Secure Mode Research Articles

An Attribute-Based End-to-End Policy-Controlled Signcryption Scheme for Secure Group Chat Communication

Secure instant communication is an important topic of information security. A group chat is a highly convenient mode of instant communication. Increasingly, companies are adopting group chats as a daily office communication tool. However, a large volume of messages in group chat communication can lead to message overload, causing group members to miss important information. Additionally, the communication operator’s server may engage in the unreliable behavior of stealing information from the group chat. To address these issues, this paper proposes an attribute-based end-to-end policy-controlled signcryption scheme, aimed at establishing a secure and user-friendly group chat communication mode. By using the linear secret sharing scheme (LSSS) with strong expressive power to construct the access structure in the signcryption technology, the sender can precisely control the recipients of the group chat information to avoid message overload. To minimize computational cost, a signcryption step with constant computational overhead is designed. Additionally, a message-sending mechanism combining “signcryption + encryption” is employed to prevent the operator server from maliciously stealing group chat information. Rigorous analysis shows that PCE-EtoE can resist adaptive chosen-ciphertext attacks under the standard model. Simulation results demonstrate that our theoretical derivation is correct, and that the PCE-EtoE scheme outperforms existing schemes in terms of computational cost, making it suitable for group chat communication.

Single-Query Quantum Hidden Shift Attacks

Quantum attacks using superposition queries are known to break many classically secure modes of operation. While these attacks do not necessarily threaten the security of the modes themselves, since they rely on a strong adversary model, they help us to draw limits on their provable security.Typically these attacks use the structure of the mode (stream cipher, MAC or authenticated encryption scheme) to embed a period-finding problem, which can be solved with a dedicated quantum algorithm. The hidden period can be recovered with a few superposition queries (e.g., O(n) for Simon’s algorithm), leading to state or key-recovery attacks. However, this strategy breaks down if the period changes at each query, e.g., if it depends on a nonce.In this paper, we focus on this case and give dedicated state-recovery attacks on the authenticated encryption schemes Rocca, Rocca-S, Tiaoxin-346 and AEGIS- 128L. These attacks rely on a procedure to find a Boolean hidden shift with a single superposition query, which overcomes the change of nonce at each query. This approach has the drawback of a lower success probability, meaning multiple independent (and parallelizable) runs are needed.We stress that these attacks do not break any security claim of the authors, and do not threaten the schemes if the adversary only makes classical queries.

Secure consensus for positive multi‐agent systems with bumpless transfer control under Denial‐of‐Service attacks

AbstractThis article investigates the secure consensus control problem of positive multi‐agent systems under multiple‐mode Denial‐of‐Service (DoS) attacks. A bumpless transfer (BT) control based secure mode strategy is proposed to improve the switching transient performance due to the system being actively switched to secure mode when attack is detected. Considering possible time delays for agents dealing with the issues of DoS attacks, an asynchronous switching model is established between system models and communication topology. With the stability theory of positive systems, sufficient and necessary conditions are established to guarantee the positivity of multi‐agent systems under the secure mode strategy. Because the switching law caused by external attacks is unknown in advance, the BT control is specifically implemented through the controller gain interpolation technique. By multiple Lyapunov functions (MLFs) approach, secure consensus is achieved with a trade‐off among controller performance, attack parameters, and switching delays. Numerical examples are presented to demonstrate the effectiveness of the obtained results.

Research on Optimization of Communication Network Security and Intelligent Supervision Model in Urban Community Aging Adaptation Renovation

In the process of increasing the number of elderly people, their care and attention have received greater attention, which has made traditional community environments face insufficient data encryption performance and data mining services in the communication network security of aging communities. This has made communication security optimization and intelligent monitoring models in urban community aging adaptation and transformation a focus of research in the field of data communication security. This study delves into the improvement and enhancement of intelligent monitoring models for communication network security in urban communities. Its goal is to improve the security and intelligent monitoring mode of data communication networks during the transformation process through technological innovation and progress in management practices, and further improve the security performance of data communication. This research has solved the communication network security problems existing in intelligent devices and Internet services in the community aging transformation. Through the analysis of improvement strategies, this article compares the basic performance indicators of data encryption, firewall performance, data analysis and mining, and intelligent recommendation in communication network security and intelligent recommendation between different models. The optimization of communication network security in urban community aging adaptation can ensure the data security of terminal devices and further improve and enhance intelligent recommendation services for aging, providing more references and suggestions for communication network security and intelligent monitoring.

