Vehicle-to-Grid (V2G) scheduling is mandatory to maximize grid stability and reduce the electricity cost of Electric vehicle (EV) owners, which also contributes to balancing the supply and demand side, peak load management, and frequency regulation. However, grid overloading, battery degradation, load fluctuations on peak demand, and power outages caused by improper scheduling that results in performance reduction in the power system. Hence, the research work implements the Unified Communication Optimization-based Online Charging Station Scheduling (UCO-CSS) method to overcome the aforementioned issues, which maintains the grid capacity within a certain range during peak and normal conditions. Moreover, the Advanced Encryption Standard (AES) algorithm is adopted to ensure reliable communication between the distribution grid and EVs, which prevents unauthorized access, malicious attacks, and data breaches. Furthermore, the UCO algorithm is employed to discover promising regions of the Charging Station to reduce the peak demand and grid congestion. Consequently, the UCO-CSS method manages the EV loads of 424.28kW, 569.6kW, 581.84kW, and 630.92kW by conducting analysis on commercial EV load, industrial EV load, public EV load, and residential EV load, respectively.

ABSTRACT Requirement engineering (RE) produces and manages well-defined requirements and is critical in cyber-physical system (CPS) development. Within RE, requirement traceability models fail due to collaboration, trust and privacy issues. The study proposes a decentralised application-based requirement traceability (DART) framework to support CPS development. The DART framework involves an Ethereum blockchain-based decentralised application, an advanced encryption standard (AES) cryptographic algorithm and graph-based representations. The proposed framework can enhance communication and security, positively impacting stakeholder collaboration, trust and decision-making. The privacy feature gives stakeholders confidence in sharing proprietary information, thus enabling continuous and consistent knowledge of the emergent CPS development.

FSM-Based Area Efficient AES-128 Encryption Processor with Pipelined Round Architecture for FPGA Security Applications

Engineering campuses in India host thousands of students navigating a complex web of daily logistical, safety, and social challenges. Despite widespread smartphone adoption, most campus services remain scattered across notice boards, WhatsApp groups, and manual complaint registers. This paper presents Smart Campus Hub (SCH), a full-stack, multi-role web and mobile platform that unifies five essential student welfare services: (i) a geo-tagged Lost & Found system with image-based item reporting, (ii) a one-tap SOS Panic Alert with real-time GPS broadcast via Firebase Cloud Messaging, (iii) a preference-weighted Roommate Finder powered by a cosine- similarity matching algorithm, (iv) a role-based digital Complaint Management system with 48- hour auto-escalation, and (v) a moderated peer-to-peer academic Marketplace for second-hand books, notes, and gadgets. Built on a RESTful microservice-influenced architecture with a React.js frontend, Python Flask backend, and a MySQL/Firebase hybrid data layer, the system achieves sub-300ms API response times and supports over 500 concurrent users. Security is enforced through JWT-based authentication, AES-256 encryption at rest, and TLS 1.3 in transit. Pilot evaluation on 1,200 student records demonstrates a 68% reduction in complaint resolution time, a 74% improvement in lost-item recovery rate, and 91% SOS alert delivery success. Future directions include NLP chatbot assistance, facial recognition attendance, AI-based image matching, and UPI payment integration.

