"Online Transaction Security Enhancement": An Algorithm Based on Cryptography

Blockchain technology has emerged as a revolutionary tool for securing online transactions by providing a decentralized, transparent, and immutable ledger for digital records. This technology operates on the principles of cryptography and consensus mechanisms, making it resistant to tampering and fraud. As online transactions have become an essential part of modern economies, ensuring the security and integrity of these transactions has become a critical challenge. Blockchain addresses these concerns by enabling peer-to-peer transactions without the need for intermediaries, thereby reducing the risk of fraud, data breaches, and financial theft. The purpose of this paper is to explore the role of blockchain technology in enhancing the security of online transactions, focusing on its implementation in various industries such as finance, healthcare, and e-commerce. This paper will analyze the fundamental features of blockchain, including its decentralized nature, transparency, and the cryptographic techniques used to ensure data integrity. Additionally, it will examine the challenges associated with the widespread adoption of blockchain, including scalability issues, regulatory concerns, and technological barriers. The paper also discusses the future potential of blockchain technology, particularly in relation to its integration with emerging technologies like artificial intelligence and the Internet of Things. By reviewing current trends, case studies, and research findings, this paper aims to provide a comprehensive analysis of blockchain technology’s impact on securing online transactions and its potential to revolutionize digital economies.

Blockchain is a digital, decentralized ledger system that enables secure and transparent online transactions. It is an innovative technology that can enhance security and streamline online transactions benefiting both businesses and users. Blockchain technology has a notable feature in that it ensures the security and protection of transactions done online. They do so using cryptography, which allows information to be encrypted and prevents it from being altered. Every transaction is recorded in a block that is then linked to the previous one, resulting in an unchangeable chain of blocks. Decentralization is yet another gift from blockchain technology. Blockchain transactions are based on the idea of trust built into the network or community, rather than in a central authority (a bank, government) as with traditional online transactions. In addition, blockchain technology permits a higher rate of transparency and accountability in real-time online transactions. Every transaction is available to everyone, and it is in the blockchain each placed with all transactions. Increased transparency means more trust and less fraud which improves ethics in businesses.

Current online transactions of aquatic products are often plagued by problems such as low efficiency, high platform supervision cost, insufficient trust and leakage of transaction data. Blockchain has been widely used in many different fields due to its decentralization, non-tampering and distributed data management. In order to resolve the existing problems, a blockchain-based aquatic product trading matching model integrated with credit mechanisms is proposed in this study to improve the efficiency, quality, security and satisfaction of online transactions for aquatic products. Then, based on this model, an online trading matching prototype system for aquatic products is developed, taking the Hyperledger Fabric as the underlying architecture. The performance testing of the prototype system has demonstrated that the introduction of the credit mechanism has a certain improvement effect on the trading matching results of aquatic products, and the system can complete more than 1000 transactions within half an hour, which can satisfy the normal business-to-business online transaction needs for aquatic products. To a certain extent, it can reduce the security risks and supervision cost, and improve the efficiency and satisfaction of online transaction. This study can also bring insights to blockchain-based online trading models in other industry fields.

Ensuring data security is an essential priority to be put forward once there will be a digital transmission between any two or more targeted audience. Hence, the objective of this paper was to propose a better data security model for a protective information exchange on the internet with steganographic and cryptographic algorithms. Three cryptographic symmetric key encryption algorithm (RC6, Rijndael and TwoFish) and four steganographic carrier object (Image, audio, text and video) were considered. Data obtained show that Rijndael (AES) takes less encipherment and decipherment time compare to RC6 and TwoFish in cryptographic symmetric key encryption algorithm, while image carrier achieves better Peak-Signal-to-Noise Ratio if related to audio, video and text steganography. This research suggests the use of Advanced Encryption Standard and image steganography for efficient information interchange on the internet.

