Search
11 articles for “Homomorphic encryption”
-
Data Privacy in AI: Securing the Sensitive Information Through Homomorphic Encryption
Abstract: Artificial intelligence (AI) technology increasingly relies on sensitive user data, particularly finance and healthcare. While legacy encryption technologies safeguard data in transit and at rest, they are of no use when data must be decrypted to be processed. This is a bleak privacy threat, particularly in AI applications that call for constant processing of data. The objective of this study is to apply homomorphic encryption, a feature in which operations …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 2, 2025 · pp. 25–30 Read article
-
A Practical Approach for Privacy Preserving in Cloud Computing Using Fully Homomorphic Encryption Scheme BFV and CKKS
Abstract: Cloud computing is a new type of computing architecture whereby data may be accessed over the Internet along with other services linked to its scalable data centers in the cloud. The risk associated with computing is increased since it provides essential services that are typically provided to any third party, making it more difficult to enable data security, privacy, confidentiality, integrity, and authentication. To reduce security risks, most users choose …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 1, 2025 · pp. 1–8 Read article
-
A Secure Storage Model with Authentication and Optimal Key Generation Based Encryption
Abstract: In digital forensics, ensuring the secure storage of digital evidence is crucial. This paper introduces a new method that uses advanced encryption and key generation techniques to protect digital evidence throughout an investigation. Cloud forensics, a modern approach to digital forensics, aims to safeguard evidence from online hacking. However, storing all evidence in one central location can reduce its reliability. To address this, we propose a digital forensics architecture for …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 7–13 Read article
-
Advanced Private Cloud Security and Privacy Preservation Through the Integration of Machine Learning and Cryptography
Abstract: In modern technological landscapes, private cloud security is of paramount concern due to the ever-increasing volume and complexity of cyber threats. This research work explores the integration of machine learning and cryptography to enhance security within private cloud environments. This study aims to mitigate vulnerabilities that may compromise data integrity, confidentiality, and availability in private cloud infrastructures by using machine learning algorithms and strong cryptography. By detecting anomalous cloud patterns …
Published in International Journal of Advanced Control and System Engineering · Vol. 2, Issue 1, 2024 · pp. 1–10 Read article
-
A Framework for Privacy-preserving AI Models in Cloud Computing: Challenges and Solutions
Abstract: The growing adoption of cloud computing for deploying artificial intelligence (AI) models has led to significant advancements in sectors such as healthcare, finance, and e-commerce. However, the integration of AI with cloud computing raises critical privacy concerns, particularly when handling sensitive data. This paper presents a comprehensive framework for implementing privacy-preserving AI models in cloud environments, addressing the unique challenges, and proposing effective solutions. The suggested framework employs advanced privacy-preserving …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 1–12 Read article
-
Advancements in Privacy-Preserving Techniques for Cloud Database Management Systems: A Review Analysis
Abstract: Cloud computing is a technology that provides a lot of configurable resources, enabling decentralized data execution and space. Cloud technologies have transformed the ideas of internal data storage and access to provide businesses with flexibility and efficiency. Thanks to cloud services like DBaaS, users may make use of advanced database features without having to worry about the burden of traditional databases. With more organizations moving to the usage of Cloud …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 1, 2026 · pp. 11–22 Read article
-
E-Voting Application Using Blockchain
Abstract: Electronic voting (e-voting) is increasingly recognized as a method for improving the electoral process by enhancing security, accessibility, and efficiency. However, traditional e-voting systems present challenges, including security vulnerabilities, lack of transparency, and privacy concerns. This study presents an e-voting system powered by blockchain technology, designed to enhance decentralization, security, and protection against fraud. By leveraging blockchain’s features such as immutability, transparency, and cryptographic security, this model mitigates risks related …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 2, 2025 · pp. 12–21 Read article
-
Network Security and Risk Technologies
Abstract: This research work delves into the dynamic domain of network security risk, providing a comprehensive analysis of corruption of data. The study explores strategic models aimed at strengthening network defenses in response to the continually changing threat environment. In the past, network security has relied on various technologies to mitigate risks, which include Firewalls, Virtual Private Networks (VPNs) and Encryption Protocols. The research scrutinizes the role of technologies such as …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 26–34 Read article
-
Differential Privacy-Aware Data Sanitization for Multi-Level Security
Abstract: Multi-level security (MLS) models are fundamental for enforcing mandatory access control in high-security environments such as government, military, healthcare, and finance. However, traditional MLS frameworks, including the Bell-LaPadula and Biba models, often create rigid data silos, preventing efficient data utilization. Differential privacy (DP) presents a novel solution by enabling controlled information leakage while preserving confidentiality. By injecting statistical noise into query results, DP allows lower-clearance users to access sanitized versions …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 1, 2025 · pp. 42–52 Read article
-
Analysis and Identification of Malicious Mobile Applications Using Machines Learning
Abstract: Over the past few years, malware attacks on the Android platform have surged, posing significant risks to users' financial security, personal information, and device integrity. In the first half of 2019 alone, approximately 25 million smartphones were infected, highlighting the severity of these threats. The model ranks manifest features based on their frequency in normal and malicious apps, identifying key components that distinguish benign from malicious applications. To improve detection …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 17–24 Read article
-
Study of Algebraic Structures in Discrete Mathematics and Its Applications
Abstract: Algebraic structures such as groups, rings, fields, semi groups, and lattices form the foundational framework of discrete mathematics. These structures are defined by specific sets and operations that follow algebraic laws, enabling a systematic approach to problem-solving in various domains. This paper explores the theoretical principles of these algebraic systems and highlights their vital role in computer science, cryptography, automata theory, coding theory, and software engineering. By examining their properties …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 1, 2025 · pp. 35–40 Read article