Hash Function Research Articles

BlockTender: A Trustworthy System

The tendering process is a critical component in the procurement practices of governments and companies worldwide. However, this process often encounters challenges that undermine its efficiency, transparency, and security. Traditional tendering methods are plagued by issues such as complex documentation, lack of transparency, susceptibility to corruption, and significant security vulnerabilities. To address these challenges, our project introduces a novel approach that integrates blockchain technology into the tendering process. This integration aims to revolutionize the way tenders are issued, managed, and awarded by leveraging the strengths of blockchain, such as decentralization, immutability, and advanced cryptographic security. Our system comprises three main modules—Admin, Tender Officer, and Bidder—each designed to streamline the respective functionalities within the tendering cycle. By utilizing smart contracts for process automation and cryptographic hash functions (SHA-256) for data integrity, the proposed system not only enhances the security and transparency of the tendering process but also significantly reduces the risks of corruption and breaches. The adoption of blockchain technology in tendering processes marks a significant leap forward in procurement practices, offering a more secure, efficient, and transparent method for conducting transactions.

INNBC DApp, a decentralized application to permanently store biomedical data on a modern, proof-of-stake (POS), blockchain such as BNB Smart Chain

BackgroundA blockchain can be described as a distributed ledger database where, under a consensus mechanism, data are permanently stored in records, called blocks, linked together with cryptography. Each block contains a cryptographic hash function of the previous block, a timestamp, and transaction data, which are permanently stored in thousands of nodes and never altered. This provides a potential real-world application for generating a permanent, decentralized record of scientific data, taking advantage of blockchain features such as timestamping and immutability.ImplementationHere, we propose INNBC DApp, a Web3 decentralized application providing a simple front-end user interface connected with a smart contract for recording scientific data on a modern, proof-of-stake (POS) blockchain such as BNB Smart Chain. Unlike previously proposed blockchain tools that only store a hash of the data on-chain, here the data are stored fully on-chain within the transaction itself as “transaction input data”, with a true decentralized storage solution. In addition to plain text, the DApp can record various types of files, such as documents, images, audio, and video, by using Base64 encoding. In this study, we describe how to use the DApp and perform real-world transactions storing different kinds of data from previously published research articles, describing the advantages and limitations of using such a technology, analyzing the cost in terms of transaction fees, and discussing possible use cases.ResultsWe have been able to store several different types of data on the BNB Smart Chain: raw text, documents, images, audio, and video. Notably, we stored several complete research articles at a reasonable cost. We found a limit of 95KB for each single file upload. Considering that Base64 encoding increases file size by approximately 33%, this provides us with a theoretical limit of 126KB. We successfully overcome this limitation by splitting larger files into smaller chunks and uploading them as multi-volume archives. Additionally, we propose AES encryption to protect sensitive data. Accordingly, we show that it is possible to include enough data to be useful for storing and sharing scientific documents and images on the blockchain at a reasonable cost for the users.ConclusionINNBC DApp represents a real use case for blockchain technology in decentralizing biomedical data storage and sharing, providing us with features such as immutability, timestamp, and identity that can be used to ensure permanent availability of the data and to provide proof-of-existence as well as to protect authorship, a freely available decentralized science (DeSci) tool aiming to help bring mass adoption of blockchain technology among the scientific community.

Enhancing Smart Communication Security: A Novel Cost Function for Efficient S-Box Generation in Symmetric Key Cryptography

In the realm of smart communication systems, where the ubiquity of 5G/6G networks and IoT applications demands robust data confidentiality, the cryptographic integrity of block and stream cipher mechanisms plays a pivotal role. This paper focuses on the enhancement of cryptographic strength in these systems through an innovative approach to generating substitution boxes (S-boxes), which are integral in achieving confusion and diffusion properties in substitution–permutation networks. These properties are critical in thwarting statistical, differential, linear, and other forms of cryptanalysis, and are equally vital in pseudorandom number generation and cryptographic hashing algorithms. The paper addresses the challenge of rapidly producing random S-boxes with desired cryptographic attributes, a task notably arduous given the complexity of existing generation algorithms. We delve into the hill climbing algorithm, exploring various cost functions and their impact on computational complexity for generating S-boxes with a target nonlinearity of 104. Our contribution lies in proposing a new cost function that markedly reduces the generation complexity, bringing down the iteration count to under 50,000 for achieving the desired S-box. This advancement is particularly significant in the context of smart communication environments, where the balance between security and performance is paramount.