Visual secret sharing is a secret sharing scheme where the decryption requires no computation. It has found many applications in online transaction security, privacy protection, and bar code security, etc. Recently, researches have indicated that combining visual secret sharing with the widely used Quick Response code may provide additional security mechanism to online transaction. However, current methods are either pixel-based, which requires high computational complexity or module-based, which sacrifices error correction capability of the original Quick Response code. Designing module-based visual secret sharing for the Quick Response code without sacrificing error correction capability is a challenging problem. To solve this problem, this paper proposes a (3, 3)-threshold visual secret sharing for Quick Response code scheme that fully explores the extra freedom provided by color visual secret sharing and color stacking. The binary secret Quick Response code is encoded into color shares. By stacking all the three shares, a binary color Quick Response code can be reconstructed. After the inherent pre-processing steps in a standard Quick Response code decoder, the original binary secret Quick Response code can be completely reconstructed. Thus, the original error correction capability of the Quick Response code is fully preserved. Theoretical analysis shows that the visual secret sharing for Quick Response code is secure under the condition that the computational device available to the attacker is limited to a decoder for standard Quick Response code. Experimental results verify that the secret Quick Response code cannot be reconstructed from just one share or any two shares. However, it can be 100% reconstructed once the three shares are stacked. The proposed visual secret sharing for Quick Response code is module-based, and it does not sacrifice the error correction capability. Furthermore, No extra pre-processing steps other than the standard Quick Response code decoder are required.

The research discussed the development of a face recognition technology for the login system of an e-commerce website. The study's main focus was enhancing the security and efficiency of online transactions through the use of biometric identification systems. The researchers implemented a Face Recognition Login Website using a CNN, known for its ability to extract features and classify faces effectively. The research involved various stages, such as data collection through a web camera, data pre-processing, and the design of a CNN architecture with feature learning and classification layers. By deploying this CNN-based facial recognition technology on e-commerce websites, the researchers expect to add an extra layer of security, boost user trust, and offer a safer and more convenient online transaction experience.

The exponential growth of e-commerce has fundamentally transformed global retail landscapes while simultaneously creating unprecedented challenges in data privacy and security management. This paper examines the multifaceted nature of data protection challenges within e-commerce ecosystems, analyzing current threats, regulatory frameworks, and technological solutions. Through a comprehensive review of recent literature and industry reports, this study identifies key vulnerabilities in online transaction systems, evaluates the effectiveness of existing security measures, and assesses the impact of evolving privacy regulations on e-commerce operations. The analysis reveals that while technological advances have enhanced security capabilities, the increasing sophistication of cyber threats and the complexity of multi-jurisdictional compliance requirements continue to pose significant challenges. The findings suggest that effective data protection in e-commerce requires a holistic approach integrating advanced technological solutions, robust regulatory compliance, and comprehensive user education. This research contributes to the understanding of contemporary e-commerce security challenges and provides insights for developing more effective privacy protection strategies in digital commerce environments.

The paper explores how blockchain technology can transform data management, especially when it comes to handling privacy and security issues. Blockchain's immutability, transparency, and decentralization make it a potentially useful tool for addressing the expanding problems associated with data security and integrity. However, the slow adoption of blockchain technology is influenced by a complex interplay of developing privacy concerns, legislative uncertainty, and technological subtleties. The current study aims to identify key data privacy, protection, and security challenges associated with blockchain adoption in various domains, assess the adequacy of the current data privacy, protection, and security laws to address these challenges, and propose potential solutions and areas for further research to mitigate data privacy, protection, and security risks in blockchain applications. Additionally, the research has examined the adaptability and dependability of the two main kinds of blockchain—public and private—as well as the variations in their reach and visibility.

This community service activity aims to improve community digital literacy, especially in terms of transaction security and personal data protection in digital marketing activities. The activity was carried out in Kayumalue Ngapa Village, North Palu District, with an educational-participatory approach involving residents, MSME players, and digital media users. The implementation of the activity was carried out through several stages, namely initial observation, interactive lectures, educational video screenings, as well as discussion and question and answer sessions. The results of the activity showed an increase in public understanding and awareness of the importance of maintaining digital data security, as well as the emergence of a more cautious attitude in online transactions. Participants welcomed the simple, visual, and applicable method of delivering the material. This activity shows that participation-based education is effective in building collective awareness of cyber threats, and needs to be continued with further technical training to strengthen the community's practical ability to deal with digital risks.

Electronic commerce is becoming increasingly common at international level and is the object of analysis by various fields and scientific disciplines. Guaranteeing the security of transactions is of fundamental importance if electronic commerce is to expand correctly. In this regard, legal protection for electronic commerce transactions is an area that is gaining in interest for scientific literature. The Spanish Information Society Services and Electronic commerce Act describes various aspects that need to be further developed in this field. This document analyses the new contractual forms arising from the “Information Society” and the legal issues associated to the latter, as well as the Spanish legal system for providing legal protection to consumers in electronic contracts. Key words: Electronic commerce, legal protection, consumers.

