Encrypted Data Research Articles

Design of Data Security Module Using Key-Policy Attribute Based Encryption (KP-ABE) Algorithm for an Internet-of-Things System

Internet becomes more popular over time. Everything can be connected with the internet with larger coverage area which makes everyone have a higher dependence on it. Along with that, internet-based technology development and application is also moving to its best pattern. In the development, there are a lot of devices that can be used for Internet-of-Things system development. However, Internet-of-Things system has the following security vulnerabilities especially for access control and data protection. For the data privacy protection, it becomes more critical especially when using a standard TCP/IP based application layer protocol to secure the data before its transmitted from the client to the server. This work will be focused on the data privacy security development using a cryptographic scheme for Internet-of-Things system. Attribute Based Encryption (ABE) is one of cryptographic scheme that can be one of the best choices for data protection implementation in embedded device using NVIDA Jetson Nano. It will demonstrate the design of Key-Policy Attribute Based Encryption (KP-ABE) scheme to generate a symmetric key that will be used for Advanced Encryption Standard (AES) while encryption and decryption process. The result shows the execution time of key generation, data encryption and decryption using unique number of attributes.

Nanoscale phase transformation in SiC wafer by spatiotemporal tailored ultrafast laser pulses for multiple optical data encryption

Color center has shown great potential in optical data encryption due to its tunable optical performance. In this work, precise and controllable implantation of color centers within 4H-SiC wafers has been demonstrated by spatiotemporal tailored ultrafast laser irradiation. Distinct microstructures via micro-ablation, micro-cracking and internal phase transformation can be achieved by precisely regulating the spatial energy input in SiC wafer. The orientation of generated microstructures can be accurately controlled by tuning the laser polarization directions. Those color centers can be further customized by varying the defocusing distances and pulse durations. Wherein, nanoscale amorphous carbon layer with thickness ~ 100 nm was achieved by ultrafast laser induced internal phase transformation, which was ascribed to an enhanced near-field optical effect. Due to the thin-film interference, various colors can display from pink to light-green in those laser modified samples with different carbon nanolayer depths. With the highly flexible and precise modification in SiC crystal, multiple colors can therefore be implanted to encode optical information at small scale, allowing high density and complex information storage. This represents a significant advance in controlled phase transformation for nanoscale color centers fabrication, which is promising in multiple optical data encryption.

Quantum Privacy-Preserving Range Query Protocol for Encrypted Data in IoT Environments.

With the rapid development of IoT technology, securely querying sensitive data collected by devices within a specific range has become a focal concern for users. This paper proposes a privacy-preserving range query scheme based on quantum encryption, along with circuit simulations and performance analysis. We first propose a quantum private set similarity comparison protocol and then construct a privacy-preserving range query scheme for IoT environments. By leveraging the properties of quantum homomorphic encryption, the proposed scheme enables encrypted data comparisons, effectively preventing the leakage of sensitive data. The correctness and security analysis demonstrates that the designed protocol guarantees users receive the correct query results while resisting both external and internal attacks. Moreover, the protocol requires only simple quantum states and operations, and does not require users to bear the cost of complex quantum resources, making it feasible under current technological conditions.

Private detection of relatives in forensic genomics using homomorphic encryption.