SEAF-IoD: Secure and efficient user authentication framework for the Internet of Drones

The Internet of Drones (IoD) stands as a rapidly advancing technology, finding applications across civilian, military, and industrial domains, facilitating the efficient execution of challenging tasks. However, the IoD environment introduces a plethora of security concerns. Drones, for example, must exchange critical information with control station servers and users through open and unsecured wireless channels. Consequently, protecting these sensitive data becomes paramount, leading to the development of SEAF-IoD, a secure and efficient user authentication framework for the IoD, as presented in this paper. SEAF-IoD relies on symmetric encryption, physical uncloneable functions (PUF), and hash functions. This framework empowers users to securely establish connections and obtain real-time data from specific drones deployed within the IoD environment. Furthermore, the utilization of PUF holds great promise in achieving cost-effective security. PUF obviates the necessity to store confidential keys in device memory, offering a potential alternative for establishing a more secure and cost-efficient authentication framework for IoD systems. PUF empowers the SEAF-IoD to enhance its resilience against privileged insider attacks and drone/device capture attempts. To ensure the robustness of SEAF-IoD, it undergoes rigorous validation using BAN logic and Scyther simulation. Furthermore, an informal analysis affirms that SEAF-IoD fulfills critical security requirements and effectively thwarts various adversarial threats, including privileged insider, replay, and impersonation attacks. A comprehensive comparison of SEAF-IoD against existing schemes highlights its resilience and superiority in safeguarding IoD environments.

Implementation of Smart KYC using Blockchain

The know your customer or know your client (KYC) is a guideline for the banking system to validate a customer using identity, appropriateness, risk assessment in establishing a banking relationship. With the growing concern of security, the KYC process is complex and involves a high cost for completing for a single customer. In this work, we propose an economical, swift, secure, and transparent platform for KYC document verification for the Banking system through InterPlanetary File System (IPFS) and blockchain technology. The proposed system allows a customer to open an account at one Bank, complete the KYC process there, and generate a hash value using the IPFS network and share it using the blockchain technique. Upon receiving the private key, any Bank/financial organization can retrieve, store customer data (i.e., KYC) securely using IPFS network if the customer wishes to open another account in that Bank/financial organization. The proposed system can save time, money, and repetitive work during the KYC process when someone tries to open an account at multiple Banks

Blockchain Technology: Transforming IoT and Finance with Privacy and Security Considerations

A Block chain, is a growing list of information, called blocks, which are linked using cryptography. A Block chain is a decentralized, distributed and a public digital ledger that is used to record transactions across many devices so that any involved record cannot be changed easily, without modifying all subsequent blocks, because of this, Block chain has found its use in wide-ranging fields. This system, therefore, describes the role of Block chain in IoT and financial applications, two fields which will be benefitted the most by it. Furthermore, this paper examines the privacy and security concerns related to it and shares some insights on how these problems can be tackled. In this paper, we have reviewed multiple such papers in which similar issues were addressed. Lastly, the public perception of block chain technology is taken to addresses how block chain is perceived in different segments of society Keywords—framework; block chain; Scalable paymentVerification; Cryptographic hash function; Serial Communication; Transaction data.

An Efficient Lightweight Authentication Scheme for Smart Meter

With the rapid development of the information age, smart meters play an important role in the smart grid. However, there are more and more attacks on smart meters, which mainly focus on the identity authentication of smart meters and the security protection of electricity consumption data. In this paper, an efficient lightweight smart meter authentication scheme is proposed based on the Chinese Remainder Theorem (CRT), which can realize the revocation of a single smart meter user by publishing a secret random value bound to the smart meter identity. The proposed scheme not only protects the security of smart meter electricity consumption data by using encryption, but also resists identity attacks from both internal and external adversaries by using hash functions and timestamps. Experiment shows that the proposed scheme has lower computation overhead and communication overhead than other authentication schemes and is more suitable for smart meter authentication.