Efficient and robust control of a standalone PV-storage system: An integrated single sensor-based nonlinear controller with TSCC-battery management

The aim of this research undertaking is to investigate an integrated approach that extends the battery life of a single-stage off-grid photovoltaic system while simultaneously increasing the availability of solar photovoltaic power. This paper takes a synergistic approach to addressing these issues, in contrast to the numerous prior papers that have investigated them individually. In regard to the initial issue, this article proposes a hybrid MPPT solution which combines a backstepping controller with a distinct single-sensor MPPT approach. The aforementioned integrated system guarantees the exact attainment of the maximum power point (MPP) of the photovoltaic solar array, regardless of weather fluctuations. With regard to the second issue at hand, the effective management of charge for lead-acid batteries is accomplished by employing a three-stage charging controller (TSCC). The simulation results generated in MATLAB/Simulink indicate that MPPT tracking and battery charge control exhibit markedly improved performance across a range of weather conditions when the climatic conditions of El Jadida city, Morocco are taken into account. The hybrid method, as proposed, indisputable surpasses alternative MPPT approaches such as Inc-PI, FLC, PSO, RegP, and IMP-PO, with respect to convergence time (<3 milliseconds), variation (<0.19 watts), and tracking efficiency (over 99.86 %). Furthermore, the battery station is outfitted with secure and appropriate charging modes. In conclusion, the experimental validation of the proposed system against an actual experimental system in the laboratory verifies its hardware and practical viability.

МЕТОД ДВОКАСКАДНОЇ ІМПЛАНТАЦІЇ ПРИХОВАНОЇ ІНФОРМАЦІЇ НА ОСНОВІ СТЕГАНОКОМПРЕСІЙНИХ ПЕРЕТВОРЕНЬ

In the article, the need for further development of the state is directly related to: solving issues of increasing defense capability and information security; development of information and intelligent systems. The necessity of ensuring the required level of completeness of information, compliance with the requirements of its relevance, achievement and maintenance of the appropriate level of integrity, accessibility and confidentiality is substantiated. The article emphasizes that for this purpose, complex systems of coding and information protection are being built. It is shown that recently, in order to further increase the level of security of information resources, methods of hidden embedding of information have been used. In this field of scientific and applied research, the direction of timely delivery of integral video information in a secure mode is outlined. For protection, the following can be used: meta-messages, which are formed on the basis of intelligent analysis of video frames; separate video segments of aerial photographs containing the most important information for decision-making. This article examines a class of methods of steganographic transformations, which are associated with embedding messages in digital containers, which are formed by a stream of video segments (VS). However, existing steganographic systems are based mainly on the use of the amount of psychovisual (PSV) redundancy available for reduction. Therefore, an increase in steganographic capacity leads to a loss of integrity and efficiency of delivery of video-container information. Steganocompression coding in the stegano-polyadic basis was created on the basis of taking into account the amount of redundancy permissible for reduction. In this case, in the process of compression of the components of the VS, the direct embedding of hidden information is organized. Concealment of information is carried out by technological stages, depending on the compression transformation of the transitional syntax of the quilted sequence. The key stage is the technology of two-stage implementation of the elements of the concealed message added to the stegano sequences to the syntax of the steganocompression representation of the BC components.

Home Automation Using Image Processing

Today, many of the automation systems deployed are mostly controlled by humans. This control by humans restricts the automation of home appliances to an extent. Also, most of the deployed home automation systems use the Internet of Things technology to control the appliances. In this we propose a system developed using action recognition to fully automate the home appliances. We recognize the three actions of a person (sitting, standing and lying) along with the recognition of an empty room. With this system, we remove the human intervention in home automation systems for controlling the home appliances and at the same time we ensure the data privacy and reduce the energy consumption by efficiently and optimally using home appliances and also it has a security mode. In the security mode if any human is detected it captures the image of the person detected and shares the picture to responsible person,the picture shared will be refreshes with every one minute and also it uploads the captured image in local IP address provided to it. through the local IP no. of persons can see the image captured.