Forensic analysis heavily relies on DNA analysis techniques, notably autosomal Single Nucleotide Polymorphisms (SNPs), to expedite the identification of unknown suspects through genomic database searches. However, the uniqueness of an individual's genome sequence designates it as Personal Identifiable Information (PII), subjecting it to stringent privacy regulations that can impede data access and analysis, as well as restrict the parties allowed to handle the data. Homomorphic Encryption (HE) emerges as a promising solution, enabling the execution of complex functions on encrypted data without the need for decryption. HE not only permits the processing of PII as soon as it is collected and encrypted, such as at a crime scene, but also expands the potential for data processing by multiple entities and artificial intelligence services. This study introduces HE-based privacy-preserving methods for SNP DNA analysis, offering a means to compute kinship scores for a set of genome queries while meticulously preserving data privacy. We present three distinct approaches, including one unsupervised and two supervised methods, all of which demonstrated exceptional performance in the iDASH 2023 Track 1 competition. Our HE-based methods can rapidly predict 400 kinship scores from an encrypted database containing 2000 entries within seconds, capitalizing on advanced technologies like Intel AVX vector extensions, Intel HEXL, and Microsoft SEAL HE libraries. Crucially, all three methods achieve remarkable accuracy levels (ranging from 96% to 100%), as evaluated by the auROC score metric, while maintaining robust 128-bit security. These findings underscore the transformative potential of HE in both safeguarding genomic data privacy and streamlining precise DNA analysis. Results demonstrate that HE-based solutions can be computationally practical to protect genomic privacy during screening of candidate matches for further genealogy analysis in Forensic Genetic Genealogy (FGG).

Data-Sharing System with Attribute-Based Encryption in Blockchain and Privacy Computing

With the development of the data-sharing system in recent years, financial management systems and their privacy have sparked great interest. Existing financial data-sharing systems store metadata, which include a hash value and database index on the blockchain, and store high-capacity actual data in the center database. However, current data-sharing systems largely depend on centralized systems, which are susceptible to distributed denial-of-service (DDoS) attacks and present a centralized attack vector. Furthermore, storing data in a local center database has a high risk of information disclosure and tampering. In this paper, we propose the ChainMaker Privacy Computing (CPC) system, a new decentralized data-sharing system for secure financial data, to solve this problem. It provides a series of financial data information and a data structure rather than actual data on the blockchain to protect the privacy of data. We utilize a smart contract to establish a trusted platform for the local database to obtain encrypted data. We design a resource catalog to provide a trusted environment of data usage in the privacy computing system that is visible for members on the blockchain. Based on cipher-policy attribute-based encryption (CP-ABE), We design a CPC-CP-ABE algorithm to enable fine-grained access control through attribute based encryption. Finally, We propose an efficient scheme that allows authenticated data-sharing systems to perform Boolean searches on encrypted data information. The results of experiment show that the CPC system can finish trusted data sharing to all organizations on the blockchain.

A Comparative Analysis of AES, RSA, and 3DES Encryption Standards based on Speed and Performance

Information security is important in the digital era, with encryption emerging as a fixed solution to safeguard sensitive data from unauthorized access. This paper provides an overview of encryption by categorizing cryptographic algorithms into symmetric and asymmetric, along with hashing. Symmetric cryptography uses a single key for encryption and decryption, and asymmetric cryptography utilizes distinct public and private keys. Hashing maps input messages into compact bit strings. The literature survey explores the performance analysis of encryption algorithms, focusing on Rivest Shamir Adleman (RSA), Data Encryption Standard (DES), and Advanced Encryption Standard (AES), considering parameters like computation time and memory usage. Furthermore, the comparative analysis of encryption algorithms, including AES, RSA, and 3DES, is discussed. The paper delves into the motivation for cryptography in secure document transfer systems, emphasizing the need for confidentiality, integrity, and availability. Finally, the study presents detailed insights into AES, RSA, and 3DES encryption standards, highlighting their principles and applications.

Enabling Visualized Time‐Resolved Dynamic Discoloring Afterglow from Carbon Dots by Engineering Luminescent Centers and Trap‐States for Security Applications

AbstractLuminescent materials with time‐resolved dynamic discoloring afterglow (TDDA) hold significant potential for applications in anti‐counterfeiting and data encryption. However, the afterglows coming from organic systems are usually unidentifiable due to their shorter durations (less than 10 s). Achievement of long‐lasting and visually discernible TDDA remains highly desirable but challenging. In this work, the TDDA duration is successfully extended from less than 10 s to minutes by engineering the luminescent centers of carbon dots (CDs) and introducing deep trap‐states in a composite of CDs and carbon nitrides (CNs) (named Y‐CDs@CN). It is confirmed that the regulation of luminescent centers in CDs containing both C═N and C═O bonds is responsible for the color changes during TDDA from yellow to green. Moreover, the generation of deep trap states is found to be significant for prolonging the afterglow duration to minutes level through converting room temperature phosphorescence into long persistent luminescence, thus making the entire dynamic discoloring process being easily recognized to naked eyes. Furthermore, the afterglow of Y‐CDs@CN can also be excited by blue light and even using white light of a cell phone. To harness these characteristics, potential applications of Y‐CDs@CN for portable anti‐counterfeiting and multidimensional information encryption are primarily investigated.