Lightweight blockchain-based remote user authentication for fog-enabled IoT deployment

The Internet of Things (IoT) seeks to enhance human life by embedding everyday objects with intelligence. As deployed in diverse environments, IoT devices exchange substantial data to offer autonomously smart and innovative services. Cloud computing serves as an effective solution for processing and storing data from IoT devices, enabling remote access for end-users. However, authenticating remote users poses a critical challenge. Although several existing schemes tackle this challenge, they have notable security and performance weaknesses. This paper introduces a lightweight, distributed multi-factor authentication scheme for remote users in IoT. The proposed approach, named Lightchain, integrates blockchain technology and fog computing while incorporating a lightweight cryptographic hash function. The security of Lightchain is rigorously confirmed through formal verification using the well-recognized Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. Additionally, we develop and assess Lightchain’s functionality using the solidity language across diverse use cases. A comparative analysis is presented to evaluate performance costs and security requirements against recent methods. The proposed scheme demonstrates efficiency and robustness, making it well-suited for a range of IoT applications.

Zero-shot discrete hashing with adaptive class correlation for cross-modal retrieval

Zero-shot retrieval aims to transfer knowledge from seen classes to unseen classes by embedding semantic information on class attributes, thus solving the unseen class retrieval problem. However, existing works have focused mainly on unimodal zero-shot retrieval tasks. In this paper, we introduce an efficient method, termed zero-shot discrete hashing with adaptive class correlation (ZSDH-ACC), to speed up cross-modal retrieval. Specifically, this proposed method combines label information with class attribute information to construct a semantic enhancement embedding, in which the problem of class attribute correspondence of multilabel instances can be solved. Furthermore, we learn semantic enhancement embedding to merge more semantic information for feature representation, and its goal is to learn more discriminative hash codes and hash functions. In addition, our proposed method adaptively learns the correlation between class attributes and then embeds more class attribute information into hash codes. Finally, pairwise similarity is used to constrain the learning of hash codes, and thus more discriminative hash codes can be generated. Extensive experimental results on four benchmark multimodal datasets demonstrate that the proposed ZSDH-ACC method can achieve encouraging performance in cross-modal retrieval tasks. The source code of this paper can be obtained from https://github.com/szq0816/ZSDH_ACC.

An improved deep hashing model for image retrieval with binary code similarities

The exponential growth of data raises an unprecedented challenge in data analysis: how to retrieve interesting information from such large-scale data. Hash learning is a promising solution to address this challenge, because it may bring many potential advantages, such as extremely high efficiency and low storage cost, after projecting high-dimensional data to compact binary codes. However, traditional hash learning algorithms often suffer from the problem of semantic inconsistency, where images with similar semantic features may have different binary codes. In this paper, we propose a novel end-to-end deep hashing method based on the similarities of binary codes, dubbed CSDH (Code Similarity-based Deep Hashing), for image retrieval. Specifically, it extracts deep features from images to capture semantic information using a pre-trained deep convolutional neural network. Additionally, a hidden and fully connected layer is attached at the end of the deep network to derive hash bits by virtue of an activation function. To preserve the semantic consistency of images, a loss function has been introduced. It takes the label similarities, as well as the Hamming embedding distances, into consideration. By doing so, CSDH can learn more compact and powerful hash codes, which not only can preserve semantic similarity but also have small Hamming distances between similar images. To verify the effectiveness of CSDH, we evaluate CSDH on two public benchmark image collections, i.e., CIFAR-10 and NUS-WIDE, with five classic shallow hashing models and six popular deep hashing ones. The experimental results show that CSDH can achieve competitive performance to the popular deep hashing algorithms.

