Approach For Data Security Research Articles

Enhancing image security via chaotic maps, Fibonacci, Tribonacci transformations, and DWT diffusion: a robust data encryption approach

In recent years, numerous image encryption schemes have been developed that demonstrate different levels of effectiveness in terms of robust security and real-time applications. While a few of them outperform in terms of robust security, others perform well for real-time applications where less processing time is required. Balancing these two aspects poses a challenge, aiming to achieve efficient encryption without compromising security. To address this challenge, the proposed research presents a robust data security approach for encrypting grayscale images, comprising five key phases. The first and second phases of the proposed encryption framework are dedicated to the generation of secret keys and the confusion stage, respectively. While the level-1, level-2, and level-2 diffusions are performed in phases 3, 4, and 5, respectively, The proposed approach begins with secret key generation using chaotic maps for the initial pixel scrambling in the plaintext image, followed by employing the Fibonacci Transformation (FT) for an additional layer of pixel shuffling. To enhance security, Tribonacci Transformation (TT) creates level-1 diffusion in the permuted image. Level-2 diffusion is introduced to further strengthen the diffusion within the plaintext image, which is achieved by decomposing the diffused image into eight-bit planes and implementing XOR operations with corresponding bit planes that are extracted from the key image. After that, the discrete wavelet transform (DWT) is employed to develop secondary keys. The DWT frequency sub-band (high-frequency sub-band) is substituted using the substitution box process. This creates further diffusion (level 3 diffusion) to make it difficult for an attacker to recover the plaintext image from an encrypted image. Several statistical tests, including mean square error analysis, histogram variance analysis, entropy assessment, peak signal-to-noise ratio evaluation, correlation analysis, key space evaluation, and key sensitivity analysis, demonstrate the effectiveness of the proposed work. The proposed encryption framework achieves significant statistical values, with entropy, correlation, energy, and histogram variance values standing at 7.999, 0.0001, 0.0156, and 6458, respectively. These results contribute to its robustness against cyberattacks. Moreover, the processing time of the proposed encryption framework is less than one second, which makes it more suitable for real-world applications. A detailed comparative analysis with the existing methods based on chaos, DWT, Tribonacci transformation (TT), and Fibonacci transformation (FT) reveals that the proposed encryption scheme outperforms the existing ones.

Hybrid Cryptographic Approach for Data Security Using Elliptic Curve Cryptography for IoT

The Internet of Things (IoT) technology has changed the contemporary digital world. Devices connected to the IoT have sensors embedded within them. All these devices are purposely connected to share data among them through the Internet. Data sharing among IoT devices needs some security protocols to maintain the privacy and confidentiality of information. IoT devices have less computing power to perform various operations of a cryptographic process. So, there is a need of cryptographic approach to reduce the computational complexity for resource-constrained devices and provide data security. However, storing data over the cloud server also reduces storage overhead, but data transmission via the cloud is not always secure. Data integrity and authentication can be compromised because the end user can only access the data with the help of a cloud server. To ensure the security and integrity of the data, various cryptographic techniques are used. Therefore, in this paper, we propose a secure and optimized hybrid cryptographic scheme for the secure sharing of data by combining Advanced Encryption Standard (AES) and Elliptic Curve Cryptography (ECC). To ensure authentication and data integrity, the proposed scheme primarily uses the Message Authentication Code (MAC). The encrypted messages are stored on a cloud server to reduce storage overhead. The experimental findings demonstrate that the proposed scheme is effective and produces superior results as compared to existing approaches.

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).

Generative Architecture for Data Imputation in Secure Blockchain-enabled Spatiotemporal Data Management

In the era of big data, one of the most critical challenges is ensuring secure access, retrieval, and sharing of linked spatiotemporal data. To address this challenge, this paper introduces a groundbreaking blockchain-enabled evolutionary indirect feedback graph algorithm for the secure management of interconnected spatiotemporal datasets. The algorithm utilizes a generative neural network model for data imputation, predicting and generating plausible values to improve dataset completeness and integrity. The core architecture utilizes blockchain technology to optimize data retrieval efficiency and uphold robust access control mechanisms. The algorithm incorporates indirect feedback mechanisms, allowing users to provide implicit feedback through their interactions, enhancing the relevance and efficiency of data retrieval. In addition. sophisticated graph-based techniques are used to model intricate relationships between data entities, facilitating seamless data retrieval and sharing in interwoven datasets. The algorithm’s data security approach includes comprehensive access control mechanisms, encryption, and authentication mechanisms, safeguarding data confidentiality and integrity. Extensive evaluations show significant enhancements in retrieval performance and access control precision, making the proposed model a promising solution for the secure management of expansive interconnected spatiotemporal data.