The growing reliance upon cloud settings has rendered secure transmission of information essential. This study introduces the future-ready DNA-based cryptography (FRDNAC) paradigm, which combines DNA-based encryption with the feedback-assisted archimedes optimization algorithm to achieve efficient key generation and improved security. FRDNAC was assessed in comparison to contemporary optimization approaches such as the feedback artificial tree, the archimedes optimization algorithm, the blue monkey optimization, the coot optimization algorithm, the butterfly optimization algorithm, the shark smell optimization, the whale optimization algorithm, and the lightweight encryption system, as well as traditional encryption methods such as DNA encryption, Blowfish, Rivest-Shamir-Adleman (RSA), the advanced encryption system, and the elliptic curve cryptography. Experimental findings demonstrate FRDNAC's exceptional encryption and decryption efficacy, achieving an encryption duration of 0.11s (key length 4.0), surpassing rivals like FAT (0.29s) and LES (0.20s). Furthermore, FRDNAC markedly enhanced memory efficiency, rendering it suitable for resource-limited cloud settings. Security evaluations indicate its robustness against cryptographic threats, encompassing known-plaintext attack, chosen-plaintext attack, and brute force attack. Despite obstacles in real-time key generation and computational cost, FRDNAC presents itself as a highly safe and efficient cryptographic framework appropriate for cloud-based applications. Its strong security framework establishes it as a viable solution for sectors requiring high-performance encryption in evolving digital environments.

This study presents a novel hybrid cryptographic model designed to enhance privacy preservation and data integrity in IoT-enabled Wireless Sensor Networks (WSNs). Traditional algorithms such as RSA, AES, and Blowfish are evaluated and combined into a Hybrid Model to address the resource-constrained nature of IoT devices. The proposed model was tested on a dataset of sensor data, with performance metrics including encryption/decryption time, security strength, memory usage, data throughput, and communication overhead. Numerical findings demonstrate the Hybrid Model's superior performance, with encryption time reduced by 18% compared to Advanced Encryption Standard (AES), The hybrid model employs RSA-2048 (112-bit security strength) for key exchange and AES-256/Blowfish for data encryption (256-bit confidentiality protection). The memory usage was optimized, requiring only 25.16KB, making it suitable for low-power IoT devices. Additionally, the Hybrid Model achieved a data throughput of 24.89KB/s and reduced communication overhead to 1.32KB. These results highlight the efficiency and robustness of the Hybrid Model in securing IoT-enabled WSNs. This research contributes a scalable, resource-efficient solution for privacy and data integrity, offering a promising advancement for real-time IoT applications in sectors such as healthcare, industrial automation, and smart homes.

In today’s digitally connected world, ensuring the secure and covert transmission of sensitive information has become a critical challenge. Traditional encryption alone reveals the existence of secret communication, inviting targeted attacks. This paper presents Stegno Vault, a web-based secure data transmission system that integrates Least Significant Bit (LSB) steganography, Advanced Encryption Standard (AES) encryption, and Deep Genetic Algorithm (GA) optimization to hide secret messages within digital images, audio, and video files. The system is built on a Java Spring Boot backend, MySQL database, and a responsive HTML/CSS/JavaScript frontend, and is accessible through any standard web browser without local installation. The Genetic Algorithm selects optimal, high-entropy embedding positions in each media file, while AES encryption ensures hidden data remains unreadable even if detected. Role-based access control, OTP-based email verification, BCrypt password hashing, and a dedicated Admin governance panel provide enterprise-grade security. Experimental results confirm PSNR above 50 dB for image steganography and 100% data recovery accuracy across all three media types.

Audio data has strong correlations between adjacent samples, which is challenging for encryption methods. Current audio encryption methods mostly rely on complex transformations and algorithms to ensure their security, but overly complex algorithms will inevitably affect efficiency. We propose a novel audio encryption method by combining quaternary logic operations with MixColumns operations; this method provides higher security than existing audio encryption methods while having faster encryption and decryption speeds. The fast speed is due to the fact that encryption and decryption processes are mainly symbol replacements, which can be implemented very fast by quaternary logic operations. The high security comes from three aspects: (1) Quaternary logic operations can provide a huge space for encryption rules, because there are at most (4!)4 types of quaternary logic operations available for encrypting every 2 bits of data; (2) MixColumns operations can reduce the correlation between adjacent samples in audio data, enhancing the diffusion effect while improving key sensitivity; (3) We also introduce dual encryption to resist statistical attacks. To prove our method's security, we analyze key sensitivity and calculate security indicators including key space, number of sample change rate, unified average changing intensity, and peak signal-to-noise ratio, where we compare our method with other existing audio encryption methods. Results show that the security indicators of our method are superior to most of the compared methods. Our method is also faster than existing audio encryption algorithms based on chaos theory, AES encryption, and lightweight password Ascon. When implemented in C++, the encryption speed of our method can reach an average of about 0.000257s/KB. When implemented on FPGA, the path delay is measured as 2.750 ns reaching a maximum frequency of 363.6MHz, which is faster than AES, Ascon and other FPGA-based audio encryption methods. Meanwhile, our method consumes fewer FPGA resources than AES and Ascon.