Electronic markets have grown substantially, and they are considered an effective form of retail in recent years. Despite such growth, lack of physical transactions between different parties, as well as users' concerns about their privacy and security of transactions in electronic commerce (e-commerce) platforms have jeopardized users' trust. Thus, trust as a key issue for reducing consumers' perceived risk and the successful promotion of e-commerce has motivated many researchers to study it. This paper created a comprehensive and up-to-date framework that synthesized the previous studies in the literature conducted on trust in e-commerce environments. A systematic literature review method was selected to achieve this aim. The initial search in 17 top-ranked information systems journals and conferences resulted in 129 papers that met the inclusion criteria. Then these studies underwent an in-depth examination to determine how trust had been conceptualized in e-commerce environments. Further, the theoretical bases in relation to trust in e-commerce contexts used in the literature were investigated. The study concludes with implications for practice and a critical agenda for future research.

The online transaction has some security issues. Some attacks such as spoofing, phishing, and key-logger may threat the security of online transaction. The use of a token is one of solutions to increase its security. This paper presented the design and implementation of an android-based authentication system using One-time pad (OTP) algorithm. The use of a mobile phone gives advantage in avoiding a requirement of a specific token machine. The experiments show that the system can generate a unique token's key for each user in a specified period. The system also successfully pass through some attacks testing.

A new LabVIEW simulation design was applied to provide a comparison study among several types of the most common symmetric and asymmetric encryption algorithms. Also, the comparison with advanced encryption package program was made. The results showed that the new LabVIEW simulation design had advantages in several points, where the evaluated time required for the encryption and decryption processes will be lesser than it values using advanced encryption package program.In this work, the symmetric encryption algorithms were used: AES (Advanced Encryption Standard), DES (Data Encryption Standard), 3DES (Triple Data Encryption Standard) and RC2 (Rivest Cipher) algorithms, while the asymmetric encryption algorithm used was the RSA (Rivest-Shamir-Aldeman) algorithm. The comparison had been achieved using different sizes of text files with different key sizes. The final results proved that the LabVIEW simulation design is better than the Advanced Encryption Package because it increased the algorithm’s performance by 65% in terms of speed and throughput, and for the algorithms’ comparison, the final results showed the effectiveness of AES algorithm over the other algorithms in terms of speed and throughput for the encryption and decryption processes.

The advancement of artificial intelligence (AI) technology has created both opportunities and risks in data protection and safeguarding. Given that numerous organizations are now employing AI systems in various industries, the goal of using data to drive innovation has never been urgent. This paper will review the relationship between AI, data privacy, and security and discuss the current issues and possible recommendations. Furthermore, this study introduces new approaches, including federated learning and homomorphic encryption, which preserve data integrity while still using the data. Using concrete examples from various industries, the study reveals practices and tendencies that company leaders should follow and avoid to achieve a proper balance. This paper offers an ethical approach that integrates practical recommendations for policymakers, technologists, and businesses to build user trust and progress responsibly and technically. Since most AI applications are based on big data, users’ data protection and systems’ performance and expandability are extremely important. This paper explores the issue of data privacy and security in AI and discusses promising strategies to address the problem, and guidelines for responsible AI implementation. The main priorities include the exposition of the algorithms, data anonymization methods, legal requirements, and strengthening cybersecurity. This paper presents real-life examples, and industry benchmarks to support the framework that can help organizations manage technologies in a way that addresses ethical concerns. In the future, the analysis presented in the study can help industries understand trends that help develop AI strategies that meet high privacy and security standards.

The Internet of Things (IoT) is an emerging field consisting of Internet-based globally connected network architecture. A subset of IoT is the Internet of Healthcare Things (IoHT) that consists of smart healthcare devices having significant importance in monitoring, processing, storing, and transmitting sensitive information. It is experiencing novel challenges regarding data privacy protection. This article discusses different components of IoHT and categorizes various healthcare devices based on their functionality and deployment. This article highlights the possible points and reasons for data leakage, such as conflicts in laws, the use of sub-standard devices, lack of awareness, and the non-availability of dedicated local law enforcement agencies. This article draws attention to the escalating demand for a suitable regulatory framework and analyzes compliance problems of IoHT devices concerning healthcare data privacy and protection regulations. Furthermore, the article provides some recommendations to improve the security and privacy of IoHT implementation.