Drone-Captured Wildlife Data Encryption: A Hybrid 1D–2D Memory Cellular Automata Scheme with Chaotic Mapping and SHA-256

In contemporary wildlife conservation, drones have become essential for the non-invasive monitoring of animal populations and habitats. However, the sensitive data captured by drones, including images and videos, require robust encryption to prevent unauthorized access and exploitation. This paper presents a novel encryption algorithm designed specifically for safeguarding wildlife data. The proposed approach integrates one-dimensional and two-dimensional memory cellular automata (1D MCA and 2D MCA) with a bitwise XOR operation as an intermediate confusion layer. The 2D MCA, guided by chaotic rules from the sine-exponential (SE) map, utilizes varying neighbor configurations to enhance both diffusion and confusion, making the encryption more resilient to attacks. A final layer of 1D MCA, controlled by pseudo-random number generators, ensures comprehensive diffusion and confusion across the image. The SHA-256 hash of the input image is used to derive encryption parameters, providing resistance against plaintext attacks. Extensive performance evaluations demonstrate the effectiveness of the proposed scheme, which balances security and complexity while outperforming existing algorithms.

An Audio Encryption Algorithm Based on 2D Chaotic Map and Dynamic S-Box

With the development of Internet, the security of information transmission has drawn widespread attention. In order to enhance the security of audio data communication, we propose an audio encryption algorithm using a two-dimensional chaotic map and dynamic S-box. To address the drawbacks of single control parameters and small chaotic space in one-dimensional chaotic map, we integrate Sine map and Fuchunao map to generate a new two-dimensional chaotic map 2D-SIFN. This map has two control parameters and a larger chaotic space. Then we generate chaotic sequences using the 2D-SIFN, construct dynamic S-boxes using these sequences for permutation operations, and finally apply chaotic sequences for diffusion operations to confuse audio data. The simulation experiment results show that the proposed algorithm performs excellently in metrics such as Number of Sample Change Rate (NSCR) and Normalized Cross-correlation (NCC) analysis, proving the feasibility of applying S-boxes to audio data encryption algorithms and proposing a feasible new approach in the field of secure communication.

Optically Transparent Complex-Amplitude Metasurface for Full-Space Manipulation of Frequency-Multiplexed Holographic Imaging.

Restricted by the physical properties of materials, most traditional metasurfaces (MSs) cannot achieve transparent stealth in the visible spectrum. Although some metasurfaces for holography have been designed, there is no standard method for evaluating the advancement of wavefront manipulation under different design algorithms. Here, a complex-amplitude metasurface with optical transparency (OT) and full-space manipulation is presented in the millimeterwave band. Through frequency multiplexing, two holographic images "HOLO" and "GRAM" with high quality are designed, achieving the signal-to-noise ratios of 14.6 and 14.4 dB, respectively. The 64 × 64 bilayered metasurface consists of glass and poly(ethylene terephthalate) (PET) substrates and three metallic mesh layers. By change of the opening size and oriented angle of split rings, phase and amplitude modulations are independently realized. Besides, a new method is provided to assess the superiority of the metasurface holography system for near-field energy regulation. The prototype was fabricated using micro-nano-technology and tested. Two holographic images were experimentally demonstrated and show good agreement with theoretical calculations and simulated results. With the advantages of OT and full-space complex-amplitude customization, the proposed metasurface holograms for frequency-multiplexed may find prospective application aspects in target perception, multichannel data storage and encryption, and many other related fields.