Authorization of Aadhar data using Diffie Helman key with enhanced security concerns

In today’s digital era, the security of sensitive data such as Aadhaar data is of utmost importance. To ensure the privacy and integrity of this data, a conceptual framework is proposed that employs the Diffie-Hellman key exchange protocol and Hash-based Message Authentication Code (HMAC) to enhance the security. The proposed system begins with the preprocessing phase, which includes removing noise, standardizing formats and validating the integrity of the data. Next, the data is segmented into appropriate sections to enable efficient storage and retrieval in the cloud. Each segment is further processed to extract meaningful features, ensuring that the relevant information is preserved while reducing the risk of unauthorized access. For safeguarding the stored Aadhaar data, the system employs the Diffie-Hellman key exchange protocol which allows the data owner and the cloud service provider to establish a shared secret key without exposing it to potential attackers. Additionally, HMAC is implemented to verify the identity of users during the login process. HMAC enhances security by leveraging cryptographic hash functions and a shared secret key to produce a distinct code for each login attempt. This mechanism effectively protects the confidentiality and integrity of stored data. The combination of Diffie-Hellman key exchange and HMAC authentication provides a robust security framework for Aadhaar data. It ensures that the data remains encrypted and inaccessible without the secret key, while also verifying the identity of users during the login process. This comprehensive approach helps preventing unauthorized access thereby protecting against potential attacks, instilling trust and confidence in the security of Aadhaar data stored in the cloud. Results of the article depict that the proposed scheme achieve 0.19 s of encryption time and 0.05 s of decryption time.

Frequency-domain image encryption based on IWT and 3D S-box

Most of the existing spatial domain image encryption techniques suffer from the difficulty of resisting cryptographic attacks. For this reason, this paper proposes a frequency-domain based digital image encryption scheme by combining Integer Wavelet Transform (IWT), three-dimensional S-box and chaotic system. First, the plaintext image is decomposed into different frequency subbands by IWT to map the digital image from spatial domain to frequency domain. Second, the plaintext hash value is selected as the dynamic key, and dynamic chaotic pseudo-random sequences with associations are generated, which are used for the encryption of each module respectively. Then, a three-dimensional S-box is designed to encrypt the information-rich low-frequency information using ‘bit-permutation three-dimensional S-box replace ciphertext interleaved diffusion’, while the high-frequency information is encrypted using a lightweight ‘XOR-row column permutation’ operation. Finally, the secure ciphertext for public channel transmission is obtained by the reconstruction method. The scheme of this paper, the frequency domain transformation is implemented through IWT, which enhances the ability to resist attacks. In addition, the diffusion encryption modules employ the introduction of ciphertext interleaved diffusion and parallel encryption mechanisms, thus the algorithm has the ability to resist plaintext attacks. Theoretical analysis and empirical results show that the algorithm has excellent numerical statistical analysis results, which corroborate that it has good confusion, diffusion and avalanche effects, and is able to resist various common cryptographic attacks. The frequency domain image encryption scheme proposed in this paper is a preferred high-security digital image privacy protection technique, so it has good application prospects.

Privacy-security oriented chaotic compressed sensing data collection in edge-assisted mobile crowd sensing

As a data-centric network, the Mobile Crowd Sensing (MCS) collects and uploads sensing data through intelligent terminal devices carried by workers. However, due to resource limitations, the confidentiality, integrity and communication cost issues of sensing data have not been well coordinated and resolved in the actual MCS data collection process. In this regard, this paper proposes an edge computing-assisted MCS Chaotic Compressed Sensing Secure Data Collection scheme (CCS-SDC), which supports the secure collection of sensing data and saves communication cost. In CCS-SDC, workers first use the encryption algorithm based on chaos theory to encrypt the collected sensing data, and then adopt the hash location algorithm based on chaos theory to calculate the corresponding hash verification code of the sensing data. After receiving the encrypted sensing data transmitted by the worker, the edge server recomputes the hash verification code of the encrypted sensing data and verifies the integrity of the data, which can locate the changed sensing task data to a certain extent. Then the sensing data is compressed and sampled based on the generated chaos measurement matrix to reduce the amount of data transmission and further enhance the confidentiality of the sensing data. In addition, the same hash positioning algorithm is used between the edge server and the sensing platform to protect data integrity. For the changed data located by integrity verification, in addition to choosing to let workers re-sense and submit, the sensing platform can also choose to discard the changed sensing data under appropriate circumstances, and still reconstruct and decrypt the remaining data through the proposed algorithm to obtain effective original sensing data. The experimental evaluation results on real data sets show that CCS-SDC achieves the best effects, not only achieving lower sensing data communication cost than other related schemes, but also better protecting the confidentiality and integrity of sensing data, which is very useful for resource-constrained MCS data collection scenarios.