Improved End-to-End Data Security Approach for Cloud Computing

Cloud computing is one of the major cutting-edge technologies that is growing at a gigantic rate to redefine computation through service-oriented computing. It has addressed the issue of owning and managing computational infrastructure by providing service through a pay-and-use model. However, a major possible hindrance is security breaches, especially when the sender uploads or the receiver downloads the data from a remotely accessed server. It is a very generic approach to ensuring data security through different encryption techniques, but it might not be able to maintain the security standard. This paper proposes an end-to-end data security approach from the sender side to the receiver side by adding extra padding sequences, as well as randomized salting, followed by hashing and an encryption technique. The effectiveness of the proposed method was established using both a simulated system and mathematical formulations with different performance metrics. Furthermore, its performance was compared with those of contemporary algorithms, showing that the proposed algorithm creates a larger ciphertext that is almost impossible to crack due to randomization modules. However, it has significantly longer encryption and decryption times, although our primary concern is ensuring security, not reducing time.

Internet of things-blockchain integration: a robust data security approach for end-to-end communication

<span>The integration of internet of things (IoT) and blockchain technology has been proposed as a promising solution to address the challenges related to security, scalability, and privacy. This integration enables the creation of secure and decentralized systems that allow devices to interact with each other and exchange data in a transparent and trustworthy manner. The significant research work has been carried out by researcher on IoT and blockchain integration to utilize their combine potential in smart applications. However, due to limitation and scope of emerging technologies, it is essential to develop robust security frameworks that address the challenges and ensure the secure data communication from IoT node to blockchain network. IoT devices come up with constrained nature and limited security mechanisms along with weak access control policy. Our work includes heterogeneous IoT and blockchain ecosystem that senses and store data intelligently after proper validation with verification into decentralized distributed blockchain network. Our proposed work includes a robust approach to convey potential data security issue to protect end to end information with suitable authorization, access control policy, device to device data protection and data integrity specially when data moving from IoT devices to blockchain network.</span>

Software-Based Security Approach for Networked Embedded Devices

As the Internet of Things (IoT) continues to expand, data security has become increasingly important for ensuring privacy and safety, especially given the sensitive and, sometimes, critical nature of the data handled by IoT devices. There exist hardware-based trusted execution environments used to protect data, but they are not compatible with low-cost devices that lack hardware-assisted security features. The research in this paper presents software-based protection and encryption mechanisms explicitly designed for embedded devices. The proposed architecture consists of two parts: the Agent, which is designed to work with low-cost, low-end devices without requiring modifications to the underlying hardware, and the Computing Module, which is designed for slightly more computationally powerful devices. The Computing Module enables devices to write data in protected memory and continuously verifies its integrity to provide protection. Additionally, it utilizes the Agents located on the device to safeguard device applications against attacks by requesting the Agent to generate an application code signature and validating it. The proposed solution is an alternative data security approach for low-cost IoT devices without compromising performance or functionality. Our work underscores the importance of developing secure and cost-effective solutions for protecting data in the context of IoT.

Data Security Approach in Remote Healthcare Monitoring

Data Security Approach in Remote Healthcare Monitoring

Towards Developing Privacy-Preserved Data Security Approach (PP-DSA) in Cloud Computing Environment

In the present scenario of rapid growth in cloud computing models, several companies and users started to share their data on cloud servers. However, when the model is not completely trusted, the data owners face several security-related problems, such as user privacy breaches, data disclosure, data corruption, and so on, during the process of data outsourcing. For addressing and handling the security-related issues on Cloud, several models were proposed. With that concern, this paper develops a Privacy-Preserved Data Security Approach (PP-DSA) to provide the data security and data integrity for the outsourcing data in Cloud Environment. Privacy preservation is ensured in this work with the Efficient Authentication Technique (EAT) using the Group Signature method that is applied with Third-Party Auditor (TPA). The role of the auditor is to secure the data and guarantee shared data integrity. Additionally, the Cloud Service Provider (CSP) and Data User (DU) can also be the attackers that are to be handled with the EAT. Here, the major objective of the work is to enhance cloud security and thereby, increase Quality of Service (QoS). The results are evaluated based on the model effectiveness, security, and reliability and show that the proposed model provides better results than existing works.