Pbins: private bins for top-k semantic search over encrypted data using transformers

pbins: private bins for top-k semantic search over encrypted data using transformers

Crypto-Spatial: A New Direction in Geospatial Data

Abstract. Geospatial technology involves the use of maps, satellite imagery, and spatial databases to collect, analyze, and visualize geographic data. Understanding the link between blockchain and geospatial technology is crucial as it opens the door to innovation and progress in both fields. “The use of Blockchain as a system for managing and verifying geospatial data necessitates accuracy, integrity, and trustworthiness”(Pengxiang et al 2022). Improving data integrity, promoting collaboration, and revolutionizing applications in the geospatial domain are all possible through the combination of these two technologies. The World Wide Web (WWW) has expanded connections worldwide, but it also makes networks susceptible to multiple attacks from various anonymous sources. Packets of fixed or variable sizes are used for transmitting data across nodes. Data is encrypted using secure algorithms at the application level, then packetized and sent at lower levels in the OSI architecture. The encrypted data can be obtained by an intruder by organizing the data contents of each packet once they have access to all the packets. Intruders may also attempt to break the secured algorithm used by the sender. This sophisticated approach to Data Security is the content and order of data, ensuring that unauthorized individuals are unable to discern sensitive information during data transmission. The primary objective of this paper is to introduce a novel spatial encryption technique designed to enhance the security of data transfers within networks. This paper, founded on a comprehensive literature review, endeavors to propose a research project focused on exploring futuristic solutions, particularly within the post-quantum era.

Real-Time Data Governance and Compliance in Cloud-Native Robotics Systems

This study investigates the frameworks and challenges of real-time data governance and compliance in cloud-native robotics systems, focusing on data integrity, cloud security, regulatory adherence, and cybersecurity risks. Using extensive datasets from the Amazon AWS Open Data Registry, the EU GDPR Enforcement Tracker, and Kaggle’s IoT dataset, the analysis explores cloud-native systems' data accuracy, security, and governance. Data were extracted through a standardized process: performance metrics, including latency and error rates, were gathered from Amazon AWS to assess system efficiency, GDPR violation records were analyzed from the EU Enforcement Tracker to understand compliance trends, and data volume and governance metrics from Kaggle’s IoT dataset were correlated to identify governance challenges. Together, these data sources provide comprehensive insights into how cloud-native systems can be optimized for real-time operations. The study highlights the cloud security benefits and governance advantages inherent to cloud-native frameworks, such as real-time monitoring, automated threat detection, and data encryption, which collectively reduce unauthorized access risks while supporting operational efficiency. Findings indicate high data accuracy (0.51% error rate) and low latency (mean of 48.96 ms) across systems; however, processing time variability (standard deviation of 28.61 ms) signals a need for further optimization in time-sensitive environments. The regression analysis of GDPR violations reveals a substantial penalty increase of €53,789.41 per violation, emphasizing the financial risks of non-compliance. Correlation analysis (r = 0.083 for data volume and governance failures) suggests that external cybersecurity threats have a greater impact on governance than internal metrics, underscoring the importance of adaptive governance frameworks that support both data integrity and regulatory compliance in cloud-native robotics systems.

Exploration of Reliability and Security of E- Banking: Selected Urban Cooperative banks

The rise of E-banking has introduced unprecedented convenience and accessibility for users, transforming traditional banking operations into efficient online experiences. However, this shift brings challenges, particularly in terms of security and reliability, as users now expect robust protections for their financial data and consistent, dependable service. This study investigates the perceptions of security and reliability in digital banking among 290 urban cooperative banking customers. Using factor analysis, we explore key dimensions of e-banking services, focusing on elements like encryption, biometric security, and trust in transaction reliability. The analysis identified two primary factors: security and reliability, each with distinct contributions to overall user satisfaction. The factor loadings revealed that users had mixed confidence in encryption technologies and data privacy measures, with some expressing high levels of satisfaction, while others indicated significant concerns. Additionally, reliability emerged as a critical factor, with findings indicating that a notable portion of customers were dissatisfied with the timeliness and trustworthiness of e-banking services. For data collection, a structured survey measured responses on a five-point Likert scale, assessing variables such as trustworthiness, encryption effectiveness, privacy maintenance, and personal security practices. Through the use of descriptive and factor analysis, we quantified customer sentiments and identified patterns in user satisfaction. The results suggest that while there is moderate confidence in digital banking security, the reliability of service delivery remains an area for improvement. Banks should consider addressing these findings by enhancing transparency in their security protocols and strengthening service consistency to better meet user expectations in digital banking environments.