Purpose: This research aims to design and implement a digital document security by integrating the Advanced Encryption Standard (AES) 256-bit algorithm with blockchain technology to protect documents from manipulation, forgery, and information leakage. Methods: The study involved implementation using Python. AES-256 was applied to encrypt digital documents, while the hash value of the ciphertext was stored on the blockchain to ensure integrity and authenticity. System performance was evaluated through avalanche effect testing, entropy analysis, and process time measurement. Result: The average efficiency is 49.989% for small documents, 49.988% for documents 50-200 KB and 49.998% for documents larger than 200 KB, using good bits. An average entropy value of 7.99 indicates a high performance. The average sending time is 1.62 ms, and the average blockchain sending time is 1061.862 ms making it possible to send in sending digital documents. Novelty: This study integrates AES-256 encryption with blockchain-based hash storage to simultaneously ensure confidentiality, integrity, and authenticity of digital documents with high efficiency.

Developing anisotropic force-induced hypso- and bathochromic bidirectional fluorescence switches based on pyrene-functionalized fluorene luminogens through manipulating steric hindrance.

This paper presents a hybrid secure data concealment system that enhances data security by integrating cryptography, steganography, and blockchain-based integrity verification. The system uses Advanced Encryption Standard (AES) and Rivest– Shamir–Adleman (RSA) algorithms to encrypt sensitive data before embedding it into digital images using Least Significant Bit (LSB) steganography. To ensure data integrity, a SHA-256 hash of the concealed data is generated and stored in a blockchaininspired append-only ledger. During verification, the extracted data is compared with the stored hash to detect tampering. Experimental results demonstrate that the proposed system ensures strong security, minimal image distortion, and reliable tamper detection. The system provides a secure and efficient solution for confidential data transmission.

The rapid evolution of 5G networks introduces unprecedented high-speed communication and massive connectivity, but it also intensifies security challenges. Ensuring confidentiality, integrity, and availability of data requires robust encryption mechanisms. This study evaluates the performance and overhead of Advanced Encryption Standard (AES), Rivest–Shamir–Adleman (RSA), and Elliptic Curve Cryptography (ECC) in 5G networks using simulation-based analysis. Metrics considered include latency (ms), throughput (%), encryption/decryption time per MB, and computational cost on UE-class hardware, providing quantitative comparison across typical 5G scenarios (high mobility eMBB, URLLC, and mMTCIoT devices). Key findings: AES achieves low latency and high throughput for bulk data; ECC provides secure, lightweight key exchange; RSA is suitable only for session key establishment due to higher computational overhead. Overall, hybrid AES+ECC provides the best tradeoff between security and performance in realistic 5G environments.

Abstract - The Advanced Encryption Standard (AES) is a widely used symmetric key encryption algorithm that secures digital data in modern communication systems. Conventional AES hardware implementations often consume high power, limiting their efficiency in resource-constrained environments. This paper presents a low-power AES hardware design implemented in Verilog HDL. The base design uses AES-128 with a 128-bit data block and 128-bit key, while the proposed design enhances security with a 256- bit key. Flip-flop based clock gating is applied to reduce dynamic power by minimizing unnecessary switching activity. Simulation results demonstrate that the proposed architecture effectively reduces power consumption while maintaining encryption performance, making it suitable for applications in IoT devices, embedded systems, and other low-power environments. Key Words: Advanced Encryption Standard (AES), Verilog HDL, Clock Gating, Low-Power Design, Cryptographic Hardware, Power Optimization, AES-128, AES-256.

