Data Security Techniques Research Articles

AN ENCRYPTION ALGORITHM EMPLOYING GRAPHS

With the advancement of technology, maintaining secrecy is a crucial concern that requires a variety of skills. A scientific method for protecting communication against unauthenticated access is cryptography. In cryptography, there are several encryption techniques for data security. It has been suggested that new nonstandard encryption techniques are needed to shield communication from conventional threats. This work presents a method that uses graphs together with some algebraic features to provide some new encryption techniques for safe message transfer. The transmission of secret communications will be safer because of the suggested encryption techniques.

Employing Cryptographic Techniques for Data Security and Privacy Preservation

Employing Cryptographic Techniques for Data Security and Privacy Preservation

Perbandingan Algoritma SIMON dan SPECK Dalam Pengamanan Citra Digital

Cryptography is a data security technique by encoding data that is to be kept secret so that the original meaning of the data can no longer be understood. SIMON and SPECK are modern cryptographic algorithms issued by the National Security Agency (NSA). SIMON and SPECK are said to be algorithms that are known for their efficiency and strong security. This research will compare the performance of the SIMON and SPECK algorithms in securing digital images. Comparisons were made by testing time performance, changes in file size, and the level of randomness of image files using the Unified Average Changing Intensity (UACI) and Number of Pixels Change Rate (NPCR) metrics. The research results show that the average encryption and decryption time required by the SIMON algorithm is greater when compared to the SPECK algorithm. The image file size resulting from encryption using the SIMON and SPECK algorithms both increased by 24% from the original image. The level of randomness of the resulting image based on the UACI value obtained using the SIMON algorithm was found to be an average of 19.65%, while the UACI value obtained using the SPECK algorithm was an average of 20.94%. This shows that there is a significant change in intensity between the original image and the encrypted image. However, not all pixels in the encrypted image change when compared to the original image, this is shown by the NPCR value obtained from the SIMON and SPECK algorithm encrypted image, with average results of 49.98% and 50.17%.

Reversible Data Hiding in Crypto-Space Images with Polynomial Secret Sharing over Galois Field

Secret sharing is a data security technique that divides secret information into multiple parts, embeds these parts into various shares, and distributes these shares to different participants. The original secret information can be retrieved only when the number of shares gathered meets a required threshold. This paper proposes a secret sharing method that can hide data in encrypted images with reversibility and allows content owners to add an additional layer of security before uploading data to the cloud. This method enables the independent extraction of images and data, ensuring that the recovered images and extracted data can serve as validation information for each other. The proposed method not only enhances data security but also guarantees the accuracy of the extracted information.

RiskTree: Decision Trees for Asset and Process Risk Assessment Quantification in Big Data Platforms

The inherent characteristics of big data lies in its voluminous scale, varied data formats, and swift processing velocity. The intrinsic characteristics of big data undermine the efficacy of conventional data security techniques and data management standards, consequently compromising the security of big data. As a consequence, big data possesses susceptibilities to security incidents, including unauthorized data access, data manipulation, and data compromise throughout the transmission, storage, and processing stages. Conventional information system security risk assessment methodologies are constrained by human resources and computational techniques, rendering them unsuitable for direct application to big data platforms. Consequently, there is an urgent necessity to develop a risk assessment framework tailored specifically for big data environments, capable of quantifying potential risks and losses. In response to this need, we have devised an automated risk assessment theory that assimilates the unique characteristics of big data with traditional quantitative methods, introducing a risk metric system suited to the big data context. Utilizing the risk-related data generated during operations on the big data platform, we train a decision tree model to derive the weights for each risk indicator. These weights are then employed to conduct a weighted summation of the operational risk indicators, thereby achieving a quantitative evaluation of the platform's risk profile. To substantiate the proposed framework, experiments were conducted on a simulated big data platform. The experimental outcomes demonstrate that, compared to existing quantitative risk assessment methodologies, our approach enables an automatic, objective, and efficient assessment and quantification of the risks associated with tangible assets and data processing operations within the big data platform.

