorithms to generate encryption keys during file- and block-level deduplication, ensuring that generated ciphertexts are unpredictable. The method is effective against both internal and external brute-force attacks, thereby increasing data security. Our method reduces the computational burden of ciphertext generation and the key storage space, and the performance advantage increases with the number of privilege sets.

LPCP: An efficient Privacy-Preserving Protocol for Polynomial Calculation Based on CRT

With the development of privacy-preserving techniques, the increasing demand for secure multiparty computation (MPC) of mobile devices has become a significant challenge. Unfortunately, it is inapplicable for mobile devices to implement the existing secure multiparty computation schemes that rely on costly computation and communication overhead. To solve this problem, we propose an efficient two-party computation protocol secure against semi-honest adversary based on the Chinese remainder theorem (CRT). Our protocol utilizes CRT-based encryption and re-encryption techniques to realize additional and multiplicative homomorphic encryption, which can be transformed into a two-party secure computation scheme. Then, we extend our two-party LPCP protocol into a multiparty LPCP protocol, which is much faster and more space saving than the previous works. For practical purpose, we describe a distance measurement application for mobile devices based on LPCP. In the end, we implement LPCP codes and compare the experimental results to the state-of-the-art two-party and multiparty computation protocols. The experimental result shows that the high computation and communication efficiency of LPCP makes it possible for low computing-power mobile devices to implement multiparty secure computation protocols in reality.

Ultrafast Secure Key Distribution Based on Random DNA Coding and Electro-Optic Chaos Synchronization

We propose and numerically demonstrate an ultrafast secure key distribution based-on random DNA coding and the chaos synchronization in two identical electro-optic oscillators (EO) with common injection. High-quality synchronization between the responses of EOs with extremely sensitivity to the mismatching of time delay and phase bias is observed. It is noted that the random DNA coding and the delay DNA-XOR in the post-processing can greatly amplify the randomness of the synchronized sequences acquired by symmetrically dual-threshold sampling the correlated physical entropies, and enhance the security of key distribution by providing additional encryption. According to our study, high rate key distribution of over 10 Gb/s can be fulfilled with a good consistency, which can be used for the commercial communication networks.

Bioinspired Perovskite Nanocrystals-Integrated Photonic Crystal Microsphere Arrays for Information Security.

Information security occupies an important position in the era of big data. Attempts to improve the security performance tend to impart them with more additional encryption strategies. Herein, inspired by the wettability feature of Stenocara beetle elytra and signal model of traffic light, a novel array of perovskite nanocrystals (PNs)‐integrated PhC microsphere for information security is presented. The photoluminescent PNs are encapsulated in angle‐independent PhC microspheres to impart them with binary optical signals as coding information. Through the multimask superposition approach, PNs‐integrated PhC microspheres with different codes are placed into fluorosilane‐treated PDMS substrate to form different arrays. These arrays could converge moisture on PhC microspheres in wet environment, which avoids the ions loss of the PNs and effectively prevented mutual contamination. In addition, the fluorescence of the PNs inside PhC microspheres could reversibly quench or recover in response to the environmental moisture. Based on these features, it is demonstrated that the PNs‐integrated PhC microsphere arrays could realize various information encryption modes, which indicate their excellent values in information security fields.

A CCA-PKE Secure-Cryptosystem Resilient to Randomness Reset and Secret-Key Leakage

In recent years, several new notions of security have begun receiving consideration for public-key cryptosystems, beyond the standard of security against adaptive chosen ciphertext attack (CCA2). Among these are security against randomness reset attacks, in which the randomness used in encryption is forcibly set to some previous value, and against constant secret-key leakage attacks, wherein the constant factor of a secret key’s bits is leaked. In terms of formal security definitions, cast as attack games between a challenger and an adversary, a joint combination of these attacks means that the adversary has access to additional encryption queries under a randomness of his own choosing along with secret-key leakage queries. This implies that both the encryption and decryption processes of a cryptosystem are being tampered under this security notion. In this paper, we attempt to address this problem of a joint combination of randomness and secret-key leakage attacks through two cryptosystems that incorporate hash proof system and randomness extractor primitives. The first cryptosystem relies on the random oracle model and is secure against a class of adversaries, called non-reversing adversaries. We remove the random oracle oracle assumption and the non-reversing adversary requirement in our second cryptosystem, which is a standard model that relies on a proposed primitive called LM lossy functions. These functions allow up to M lossy branches in the collection to substantially lose information, allowing the cryptosystem to use this loss of information for several encryption and challenge queries. For each cryptosystem, we present detailed security proofs using the game-hopping procedure. In addition, we present a concrete instantation of LM lossy functions in the end of the paper—which relies on the DDH assumption.

Distributed additive encryption and quantization for privacy preserving federated deep learning

Homomorphic encryption is a very useful gradient protection technique used in privacy preserving federated learning. However, existing encrypted federated learning systems need a trusted third party to generate and distribute key pairs to connected participants, making them unsuited for federated learning and vulnerable to security risks. Moreover, encrypting all model parameters is computationally intensive, especially for large machine learning models such as deep neural networks. In order to mitigate these issues, we develop a practical, computationally efficient encryption based protocol for federated deep learning, where the key pairs are collaboratively generated without the help of a trusted third party. By quantization of the model parameters on the clients and an approximated aggregation on the server, the proposed method avoids encryption and decryption of the entire model. In addition, a threshold based secret sharing technique is designed so that no one can hold the global private key for decryption, while aggregated ciphertexts can be successfully decrypted by a threshold number of clients even if some clients are offline. Our experimental results confirm that the proposed method significantly reduces the communication costs and computational complexity compared to existing encrypted federated learning without compromising the performance and security.

Two-level security approach combining watermarking and encryption for securing critical colored images

With the widespread of the Internet and the rapid growth of technologies, several challenges face data hiding process. Although watermarking is widely used to hide/embed critical data into a cover image, the watermarked image may be attacked/hacked and the embedded data may be extracted or damaged. This paper presents an efficient two-level security approach to protect colored watermark images. In the first level, the color image is embedded into a grayscale image using a multi-level Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD), and wavelet fusion. In the second level, an additional encryption process on the watermarked image is done by using two-dimensional logistic chaotic map in a case and Advanced Encryption Standard (AES) in another case. The proposed scheme is evaluated by using several images and different hacks on the transmitted image. The experimental results show that the proposed scheme is efficient and can face many attacks such as Gaussian, Blur, Wrap, and Cropping. In addition, the extracted watermarks are recognized even when the marked images suffered from attacks.