Vehicular ad-hoc security improvements using decentralised consensus blockchain

For safer roads, a more efficient driving experience, and protection against attackers, the intelligent cars communicate with one another or with the roadside unit (RSU). The fundamental security requirements of Vehicular Ad-hoc Networks (VANETs) must be nonrepudiable, genuine, and incorporate these three. Additionally, protecting against attackers should be done in particular specific situations. However, the VANET's main disadvantages are its centralized design and the absence of procedures for ensuring confidentiality and privacy. In this paper, proposed decentralised consensus blockchain architecture for VANET that uses blockchain technology to address these problems. The VANET no longer needs a central authority or third-party administration thanks to the introduction of the blockchain. In order to ensure data integrity and accelerate up system processing, the hash value of the pseudonyms will be recorded on the blockchain. By eliminating trust difficulties between the entities, this effectively addresses challenges that arise in centralised designs. The suggested method for VANETs security. Experimental investigation demonstrates that the provided architecture outperforms the available options in terms of security enhancement.

S-box design based on logistic skewed chaotic map and modified Rabin-Karp algorithm: applications to multimedia security

A substitution box (S-box) serves as the nonlinearity component in a symmetric key encryption scheme; it directly determines the performance and security level of ciphers. Thus, the construction of an S-box with superior performance and efficiency, specifically in terms of high cryptographic properties, is critical. This research proposes a novel method to construct the S-box using the skewed logistic chaotic map and modified Rabin-Karp rolling hash function without disturbing its mathematical structure. First, iterate the skewed logistic map by selecting a seed value and specifying the parameters to generate the chaotic values. The map’s sensitivity to initial conditions and parameters results in a seemingly random and unpredictable chaotic values. Second, hash the chaotic values using Rabin-Karp for generating sequences of numbers within a specific range (0–255 for an 8-bit S-box). Then an S-box is constructed using the hash values. Performance evaluations indicate that the S-box produced through our suggested approach exhibits superior performance, demonstrating robust resistance against various security threats, including but not limited to linear attacks, differential attacks, and others. To demonstrate the effectiveness of the constructed S-box, this paper goes on to employ it in an image encryption application. Security analyses reveal that the developed image encryption algorithm successfully encrypts diverse types of images, producing cipher images characterized by uniformly distributed histograms. Performance assessments illustrate its high-security level, surpassing several state-of-the-art encryption algorithms.

“A lightweight authentication scheme for 6LoWPAN-based Internet-of -things”

ABSTRACT IPv6-based IoT networks, i.e. 6LoWPAN network, require authentication for security. The existing authentication schemes on symmetric-key based approaches for 6LoWPAN consume huge computational and processing overhead in the literature. In a large network, pre-deployment of the key leads to huge memory consumption due to storing many keys. Furthermore, in asymmetric key cryptography, operations with the public key are computationally expensive, which is unsuitable for resource-constrained devices. We proposed a lightweight key exchange and authentication scheme for 6LoWPAN to mutually authenticate the sensor nodes, the gateway, and the server with less computational overhead and without compromising any security credentials. The authentication scheme helps to generate a session key without storing any secrets in the 6LoWPAN devices. We utilized a one-way hash function and XOR operation to reduce overhead in multi-hop communication. The AVISPA verification tool and the formal verification show that the proposed method is resistant to well-known attacks. The proposed scheme outperforms relevant methods in computational overhead, communication cost, and computation time.