Encryption techniques for financial data security in fintech applications

In the dynamic world of financial technology (Fintech), securing financial data is a key priority. Increasing digital connectivity, adoption of cloud-based services requiring complex measures to protect the integrity, privacy and availability of sensitive information. Encryption techniques are emerging as a key tool to achieve these goals about itself by converting plaintext into ciphertext, protected from unauthorized access and probability violations. This review paper examines the various encryption techniques required to secure financial information in fintech applications. The main methods described include symmetric encryption, asymmetric and hybrid encryption techniques. Additionally, the function of end-to-end encryption (E2EE) is discussed in terms of protecting data privacy while it is being sent, which is essential for safeguarding sensitive financial activities such as mobile banking and digital payments. With its sophisticated method of permitting calculations on encrypted data without the need for decryption, homomorphic encryption shows promise for facilitating safe data analysis in Fintech settings while preserving data confidentiality. Each encryption method is scrutinized in terms of its strengths, weaknesses and practical applications in Fintech. Considerations such as computing efficiency, scalability, and regulatory compliance are addressed to provide insights for optimizing data protection strategies while adhering to industry standards and regulatory frameworks. The future of Fintech security is expected to be shaped by new developments in encryption technology, including post-quantum cryptography, artificial intelligence integration for adaptive security measures, and privacy-preserving solutions. The goal of these advancements is to strengthen the robustness of financial data security techniques in an increasingly linked digital world while mitigating changing cyber risks.

A systematic review on elliptic curve cryptography algorithm for internet of things: Categorization, application areas, and security

Cyberattacks on the Internet of Things (IoT) may be avoided by implementing cybersecurity protocols on IoT devices, platform packages, and Internet tools. A significant problem is developing a simple security mechanism suitable for resource-constrained IoT devices. Elliptic curve cryptography (ECC) is extensively utilized and well-suited for use in low-resource environments like smartphone devices. ECC utilizes short crypto keys with the same security strength as conventional cryptosystems, decreasing power consumption and enhancing device efficiency. This study comprehensively evaluates ECC data privacy and security techniques in IoT-based devices. The research also looked into other cryptography protocols that ECC may use to increase security and performance. The inclusion procedures were papers published between 2018 and 2023, written in English, and published in a peer-reviewed scholarly outlet. This research eventually reviewed 61 suitable publications in total. Compared to other cryptographic methods, the study discovered that ECC has received greater attention or is frequently employed in IoT-based systems. However, additional issues and concerns must be addressed, including efficient IoT device security, maintaining privacy, and device security against vulnerability assaults such as man-in-the-middle attacks. For the efficient security of the IoT-based system, an improved ECC-based algorithm should be developed to enhance the security and privacy issues of the IoT system.

Trust based Routing – A Novel Approach for Data Security in WSN based Data Critical Applications

Wireless technology has changed the way entities communicate with one another. Wireless networks have created several opportunities in fields such as military, health care, and habitat monitoring, to name a few. However, only a few data-critical applications are built on wireless sensor networks, such as border reconnaissance, detecting infringement, and patient monitoring. These applications require the processing of a large amount of private data. Because most applications are data-sensitive, securing data transmission among wireless sensor networks is crucial. While incorporating data security, the most important requirement of wireless sensor nodes being energy optimized also need to be kept in consideration. There are various forms of assaults that are relevant in Wireless Sensor Networks (WSN). Attacks like Black Hole attacks, sink hole attacks, False data Injection attacks etc. are the most commonly seen attacks on WSNs. The common element in all these attacks is the concept of malicious / compromised node - a node which either drops / modifies the data content while forwarding it. Existing techniques for data security generally use cryptographic algorithms, but the use of cryptographic algorithms is in contrast with the energy optimization requirement of sensor nodes. An energy efficient data security scheme needs to be developed. The proposed system analyses several attacks and proposes a multi-layer data security approach to prevent change of data / dropping of data by the compromised nodes. The proposed system is a routing protocol referred as Trust Based Routing (TBR). A concept of trust value of a node is the core idea of TBR. Forwarding node is selected based on highest trust value and thus avoid malicious / compromised nodes from being involved in the routing process. The trust factor is calculated by considering the number of packets dropped, packets rejected, and the node's remaining energy. The idea of TBR is enhanced by incorporating the concept of past trust and trust of node towards a specific destination. This proposed scheme is referred as Extended Trust Based Routing (ETBR). This scheme is further enhanced by including Direct Trust, Indirect Trust and Energy Trust concepts. This scheme is referred as Consolidated Trust Estimation – Trust Based Routing (CTE-TBR). Network Simulator NS2 is used to simulate the proposed schemes. Various network factors are compared to classic Adhoc On-Demand Vector (AODV) and newly proposed schemes. The result indicates the effectiveness of the proposed data security scheme in terms of energy efficiency and Packet Delivery ratio (PDR).