The Study on The Role of E-Wallets Feature in Influencing Universities Students' Purchasing Decisions

This research investigates the influential role of e-wallet features on the purchasing decisions of students at University Malaysia Kelantan, within the context of the rapidly evolving digital payment landscape. With e-wallets gaining popularity as a convenient and secure mode of financial transactions, understanding their impact on student consumers becomes imperative. Through a mixed-methods approach, data was collected from undergraduate students through surveys and interviews, analyzing various e-wallet attributes such as ease of use, security, rewards, and merchant variety. Preliminary findings reveal that e-wallets play a significant role in shaping students' purchasing behavior, primarily due to their convenience and availability of attractive rewards. The study also uncovers the influence of peer interactions and perceptions of e-wallets on students' adoption and usage patterns. Keywords: E-wallets, digital payments, purchasing decisions, consumer behavior, financial technology, convenience, rewards, student consumers.

An attribute-encryption-based cross-chain model in urban internet of vehicles

With the maturity of Internet of Vehicles (IoV) technology and blockchain technology, numerous application scenarios have emerged, including urban Internet of Vehicles, Highway Internet of Vehicles, and Specific Area Internet of Vehicles. However, the urban Internet of Vehicles systems face data security and operational mode discretization challenges. To address these issues, we propose a data security cross-chain model for the urban Internet of Vehicles. Our model utilizes hash time lock contracts to exchange data between vehicles of the same brand and model but located in different urban areas. It also uses trusted relay chains to facilitate data exchange between vehicles of the same brands but varying models within the same urban area, thus solving the problem of difficult inter-system data exchange in the urban Internet of Vehicles. In the urban Internet of Vehicles, the transmitted data encompasses business and general data, which may have varying sensitivities. To ensure data confidentiality, we propose the HR-CP-ABE algorithm, which extends CP-ABE functionalities by incorporating hierarchical decryption and revocable vehicle attributes. And the fine-grained access control by setting different access tree structures and file access validity periods. This guarantees the confidentiality and security of urban data. Finally, experimental results demonstrate that the proposed model effectively satisfies the standards for cross-chain transactions as outlined in the Evaluation Requirements for Blockchain Application Security Technology(DB43/T 1842–2020) and Evaluation Requirements for Blockchain Network Security Technology(DB43/T 1840–2020). Additionally, our model demonstrates enhanced resilience against man-in-the-middle and replay attacks.

An investigation of novel features for predicting student happiness in hybrid learning platforms – An exploration using experiments on trace data

The current study investigated the novel factors influencing informatics students' happiness and satisfaction using statistical and machine learning algorithms. A statistical t–test proved that the students in the younger age group (<=20) who were enrolled in bachelor's programs (B.Sc.) were more confident than those in the older age group (>=21) who had enrolled in master's programs (M.Sc.) that hybrid learning was a secure mode of education during the pandemic (p < 0.05). The happiness of students has had a significant influence on the challenges and prospects for online education that involve safety (p < 0.05). It was determined that factors such as time and cost utilization with management, university initiatives and assistance, and challenging group tasks substantially affected student satisfaction (p < 0.05). The paper's findings recommended some vital issues such as Internet disconnection during the lesson, Less support during technical glitches or errors, Less competitive environment, Possibility of cheating in exams due to lack of surveillance, Less focused and interactive during hybrid learning, important assistance and support, and safety modes for higher educational institutions during a pandemic. Using a maximum accuracy of 88%, Random Forest (RF) outperformed Logistic Regression (LR), Xtream Gradient Boosting (XGBoost), and other classifiers to predict student happiness based on hybrid learning features. The RF algorithm's superior performance was validated and confirmed by all performance metrics, such as F1-score, precision, recall, and specificity.