The increasing use of digital documents in export-import activities, especially in government agencies such as the Directorate General of Customs and Excise, has the potential to pose a threat of leaks if not supported by an adequate security system. The design of this security system aims to design and develop a web-based digital export-import document security system by implementing the Advanced Encryption Standard (AES) 256-bit encryption algorithm. The system development was carried out using the Waterfall method by utilizing PHP, HTML, CSS, JavaScript, and MySQL database technology. This system implements encryption and decryption mechanisms on export-import documents in PDF and DOCX formats. Test results indicate that encrypted documents cannot be accessed without a valid decryption process, and data integrity is maintained referring to the AES-256 validation results. This system is able to increase the level of digital document security and minimize the risk of data leaks in a web-based system environment. This research requires the addition of a multi-layer authentication mechanism, the implementation of a more comprehensive encryption key management system, and the development of applications for mobile platforms. The rapid development of information technology has changed the way individuals, organizations, and government institutions manage and distribute information. One of the main impacts is the increasing use of digital import-export documents as the primary medium for storing and exchanging critical data. These documents generally contain sensitive information, requiring security mechanisms capable of ensuring data confidentiality, integrity, and authenticity during storage and distribution.

The widespread adoption of Internet of Things (IoT) systems has created a strong need for cryptographic solutions that are both secure and energy-efficient, especially due to limited power and hardware resources. This work presents a low-power design of an Advanced Encryption Standard (AES) cryptographic chip that utilizes clock gating techniques to reduce dynamic power consumption. By selectively disabling the clock signal to inactive sections of the circuit, unnecessary switching activity is minimized, leading to improved energy efficiency without affecting overall system performance. The proposed system features a hardware-based AES encryption module designed for efficient operation with reduced power usage while still ensuring high data throughput and robust security. The architecture is described using a hardware description language and implemented on an FPGA platform to analyse key performance parameters, including power consumption, area requirements, and timing characteristics. A comparative evaluation shows that the integration of clock gating significantly lowers power usage when compared to traditional AES implementations lacking such optimization. The findings demonstrate that the proposed design is well-suited for IoT environments where energy efficiency is critical. It achieves an effective balance between security, performance, and power consumption, making it a practical solution for modern embedded and resource-constrained applications.

Unprotected PHP source code is vulnerable to reverse engineering, piracy, and illegal modifications. This research aims to design and develop a multi-layer PHP source code protection model that combines obfuscation techniques, multi-layer encoding, AES-256 encryption, and hashing mechanisms with anti-tamper capabilities to maintain code confidentiality and integrity. The system is also equipped with auto-restore features and panic notification via Telegram Bot that automatically restores original files and sends security warnings when illegal changes are detected. The methodology used is Research and Development (R&D), with stages including literature review, system design, prototype development, security experiments, and performance benchmarking. The expected results show that the multi-layer model can hinder reverse engineering, accurately detect file changes, and provide rapid responses via auto-restore and Telegram notifications, significantly improving PHP source code security compared to conventional encoders. The security experiments demonstrated superior protection against deobfuscation attacks, with benchmark results showing acceptable performance overhead (an average execution-time increase of 15-20ms, a CPU load increase of 8-12%, and a memory usage increase of 5-8 MB) compared to commercial encoders.