SKHASH: A Python Package for Computing Earthquake Focal Mechanisms

Abstract We introduce a Python package for computing focal mechanism solutions. This algorithm, which we refer to as SKHASH, is largely based on the HASH algorithm originally written in Fortran over 20 yr ago. HASH innovated the use of suites of solutions, spanning the expected errors in polarities and takeoff angles, to estimate focal mechanism uncertainty. SKHASH benefits from new features with flexible input formats and allows users to take advantage of recent advances in constraining focal mechanisms for small magnitude or poorly recorded earthquakes. The 3D locations of earthquakes and the velocity models used are varied when finding acceptable solutions. As a result, source–receiver azimuths are reflective of errors from the earthquake locations and velocity models, in addition to the takeoff angles. Users can consider weighted P-wave first-motion polarities derived from traditional or machine-learning picks, cross-correlation consensus, and/or imputation techniques using SKHASH. Focal mechanism solutions can also be further constrained using traditional, machine learning, and/or cross-correlation consensus S/P amplitude ratios. With improved reporting of individual and collective P polarity and S/P amplitude misfits, users can better evaluate the success of the solutions and the quality of the measurements. The reporting also makes it easier to identify potential issues with metadata, including incorrectly reported station polarity reversals. In addition, by leveraging vectorized operations, taking advantage of an efficient backend Python C Application Programming Interface, and the use of a parallel environment, the Python SKHASH routine may compute mechanisms quicker than the HASH routine.

StealthPassage: Encrypted Text Concealed with Hashing ,

An innovative method of protecting confidential data is to hide it using encryption and decryption. In order to make the secret message disappear to the unaided eye, this encryption method embeds it into the visible text. When it comes to protecting data from unwanted access, the emergence of digital communication has made novel approaches necessary. One such approach is concealed text encryption. In order to better understand of concealed text encryption, this study examines the fundamental algorithms and approaches as well as their principles and methodologies. This text encryption makes certain that the encrypted communication is not revealed to uninvited parties by utilizing cryptography, the art of hiding information within other data. The content of the encrypted file will disappear, which means no one can predict the information hiding behind the whitespace background, and it is very complex to decrypt the encrypted file. This method provides stronger security for our information than other methods of cryptography. Keyword: Encryption, Decryption, Hashing Algorithm

Analyzing FOSS license usage in publicly available software at scale via the SWH-analytics framework

The Software Heritage (SWH) dataset represents an invaluable source of open-source code as it aims to collect, preserve, and share all publicly available software in source code form ever produced by humankind. Although designed to archive deduplicated small files thanks to the use of a Merkle tree as the underlying data structure, querying the SWH dataset presents challenges due to the nature of these structures, which organize content based on hash values rather than any locality principle. The magnitude of the repository, coupled with the resource-intensive nature of the download process, highlights the need for specialized infrastructure and computational resources to effectively handle and study the extensive dataset housed within SWH. Currently, there is a lack of infrastructures specifically tailored for running analytics on the SWH dataset, leaving users to handle these issues manually. To address these challenges, we implemented the SWH-Analytics (SWHA) framework, a development environment that transparently runs custom analytic applications on publicly available software data preserved over time by SWH. Specifically, this work shows how SWHA can be effectively exploited to study usage patterns of free and open-source software licenses, highlighting the need to improve license literacy among developers.

BLOCKCHAIN BASED E-COMMERCE ONLINE APPLICATION

In existing E-commerce application all customers and product details will be stored and managed in single centralized server and if this server crashed due to too many requests and or if server is hacked then services will not be available to other customers and to overcome from this problem, we are migrating E-commerce application to Blockchain which will maintain data at multiple nodes/servers and if one node down then customers can get data from other working nodes. Another advantage of Blockchain is inbuilt support for data encryption and immutability (data cannot be altered by unauthorized users) and it will consider each data as block/transaction and associate each block storage with unique hash code and before storing new records. Blockchain will verify hash code of previous blocks and if all nodes’ blocks verification successful then data is consider as secured. KEYWORDS – Blockchain, Decentralize, E-Commerce, Smart Contracts, Solidity, Hash code.