Risk evaluation of mega infrastructure construction supply chain in engineering-procurement-construction projects: an integrated fuzzy AHP and fuzzy DEMATEL approach

PurposeThe paper covers mega infrastructure construction supply chain (MICSC) in Engineering-Procurement-Construction (EPC) projects, where the frequent occurrence of risk incidents has greatly affected human life. The research aims to establish a risk evaluation index system for MICSC in EPC projects, exploring what risk factors lead to risk incidents and measure the importance and causality of all these risk factors.Design/methodology/approachThe research applies a combination of quantitative and qualitative analysis methodology to process data sequentially. In the first place, risk factors for MICSC in EPC projects are extracted and identified from literature survey and expert interviews. In the second place, an integration model fuzzy Analytic Hierarchy Process (f-AHP) and fuzzy Decision-making Trial and Evaluation Laboratory (f-DEMATEL) is constructed to comprehensively analyze all these risk factors.Findings12 primary risk factors and 36 secondary risk factors comprise the risk evaluation index system for MICSC in EPC projects from 178 literature and 5 professionals. The results indicate that Political Situation (F1), Social Security (F2) and Management Mode (F8) are critical risk factors, where F1 and F2 are cause factors and F8 is an effect factor.Originality/valueThere are three main contributions of this paper. First and foremost, from the perspective of the research content, no other study has been able to assess risk factors for MICSC in EPC projects, while embedding nine phases of the whole project life cycle and six subjects of stakeholders into a risk evaluation index system. Additionally, from the perspective of research method, a combined model incorporating f-AHP and f-DEMATEL is constructed to avoid the one-sidedness of a single model. Last but not least, from the perspective of practical significance, focusing on the critical risk factors, a series of effective measures are formulated to make appropriate management decisions for nodal enterprises of MICSC, which can improve their risk management capabilities.

Dynamic event‐based consensus of multi‐agent systems with secure mode resilient to DoS attack

AbstractIn this article, the resilient leaderless consensus problem for a multi‐agent system (MAS) under denial‐of‐service(DoS) attack is investigated. The DoS attack is carried out with multiple strategies. The sufficient condition for MASs achieving consensus under multi‐mode DoS attack is developed. In order to actively alleviate the influence caused by the DoS attack, the MAS switches between normal and secure modes. Once a DoS attack occurs, the agents will switch into the secure mode with a lower open‐loop divergence rate. A dynamic event‐based consensus protocol is proposed, driving the MAS achieve consensus while saving communication resources effectively. Moreover, rigorous proof analysis demonstrates the Zeno‐free property of the developed dynamic event‐triggered mechanism. Finally, a numerical simulation is provided to illustrate the effectiveness of the proposed theoretical results.

Psychological screening, providing social security or strengthening training? How can government and labor unions protect the mental health of young employees.

As the mental health problems of young employees become more and more prominent, the government and labor unions need to take measures to protect the mental health of young employees. Considering that the main mental health safeguard measures are divided into psychological screening, providing social security and strengthening training, this article constructs a differential game model under these three modes. The balanced efforts and social benefits of the government and labor unions under the three modes are obtained, and the applicable conditions of various mental health protection modes are compared. The results show that if the government pays a lower cost, the government gets the highest economic benefit under the training mode, followed by the security mode, and the government gets the lowest economic benefit under the psychological screening mode. If the reputation of the labor unions improved by its efforts is low, the equilibrium benefits of the labor unions under psychological screening and providing security are the same, and greater than the equilibrium benefits under the intensive training mode. If the labor unions have a higher reputation enhanced by its efforts, the balance return of the labor unions under the guarantee mode is the highest, followed by the balance return under the intensive training mode, and the balance return of the labor unions under the psychological screening mode is the lowest.

A Comprehensive Analysis: Evaluating Security Characteristics of Xbee Devices against Zigbee Protocol.

In recent times, the security of sensor networks, especially in the field of IoT, has become a priority. This article focuses on the security features of the Zigbee protocol in Xbee devices developed by Digi International, specifically in the Xbee 3 (XB3-24) devices. Using the TI LaunchXL-CC26X2R1 kit, we intercepted and analyzed packets in real-time using the Wireshark application. The study encompasses various stages of network formation, packet transmission and analysis of security key usage, considering scenarios as follows: without security, distributed security mode and centralized security mode. Our findings highlight the differences in security features of Xbee devices compared to the Zigbee protocol, validating and invalidating methods of establishing security keys, vulnerabilities, strengths, and recommended security measures. We also discovered that security features of the Xbee 3 devices are built around a global link key preconfigured therefore constituting a vulnerability, making those devices suitable for man-in-the-middle and reply attacks. This work not only elucidates the complexities of Zigbee security in Xbee devices but also provides direction for future research for authentication methods using asymmetric encryption algorithms such as digital signature based on RSA and ECDSA.