The proliferation of digital assets has catalyzed a profound decoupling between intangible property and traditional inheritance jurisprudence. Under the existing legal framework in Taiwan, practitioners must rely on the testamentary forms prescribed in Article 1189 of the Civil Code, which are fundamentally ill equipped to handle cryptographic assets. Specifically, Notarized Wills (Article 1191) necessitate full disclosure to a notary, creating a “Privacy–Security Paradox” where revealing private keys exposes assets to misappropriation. Conversely, while Sealed Wills (Article 1192) offer confidentiality, they are plagued by risks of physical degradation and technical non-executability. This study proposes zkWill, an EVM-compatible decentralized testamentary framework designed to bridge these structural gaps. By leveraging Zero-Knowledge Proofs (ZKPs), zkWill achieves a state of “blind compliance,” verifying that a sealed will meets the statutory requirements of the Civil Code without disclosing its underlying content. The system integrates the Permit2 protocol for secure asset migration and combines AES-256 encryption with IPFS to immunize testaments against centralized storage failures. Unlike conventional services that demand custodial trust, zkWill employs decentralized oracles to trigger automated execution, ensuring legacy distribution without compromising wallet private keys. Empirical data from the Arbitrum Sepolia testnet confirms that the framework maintains constant verification efficiency and a judicially resilient audit trail, providing a paradigm that harmonizes legal pragmatism with cryptographic security for digital inheritance.

The conventional asset-backed lending business is often reliant on outdated data management platforms and opaque storage platforms, presenting the industry with very daunting problems, including security breaches, the lack of verifiable ownership histories, and obscure asset disposal practices. To address this, this study came up with a safe web-based system that digitalizes the activities of loans by applying the blockchain technology. The platform is integrated with a modern online architecture, which uses a Virtual Vault Guard to implement the dual-key access protocol, as well as AES encryption and SHA-256 hashing that would guarantee that data about the assets are safely secured on-chain. Smart contracts were automated to create digital receipts that were immutable and to conduct digital bidding of defaulted loans in an atomic swap. The empirical research indicates that the ecosystem improves the general performance of management in terms of availing very structured, secure digital data storage and reliable auditing facilities. The paper concludes that the implementation of a blockchain-based system, which is associated with immutable receipts and transparent bidding, is necessary to ensure complete security, fairness, and efficiency. Based on this, the study suggests that the lending institutions should incorporate this secure ledger of assets and automated system of bidding to enhance customer confidence by providing verifiable digital receipts as well as to provide fair and transparent recovery of capital.

In the digital era, communication through messaging applications has become an essential part of daily life, especially among students in a college environment. However, most existing chat applications lack sufficient security measures to protect sensitive user data and ensure controlled communication. This paper presents the design and implementation of a College Campus Secure Chat Application, which focuses on providing secure, reliable, and moderated communication within a campus. The proposed system uses AES (Advanced Encryption Standard) to encrypt messages before transmission and decrypt them upon reception, ensuring confidentiality. In addition to encryption, the system incorporates device-level security features such as root detection, debugger detection, and emulator detection to prevent unauthorized access. Furthermore, the application includes abuse detection and temporary user blocking mechanisms to maintain a disciplined communication environment. The integration of Firebase enables real-time messaging and efficient data handling. The results demonstrate that the application successfully ensures secure communication while maintaining usability. The combination of encryption, device validation, and user moderation provides a comprehensive solution for secure campus communication. Keywords: AES Encryption, Secure Chat Application, Firebase, Android Security, Abuse Detection, Data Protection

Data security and encryption is one of the most useful at highly essential aspects of enabling effective security of the data against attacks and intrusions. This is an effective and useful technique that has been evolved significantly over the past few years. For the purpose of encryption the AES was prominently used before. The data encryption standard is highly effective but was prone to encryption failure against brute force attacks that have been highly effective against this encryption standard. Therefore the advanced encryption standard has been used since then to improve the performance of encryption significantly. The advanced encryption standard has been useful and realization of effective security but has been optimized specifically for achieving high throughput and high bandwidth for a variety of implementations. In this methodology we propose an enhancement to the AES encryption approach through the improvement of key generation process through the utilization of the genetic algorithm. The effective and useful implementation of genetic algorithm has been significantly useful for improving the performance of the AES encryption con siderably. Keywords: Data Security, Advanced Encryption Standard (AES), Genetic Algorithm, Key Generation, Cryptography