Encryption of Card Details Using AES with a 128-bit Key a Secure Approach to Data Protection

Data security is a critical concern in today's digital age, particularly regarding the protection of sensitive information such as cardholder data. This research paper explores the implementation of Advanced Encryption Standard (AES) encryption with a 128-bit key as a means of safeguarding card details. The project demonstrates the encryption and decryption process, ensuring data confidentiality and integrity. Utilizing the pycryptodome library in Python, the AES encryption technique is applied to encrypt card details, offering a secure approach to data protection. The methodology section outlines the AES encryption process, emphasizing key generation, encryption, and decryption. A detailed explanation of the Python implementation highlights the importance of key length and randomness in the encryption process. The results section presents the outcomes of encrypting and decrypting card details using AES encryption, analyzing the efficiency and security of the encryption process. Additionally, potential vulnerabilities and challenges encountered during implementation are discussed, along with their resolutions. In the discussion section, the research findings are interpreted in the context of data security and encryption standards. A comparison between AES encryption and other encryption algorithms is provided, evaluating performance and security aspects. Consideration is given to future research directions in the field of data encryption and security. Overall, this research paper underscores the significance of AES encryption with a 128-bit key for protecting cardholder information. By implementing AES encryption, organizations can enhance data security measures, ensuring the confidentiality and integrity of sensitive data in digital transactions. This abstract provides a concise overview of the research paper, summarizing the objectives, methodology, results, and implications of implementing AES encryption for card data protection. It highlights the importance of data security and encryption techniques in safeguarding sensitive information in digital transactions. Tokenizing cards enhances security, ensures regulatory compliance, boosts customer trust, and streamlines payment processes while reducing liability for organizations. Future developments may involve tokenizing cards even without customer consent. Keywords: Tokenization, Payment systems, Encryption, Fraud prevention

Patient-Generated Health Data (PGHD): Understanding, Requirements, Challenges, and Existing Techniques for Data Security and Privacy.

The evolution of Patient-Generated Health Data (PGHD) represents a major shift in healthcare, fueled by technological progress. The advent of PGHD, with technologies such as wearable devices and home monitoring systems, extends data collection beyond clinical environments, enabling continuous monitoring and patient engagement in their health management. Despite the growing prevalence of PGHD, there is a lack of clear understanding among stakeholders about its meaning, along with concerns about data security, privacy, and accuracy. This article aims to thoroughly review and clarify PGHD by examining its origins, types, technological foundations, and the challenges it faces, especially in terms of privacy and security regulations. The review emphasizes the role of PGHD in transforming healthcare through patient-centric approaches, their understanding, and personalized care, while also exploring emerging technologies and addressing data privacy and security issues, offering a comprehensive perspective on the current state and future directions of PGHD. The methodology employed for this review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and Rayyan, AI-Powered Tool for Systematic Literature Reviews. This approach ensures a systematic and comprehensive coverage of the available literature on PGHD, focusing on the various aspects outlined in the objective. The review encompassed 36 peer-reviewed articles from various esteemed publishers and databases, reflecting a diverse range of methodologies, including interviews, regular articles, review articles, and empirical studies to address three RQs exploratory, impact assessment, and solution-oriented questions related to PGHD. Additionally, to address the future-oriented fourth RQ for PGHD not covered in the above review, we have incorporated existing domain knowledge articles. This inclusion aims to provide answers encompassing both basic and advanced security measures for PGHD, thereby enhancing the depth and scope of our analysis.

Efficient Technique for Data Management and Security Over the Cloud

Efficient Technique for Data Management and Security Over the Cloud

Advancements in Encryption Techniques for Enhancing Meteorological Data Security During Catastrophic Weather Events

With the widespread utilization of meteorological data across diverse fields, the imperative for ensuring its security and safeguarding privacy has escalated. Meteorological data encompasses a wealth of sensitive information, including frequency bands and the precise locations of sensing devices. Inappropriate handling of this data may engender profound ramifications for multiple stakeholders. Particularly in the face of severe catastrophic weather conditions, the conundrum of optimizing the analysis and transmission of critical meteorological data within the confines of finite resources and time constraints looms large, demanding immediate attention from researchers. This paper centralizes its focus on the analysis and storage of information derived from common meteorological devices, proposing a priority-weighted encryption strategy. Within this strategy, meteorological data attains the utmost degree of privacy attainment while concurrently improving encryption efficiency, even when faced with the stringent limitations of limited resources and time constraints during severe catastrophic weather events.