On the control of microgrids against cyber-attacks: A review of methods and applications

Nowadays, the use of renewable generations, energy storage systems (ESSs) and microgrids (MGs) has been developed due to better controllability of distributed energy resources (DERs) as well as their cost-effective and emission-aware operation. The development of MGs as well as the use of hierarchical control has led to data transmission in the communication platform. As a result, the expansion of communication infrastructure has made MGs as cyber-physical systems (CPSs) vulnerable to cyber-attacks (CAs). Accordingly, prevention, detection and isolation of CAs during proper control of MGs is essential. In this paper, a comprehensive review on the control strategies of microgrids against CAs and its defense mechanisms has been done. The general structure of the paper is as follows: firstly, MGs operational conditions, i.e., the secure or insecure mode of the physical and cyber layers are investigated and the appropriate control to return to a safer mode are presented. Then, the common MGs communication system is described which is generally used for multi-agent systems (MASs). Also, classification of CAs in MGs has been reviewed. Afterwards, a comprehensive survey of available researches in the field of prevention, detection and isolation of CA and MG control against CA are summarized. Finally, future trends in this context are clarified.

Blockchain Technology in Construction Supply Chain Management: Enhance Transaction Speed, Cost Effectiveness and Security

The traditional construction sector encountered obstacles that prevented it from developing, including knowledge asymmetry, complicated intermediary relationships, and high transaction costs. Blockchain technology offered a more effective, secure, and convenient mode of transaction and management to the construction industry because it was a decentralized, safe, and reliable information transmission and management tool. Blockchain technology could be applied to the construction industry's supply chain to achieve traceability and supervision, enhancing the transparency and dependability of transactions. At the same time, blockchain technology could be applied to the management of the construction supply chain to achieve rapid information sharing and verification, lowering transaction costs, and increasing transaction efficiency. However, the previous study on the use of blockchain technology in the building sector was still in its infancy and required more investigation and study. This study aimed to investigate how blockchain technology could be used in supply chain management for the construction sector to address present issues. The study's goals were to examine how blockchain technology could speed up transactions and improve supply chain management for the construction industry, as well as to examine how it could lower transaction costs and increase data sharing and information transparency. This study used a semi-structured interviewing technique for the purpose of gathering and analysing data. The researcher learned more about professionals and industry experts' thoughts and experiences with blockchain technology in construction supply chain management through in-person or remote interviews with them. The advancement of the construction industry's digital transformation and information upgrading reflected the significance of this study. This study would help the supply chain management in the construction sector in enhancing the effectiveness of supply chain transactions in the construction industry and reducing the transaction cycle; lowering the price of supply chain transactions in the construction industry and boosting the industry's competitiveness; strengthening the security and reliability of supply chain transactions in the construction industry and reducing data compromise and transaction risks.

Biomechanical Comparison of 1.2-mm Suture Tape, 2.0-mm Suture Tape, and 0.5-mm Suture Using Various Arthroscopic Knot Techniques.

The biomechanical properties of the 1.2-mm suture tape have outperformed conventional sutures in previous studies. To compare the loop and knot security of 2 tape-type and 1 cord-type sutures using different arthroscopic knot techniques. Controlled laboratory study. The biomechanical characteristics of the 1.2-mm tape, 2.0-mm tape, and 0.5-mm No. 2 suture were compared using 4 different knot types: 2 sliding knots (Samsung Medical Center [SMC] and Tennessee) and 2 nonsliding knots (2-throw surgeon's and 2-throw square) with 2 and 3 additional reverse half-hitches on alternating posts (RHAPs) in a closed-loop system on a materials testing device. Each configuration was tested for loop security (maximal load applied between 0 and 3 mm of displacement), knot security (ultimate failure load), and failure mode with cyclical loading (30 N load for 20 cycles at 1 cycle per sec until failure). Loop and knot security among the configurations were compared using an analysis of variance. With 2 RHAPs, the 2.0-mm tape showed significantly greater loop security than the 1.2-mm tape and suture (P = .001). With 3 RHAPs, the loop security of the suture was significantly superior compared with the 1.2-mm tape (P = .010). Regarding knot security, with 2 RHAPs, the 2.0-mm tape was significantly better than the 1.2-mm tape and suture (P < .001), while with 3 RHAPs, the suture was significantly superior to the 1.2-mm tape (P = .012). Using a square knot with 2 RHAPs, the 2.0-mm tape had significantly greater loop security (P = .001) and better knot security (P = .001) to the 1.2-mm tape and suture. Using the Tennessee knot with 2 RHAPs, the 1.2-mm tape had less loop security (P = .011) and knot security (P = .005) than the suture. Using the SMC knot with 3 RHAPs, the 2.0-mm tape and suture were significantly superior in loop security (P = .001) and knot security (P < .001) to the 1.2-mm tape. There was no significant difference in the failure mode between tapes and sutures with 2 and 3 RHAPs. With 2 RHAPs, the 2.0-mm tape demonstrated greater resistance to suture loop displacement and better knot security compared with the 1.2-mm tape and suture. However, with 3 RHAPs, the 1.2-mm tape manifested weaker loop and knot security compared with the suture.