Triplet Energy Gap‐Regulated Room Temperature Phosphorescence in Host–Guest Doped Systems

AbstractThe organic room temperature phosphorescence (RTP) materials via host–guest doped method receive considerable attention in the fields of optoelectronics, bioimaging, and information encryption. Despite many host–guest doped materials with excellent RTP properties have been developed, their luminous mechanism is still limited. Here, a series of host–guest doped materials, using benzophenone as the host and quinone compounds as the guests, were constructed to investigate the effect of the triplet energy gap (ΔET) between the host and guest on triplet states population. The guest's triplet state is proposed to be a “triplet energy reservoir”, gathering the triplet excitons to emit RTP when ΔET is large and returning triplet excitons to the host when ΔET is small. By combining the results of steady‐state and delayed emission spectra, time‐resolved transient absorption spectra, and theoretical calculations, a bidirectional energy transfer process is proved, which are triplet‐triplet energy transfer and reverse triplet‐triplet energy transfer processes. The thermal equilibrium of these two energy transfer processes can be regulated by the ΔET and temperature. The potential applications of these RTP properties are also realized in data encryption and anti‐counterfeiting. This work provides valuable insight into the design of host–guest doped materials based on energy transfer mechanisms.

Triplet Energy Gap-Regulated Room Temperature Phosphorescence in Host-Guest Doped Systems.

The organic room temperature phosphorescence (RTP) materials via host-guest doped method receive considerable attention in the fields of optoelectronics, bioimaging, and information encryption. Despite many host-guest doped materials with excellent RTP properties have been developed, their luminous mechanism is still limited. Here, a series of host-guest doped materials, using benzophenone as the host and quinone compounds as the guests, were constructed to investigate the effect of the triplet energy gap (ΔET) between the host and guest on triplet states population. The guest's triplet state is proposed to be a "triplet energy reservoir", gathering the triplet excitons to emit RTP when ΔET is large and returning triplet excitons to the host when ΔET is small. By combining the results of steady-state and delayed emission spectra, time-resolved transient absorption spectra, and theoretical calculations, a bidirectional energy transfer process is proved, which are triplet-triplet energy transfer and reverse triplet-triplet energy transfer processes. The thermal equilibrium of these two energy transfer processes can be regulated by the ΔET and temperature. The potential applications of these RTP properties are also realized in data encryption and anti-counterfeiting. This work provides valuable insight into the design of host-guest doped materials based on energy transfer mechanisms.

Pathway-directed recyclable chirality inversion of coordinated supramolecular polymers

It remains challenging to elucidate the fundamental mechanisms behind the dynamic chirality inversion of supramolecular assemblies with pathway complexity. Herein, metal coordination driven assembly systems based on pyridyl-conjugated cholesterol (PVPCC) and metal ions (Ag+ or Al3+) are established to demonstrate pathway-directed, recyclable chirality inversion and assembly polymorphism. In the Ag(I)/PVPCC system, a competitive pathway leads Ag-Complex to form either kinetically controlled supramolecular polymer (Ag-SP I) or thermodynamically favored Ag-SP II, accompanied by reversible chiroptical inversion. Conversely, the Al(III)/PVPCC system displays a solvent-assisted consecutive pathway: the Al-Complex initially forms ethanol-containing Al-SP II, and subsequently converts into ethanol-free Al-SP I with opposite chiroptical performance upon thermal treatment. Moreover, stable chirality inversion in the solid state enables potential dynamic circularly polarized luminescence encryption when Ag(I)/PVPCC is co-assembled with thioflavin T. These findings provide the guidance for the dynamic modulation of chirality functionality in supramolecular materials for applications in information processing, data encryption, and chiral spintronics.