A Novel Approach to Reduce Breaches of Aircraft Communication Data

Aircraft are complex systems that rely heavily on monitoring and real-time communications with the base station. During aviation and flight operations, diverse data are gathered from different sources, including the Cockpit Voice Recorder (CVR), Flight Data Recorder (FDR), logbook, passenger data, passenger manifest etc. Given the high sensitivity of flight data, it is an attractive target for adversaries which could result in operational, financial and safety related incidents. Communications between aircraft pilots and air traffic controllers are all unencrypted. The data, mainly audio communication files, are placed openly within data centers on the ground stations which could lead to a serious compromise in security and privacy. One may rely on the cloud owing to its on-demand features but to thwart possible attacks, the data need to be encrypted first, giving rise to the issue of conducting search over encrypted data. This research presents a novel approach for data security in aviation industry by introducing a semantic-based searchable encryption scheme over the cloud. The designed system has proven to be extraordinarily effective for semantic-based searchable encryption at the word and the text level. The rigorous security and complexity analysis shows that the proposed solution provides a high level of security and efficiency and can be effectively deployed in the aviation sector. The designed scheme is tested through a real-world aviation dataset collected to demonstrate the significance of this research. The proof of concept proves to be secure, privacy-preserving and lightweight while resisting distinguishability attacks.

Healthcare Internet of Things (HIoT) data security enhancement using blockchain technology

In recent years, the Internet of Things (IoT) has attracted more attention after the integration of IoT devices with the cloud for data management. IoT is used for sharing data in healthcare services. However, security and privacy vulnerabilities still exist in data transfers to and from cloud environments. Due to memory limitations, it is difficult to implement security protocols in IoT devices. So an intermediate secure node is established to enhance data security and privacy while handling healthcare data. Blockchain is a renowned technology that is adopted in various data management and security applications, but its potential is not unleashed effectively in healthcare data management. Therefore in this research work, firstly, the data is pre-processed and then the Ant colony optimization method is used to find the shortest path for efficient data delivery. And, a blockchain based data security approach for healthcare data management is presented. The main objective is to enhance security against healthcare data threats. In the IoTs fog layer, a public-permissioned blockchain security process with elliptical curve cryptography and digital signature is presented as a distributed ledger database that provides immutable security, transparency in transactions, and prevents data tampering. The performance of the proposed approach is verified through various parameters like certificate generation time and size, data retrieval time, and size for better validation.

Performance Analysis and Systematic Review of Privacy Preservation-Based Authentication Models and Cryptographic-Based Data Protocols

This paper proposes a privacy preservation-based data security and secure data protocol for distributed Data Storage and Communication (DSaC). An effective performance analysis is done between privacy preservation-based data security approach for authenticated encrypted access and secure data protocol for DSaC in cloud and the approaches are compared with the traditional schemes like Ins-PAbAC, Homomorphic Proxy Re-encryption (HPRE), LAM-CIoT, SA-EDS, Advanced Encryption Standard (AES), and Data Encryption Standard (DES). The proposed privacy preservation approach achieved a minimum time of 12614ms, maximum detection rate of 0.985, maximum privacy factor of 0.645, maximum TPR of 0.785, and maximum TNR of 0.777 for Switzerland dataset and the ACS-based secure data protocol achieved a minimum time of 5527ms, maximum detection rate of 0.953, minimum E2E delay of 85, maximum TPR of 0.817, and maximum TNR of 0.754 for Cleveland dataset.