Secure Cloud-Based Media Sharing: Scalable Access Control and Privacy-Preserving Deduplication

This research delves into the realm of secure deduplication schemes, strategically designed to enhance storage efficiency within cloud environments. An initial focus is placed on an advanced AES encryption scheme utilizing a message-derived key, resulting in a consistent mapping of identical plaintexts to ciphertexts. The proposed AES framework not only incorporates convergent encryption but also provides meticulous security definitions. While the landscape of cloud computing boasts numerous techniques for data security, existing methodologies fall short in addressing nuanced aspects related to ciphertext. In response to this gap, our study introduces a pioneering information management paradigm. This comprehensive framework encompasses data gathering, sharing, and restrictive distribution, with a particular emphasis on multi-owner privacy preservation within the cloud. Under this innovative framework, data owners gain the capability to securely disseminate private information to predefined groups of clients through the cloud infrastructure. The research presented herein serves as a significant contribution to the ongoing discourse on secure deduplication in cloud storage. By combining advanced encryption techniques with a forward-looking information sharing strategy, our approach seeks to elevate the effectiveness of data security protocols in cloud environments

A Lightweight Security Model using Delta Probabilistic Hashing Technique for Secured Data Transmission in IoT Systems

Secure data transmission is one of the most pressing concerns for resource constrained IoT devices. There is a need for an efficient and lightweight solution for data security in IoT applications. The proposed study is primarily concerned with the creation of a lightweight data security model for an IoT data transmission-based application for data transmission and storage in smart cities. The fundamental contribution of the proposed security model is the creation of a distinct hashing algorithm based on the specific pattern of the previous sequential change in value. The Delta Probabilistic Hashing (DPH) based architecture of key extraction technique for data security will perform this. Based on the hash key signature approach, this kind of safe data handling procedure provides a random key for data encryption, which will simplify the model and speed up the algorithm's operation. Our approach's main features are enhanced efficiency and throughput, lightweight data security, and adaptive key generation.

A Novel Technique for Enhancing Data Security Using Hybrid Coding in Medical Images

The Internet's rapid development in data transmission has made it simpler to convey data quickly and accurately to the intended recipient. Data is one of the most essential assets to be protected during Internet transmission, thus it is necessary to handle the rising danger of security. Through hacking, unauthorized person can alter or misuse the crucial data. Therefore, security is a primary problem that requiring attention. Compression and encryption are frequently used to share and save images respectively. The effectiveness of digital image services depends on how the two activities are performed. Medical images play a significant role in the modern healthcare system because they are utilized to preserve patient data including illness diagnoses and other pertinent details. Thus, data must be maintained in a secure manner. To deliver data safely and unchanged to the target place, a variety of techniques, including cryptography and steganography are utilized to solve security difficulty, several research and exercises were done to produce a range of tactics and algorithms. In this paper, a technique for concealing the secret image is proposed.

RSA and AES Based Hybrid Encryption Technique for Enhancing Data Security in Cloud Computing

Cloud computing security has become the most crucial problem in its growth. Encryption has been developed as a solution and plays a vital role in the security of information systems in cloud computing. Many methods are required to secure the shared data. The advanced internet, networking firms, health information, and cloud applications have significantly increased our data every minute. The current work focuses on cryptography to protect sensitive data exchanged between personal users, companies, organizations, or in the cloud applications and others during data transfer across the network. Firstly, data sent from the sender to the network receiver must be encrypted using the cryptographic algorithm. Secondly, the recipient shows the original data using the decryption technique. In this paper, we have proposed a model to use a hybrid encryption and decryption process based on AES-128 and the RSA algorithm. Furthermore, we used the HMAC algorithm to ensure the integrity and authenticity of data. Our experiment work has been done to explain the time required and throughput for encryption and decryption of three encrypting algorithms, AES, RSA, and hybrid algorithms, based on different data sizes, and their efficiency is compared. The results of the experiments show that the hybrid algorithm is better in terms of security.