Secure authentication and encryption via diffraction imaging-based encoding and vector decomposition

Abstract Traditional optical encryption systems have security risks due to their linearity and usually encounter problems such as the heavy burden of key transmission and storage. This paper proposes a novel security-enhanced optical image authentication and encryption framework that combines diffractive imaging-based encryption with the vector decomposition algorithm (VDA). Chaotic random phase masks (CRPMs) are used to encrypt data for authentication via VDA, and a pair of complementary binary matrix keys are utilized to extract information from the encrypted data to generate ciphertext. During the authentication and decryption processes, a sparse reference image is reconstructed from the ciphertext for verification. If the authentication is successful, image decryption can be executed using a key-assisted phase retrieval algorithm. The employment of nonlinear VDA, an additional layer of authentication, and the use of CRPMs and binary matrix keys enhance security and address key burden concerns. Simulation results demonstrate the feasibility, effectiveness, and security of the scheme.

Building an Impenetrable Vault: Advanced Cybersecurity Strategies for Database Servers

Organizations are relying more on database servers as storage for important information. This makes it imperative for strong measures against cyber-attack to safeguard sensitive data. The study focusses on some advanced ways of protecting database servers from cyber-crime and these are: SQL injection prevention, role-based access control, data encryption techniques, and insider threat mitigation. It also looks into the latest developments in the area such as machine learning based abnormality detection, Zero Trust architecture, and multi-factor authentication. Such practices make it possible to establish a multi-layered defensive mechanism that enhances data protection by considering the outside as well as inside dangers. Besides compliance with regulations, maintaining visibility and patch management is vital so as to remain ahead of changing cyberspace dangers. Therefore, this research presents an array of recommendations to address the entire security landscape for resilient database platforms against sophisticated assaults. The conclusions point out that there is need to amalgamate these practices towards ensuring safety in terms of risks related with contemporary database server setups. Key Words: Database Security, SQL Injection, Role-Based Access Control, Data Encryption, Insider Threat, Zero Trust Architecture.

Enhanced Asymmetric Circularly Polarized Luminescence in Self-Organized Helical Superstructures Enabled by Macro-Chiral Liquid Crystal Quantum Dots.

Circularly polarized luminescent (CPL) materials have garnered considerable interest for a variety of advanced optical applications including 3D imaging, data encryption, and asymmetric catalysis. However, the development of high-performance CPL has been hindered by the absence of simple synthetic methods for chiral luminescent emitters that exhibit both high quantum yields and dissymmetry factors. In this study, we present an innovative approach for the synthesis of macro-chiral liquid crystal quantum dots (Ch-QDs/LC) and their CPL performance enhancement through doping with 4-cyano-4'-pentylbiphenyl (5CB), thus yielding a CPL-emitting generator (CEG). The Ch-QDs/LCs were synthesized, and their surfaces functionalized with a chiral mesogenic ligand, specifically cholesteryl benzoate, anchored via a lipoic acid linker. Under the regulation of chiral 2S-Zn2+ coordination complexes, the chiral LC encapsulation process promotes coordinated ligand substitution, resulting in an exceptional quantum yield of 56.3%. This is accompanied by high absorption dissymmetry factor (gabs) and luminescence dissymmetry factor (glum) values ranging from 10-3 to 10-2, surpassing most reported dissymmetry factors by at least an order of magnitude. The modular Ch-QDs/LCs demonstrate the ability to transfer chirality to the surrounding medium efficiently and manifest macro-chiral characteristics within a nematic LC matrix. Utilizing Ch-QDs/LC as an effective CPL emitter within achiral 5CB matrices enabled the system to achieve a maximum glum value of 0.35. The resultant CEG device acted as a direct CPL source, initiating enantioselective photopolymerization.