Secure Model for IoT Healthcare System under Encrypted Blockchain Framework

With the advancements in the new technologies like IoT, the healthcare sector is also growing rapidly. The core concept of introducing IoT in the healthcare centers is to make it remotely accessible, so that communication between doctor and patient can be easy, and diagnosis of any disease can be remotely done through the Internet in case of emergency. The major objective of this study is to develop a security framework for the healthcare industry that can encrypt secret data on cloud servers using block-based data encoding. Since any information that is available on the Internet is vulnerable to various attacks, and the medical records of the patients carry sensitive information that must not be accessible to any unauthorized or unauthentic person, in this context, the concept of Blockchain (BC) technology was introduced in the healthcare systems. In the past few years, a number of BC based healthcare models were proposed in the system; however, these systems are decentralized in nature, which is a feature of Blockchain technology, but in certain applications, especially in healthcare, this feature gave rise to a problem termed as disease overlapping when the count of chains gets increased. To solve this issue, a BC based framework is used in this work that has a feature of creating a separate block in the chain every time whenever any alteration in information about patient’s health, any allergies, new symptoms, medications, etc. is updated. In addition to this, securing the sensitive information of patients is taken into consideration by developing an improved and enhanced multilayer Blockchain based IoT data security approach that not only protects the data, but also builds the trust between patients/user and healthcare service providers. The main focused area of this research article is to propose a security framework for healthcare domain that can encrypt the confidential data over cloud server under block-based data encoding. In the proposed approach, 128-bit AES key is generated in order to support the SHA-256 hashing algorithm. Individual user’s data is subdivided to blocks and encrypted to secure it from unauthorized access. An interface-based system is designed to present the real-world usage of the proposed model in healthcare application. Finally, the effectiveness of the proposed approach is validated in the MATLAB software in terms of MAE, RMSE, MSE, encryption time, and decryption time. The RSA and DSA are the most trending encryption algorithms. These algorithms are crucial components of Blockchain technology, implemented in the proposed work, and later on, their performances are also compared with each other to check their effectiveness. The simulation results demonstrated that the proposed encrypting algorithm surpasses the other encryption approaches such as RSA and DSA in all factors to prove its supremacy. The experimental results show that the encryption and decryption time are lowest in the proposed framework; therefore, its performance is more effective and robust. It is also more effective and resilient.

Secure Cloud Data Storage Using Hybrid Cryptography

Abstract: Nowadays a huge number of organizations use the cloud for storing Big data. And some of the sectors have sensitive data, for example, Military, Agencies, Colleges, Industries, etc. The data can be retrieved when the user requests it. And others can also access the data. Cloud computing provides a lot of features with affordable prices and knowledge accessibility by using the Internet. Security is the main concern in the cloud computing environment as clients store secret information with cloud providers, but sometimes these providers may not be trustful. Splitting data in a safe approach while protecting data from an untrusted cloud is still a demanding topic. In this paper we ensure the right approach for data security and privacy, using Blowfish, and RSA/SRNN algorithms. Keywords: Cloud Computing, Data storage, RSA/SRNN algorithm, Blowfish algorithm, Data storage.

Addressing new data privacy realities affecting agricultural research and development: A tiered‐risk, standards‐based approach

AbstractConcerns related to data ownership and privacy cut across all sectors of our economy, shape public–private research relationships, and, if left unaddressed, threaten to limit the potential gains to be had from the “big data” revolution. Rather than offer a one‐size‐fits‐all approach to dealing with data privacy and security concerning food and agricultural research and development (R&D), we propose a three‐tiered data security approach based on three tiers of risk tolerance: high, medium, and low with general guidelines explicitly mapped to standards. Data privacy and security are not costless, and so an economically informed approach that weighs the cost of a potential security breach against the benefits from accessing and using data for R&D is a more practical approach than treating all data equally from a risk management perspective. These tiers of risk must be understood in relation to standards for there to be meaningful governance of these data. We begin by characterizing the rapidly evolving nature of data privacy in an agricultural R&D context before providing an overview of the key means by which the privacy of agricultural data is presently being governed in various regions of the world. As an illustration of the approach that we propose, we apply our tiered risk and standards‐based approach to the CGIAR's Responsible Data Guidelines. This approach is similar to that used by the healthcare sector to effectively implement data privacy requirements and promote an awareness among key stakeholders of the need for and importance of well‐defined data privacy standards.