A unique database synthesis technique for coverless data hiding

Coverless data hiding is a powerful technique for data security, but synthesizing text or images, often leads to semantically incorrect results. Prior state-of-the-art works have typically used media files as covers or as references for cover synthesis. This scope of improvement has inspired us to propose a novel data hiding technique by synthesizing self-sufficient, independent object without using any cover, even as metadata for data hiding. The approach focuses on synthesis of a database, by generating a dataset for the domain values of the attributes of it. Application of comparison-based sorting technique to the dataset, reveals the hidden message. The skill of the technique lies in unlimited hiding capacity, while preserving the semantic integrity of the database. Multiple security measures are taken into account along with thorough analysis of time complexity, to evaluate the efficacy of our method, that surpasses recently proposed approaches, providing solution for highly resistant covert communication.

Digital Watermarking Implementation Of Digital Watermarking On Images Using The Least Significant Bit Method

The ease of accessing the internet in this modern era has led to illegal crimes, especially data copying, data distribution and abuse of intellectual property rights. From these problems emerged a method of securing data and information, namely watermark. Watermark is used for data security techniques, both for copyright protection and digital signatures in the visible and invisible realms. One of the data security techniques used here is to use the least significant bit (LSB) method. This method is used for data security or images that contain watermarks, for example on currency there is usually a logo to distinguish real and fake currencies. This study uses nine host images taken from the https://www.kaggle.com/datasets/felicepollano/watermarked-not-watermarked-images dataset with different sizes, namely 513 x 513 pixels, 488 x 350 pixels, 467 x 350 pixels, 500 x 333 pixels, 512 x 301 pixels, 490 x 350 pixels, 500 x 332 pixels, 400 x 266 pixels, and 500 x 308 pixels. As for the label image, it uses the uty logo which has a size of 50 x 50 pixels, 80 x 80 pixels, and 124 x 124 pixels. From the results of the watermark test that has been carried out using the LSB method, the average PNSR value is 65 dB, so it can be concluded that the watermark research using the LSB method gets pretty good image results and can be used for data security.
 Keywords: Watermark, Least Significant Bit, Peak Signal to Noise Ratio (PNSR)

Securing Non-Terrestrial FSO Link with Public Key Encryption Against Flying Object Attacks

Free Space Optical (FSO) communication has potential terrestrial and non-terrestrial applications. It allows large bandwidth for higher data transfer capacity. Due to its high directivity, it has a potential security advantage over traditional radio frequency (RF) communications. However, eavesdropping attacks are still possible in long non-terrestrial transmission FSO links, where the geometry of the link allows foreign flying objects such as Unmanned Aerial vehicles (UAVs) and drones to interrupt the links. This exposes non-terrestrial FSO links to adversary security attacks. Hence, data security techniques implementation is required to achieve immune FSO communication links. Unlike the commonly proposed physical layer security techniques, this paper presents a lab-based demonstration of a secured FSO communication link based on data cryptography using the GNU Radio platform and software-defined radio (SDR) hardware. The utilized encryption algorithm (Xsalsa20) in this paper requires high-time complexity to be broken by power-limited flying objects that interrupt the FSO beam. The results show that implementing cryptographic encryption techniques into FSO systems provided resilience against eavesdropping attacks and preserved data security. The experiment results show that, at a distance of 250 mm and laser output power of 10 mW, the system achieves a packet delivery rate of 92% and transmission rate of 10 Mbit/s. This is because the SDR used in this experiment requires a minimum received electrical amplitude of 27.5 mV to process the received signal. Long distance and higher data rates can be achieved using less sensitive SDR hardware.

BBRP22 based security technique for data security

Nowadays data plays major role in the current internet world. People generate more data through online media. The generated data are not secured properly and can easily get hacked by the hackers. To overcome from this data security issue, we have planned to apply BBRP25 technique to secure the data. BBRP22 technique has 6 phases. To apply this technique, we must follow the given below steps:1. To track down the great key S; 2. To get the Z1 & Z2 values from indivisible numbers; 3. To view as the an and b values in lattice; to find the values with the assistance k; and trade x and y values. 4. To get the T-test values and match those numbers. 5. To find the n esteem by utilizing k. 6. Apply the n values in legitimate condition; and trade x and y values. The data will be fully secured by applying BBRP22 strategy while compared to ChaCha.