Hybrid probabilistic triple encryption approach for data security in cloud computing

Hybrid probabilistic triple encryption approach for data security in cloud computing

Provably Secure Authentication Approach for Data Security in Cloud Using Hashing, Encryption, and Chebyshev-Based Authentication

Secure and efficient authentication mechanism becomes a major concern in cloud computing due to the data sharing among cloud server and user through internet. This paper proposed an efficient Hashing, Encryption and Chebyshev HEC-based authentication in order to provide security among data communication. With the formal and the informal security analysis, it has been demonstrated that the proposed HEC-based authentication approach provides data security more efficiently in cloud. The proposed approach amplifies the security issues and ensures the privacy and data security to the cloud user. Moreover, the proposed HEC-based authentication approach makes the system more robust and secured and has been verified with multiple scenarios. However, the proposed authentication approach requires less computational time and memory than the existing authentication techniques. The performance revealed by the proposed HEC-based authentication approach is measured in terms of computation time and memory as 26ms, and 1878bytes for 100Kb data size, respectively.

GraphCrypto: Next generation data security approach towards sustainable smart city building

Data confidentiality and integrity are essential security goals in the data communication in the smart city or similar applications. Despite significant changes in modern data communication systems and devices, the cryptosystems are still the primary option to achieve data security. Several cryptosystems have been developed, implemented and standardized to date. However, there is always a continuous demand for a new cryptosystem for providing security during data communication. In this paper, a novel symmetric cryptosystem is presented for achieving data confidentiality. The proposed cryptosystem is a graph-based system, where an algebraic structure of directed graphs along with a novel operation is defined to provide the base of the cryptosystem. Here, a directed graph represents a plaintext, a ciphertext, and a secret key as well. The defined operation is used for encrypting and decrypting plaintext and ciphertext graphs. The proposed cryptosystem provides a simplified transformation process and representation of plaintext to plaintext graph. The correctness of the proposed cryptosystem is validated, and also shown that the conventional brute-force approach to obtain the key from either plaintext or ciphertext is exponential and this computational time is significantly higher than AES. This implies that the proposed cryptosystem is highly secured against this attack. The proposed cryptosystem is implemented and compared with AES and the results infer that it incurs a marginally higher execution time than the AES for larger plaintext due to the involvement of matrix operations.

Cryptographic Solution for Security Problem in Cloud Computing Storage During Global Pandemics

Cloud computing has emerged as a potential substitute over traditional computing systems during the time of the COVID-19 pandemic. Almost all organizations shift their working from conventional ways to the online form of working. Most of the organizations are planning to permanently change some % of their work to online WFH (Work from Home) mode. There are numerous benefits of using cloud services in terms of cost, portability, platform independence, accessibility, elasticity, etc. But security is the biggest barrier when one wants to move towards cloud computing services, especially the cloud storage service. To overcome the problem of security in cloud storage systems, we have presented an approach for data security in cloud storage. The proposed approach uses the cryptographic methods and provides security and monitoring features to the user data stored in cloud storage systems. The proposed approach continuously monitors user’s data for any kind of modification by attackers. Thus, approach not only provides data security but also improves user’s trust on cloud based storage services.

Implementation of Rivest Cypher 4 algorithm in Security Assertion Mark-up Language protocols on Single Sign-On services

Single Sign-On (SSO) is an authentication service that allows users to use a set of credential data to access multiple applications. The SSO can be implemented using Security Assertion Mark-up Language (SAML) which is recognized as a framework or standard for sending open messages that allow identity and security information to be shared to each entity. Credential data sent over the network enable unauthorized users to capture the data and this will be fatal since the data can be used to access all applications in the SSO entity. This study aims to propose a credible data security approach that is reliable so that the data is not easily read by unauthorized users even with the dictionary attacks. This security method is performed using the Rivest Cypher 4 (RC4) algorithm. This study is resulting in two major phenomena, (1) the utilization of the RC4 algorithm on SAML in SSO services has proven to be an effective data security approach for dictionary attacks, (2) the formulation of the RC4 algorithm on SAML has proven to not interfere with SSO services in the user authentication process.