Devising an approach to safety management of vessel control through the identification of navigator’s state

The object of this study is the processes of automated management of maritime safety by analyzing the manifestations of the human factor of sea navigators. The task solved is justified by the need for formal and logical analysis and intelligent identification of mental motivational states (MMS) of marine navigators whose actions can cause dangerous situations during the control of the ship’s movement. High accident rates due to the fault of the navigators, in the absence of automated means of monitoring their condition, cause a contradiction between the existing means of safety control in controlling the movement of the vessel and the modern requirements of navigation, which needs to be resolved. A safety management approach was devised that takes into account the specificity of navigational tasks and the p-adic classification of dangerous MMS for navigators. This has made it possible to create three security modes that are activated depending on the detected state of the navigator’s MMS. Features of the results are the combination of analysis by means of p-adic systems and intelligent methods of data processing. As a result, sufficient identification accuracy was obtained for more than 75 % of MMS through neural network training. Experimental data collected during the navigation watch, as well as on the Navi Trainer 5000 navigation simulator (Wärtsilä Corporation, Finland), became the basis for simulation by means of neural networks. In turn, the training of neural networks made it possible to obtain sufficient identification accuracy by performing up to 3000 iterations. Overall, the learning rate of the neural network was 0.98, which indicates a high level of identification. From a practical point of view, the results could be used for the automated management of shipping safety, as well as for evaluating the level of adaptation of the navigator to dynamically changing conditions. The proposed approach provides opportunities for the application of modern intelligent technologies in the field of maritime transport safety, namely artificial neural network tools that determine notification modes or activation of automatic ship traffic control modules. The specified contradiction requires the design of specialized systems for automated safety management of ship traffic control based on the identified states of navigators

Formal modeling and analysis of security schemes of RPL protocol using colored Petri nets.

In the Internet of things (IoT), data packets are accumulated and disseminated across IoT devices without human intervention, therefore the privacy and security of sensitive data during transmission are crucial. For this purpose, multiple routing techniques exist to ensure security and privacy in IoT Systems. One such technique is the routing protocol for low power and lossy networks (RPL) which is an IPv6 protocol commonly used for routing in IoT systems. Formal modeling of an IoT system can validate the reliability, accuracy, and consistency of the system. This paper presents the formal modeling of RPL protocol and the analysis of its security schemes using colored Petri nets that applies formal validation and verification for both the secure and non-secure modes of RPL protocol. The proposed approach can also be useful for formal modeling-based verification of the security of the other communication protocols.

State of charge estimation and error analysis of lithium-ion batteries for electric vehicles using Kalman filter and deep neural network

The lithium-ion battery has a great significance in meeting the growing demand for Electric Vehicles (EVs) due to its higher energy density, longer life cycle, and notable nominal voltage and capacity. One crucial parameter for lithium-ion batteries is the State of Charge (SOC), which represents the available capacity and ensures that the system operates in a secure and reliable mode for EVs. SOC plays a significant role in the Battery Management System (BMS). This research aims to propose an Equivalent Circuit Model (ECM) based on Kalman filtering method and a data-driven technique, Deep Feed-Forward Neural Network (DFNN), for accurate SOC estimation of Electric Vehicle Battery (EVB). Initially, lithium-ion battery parameters are identified using a second-order RC (2-RC) Equivalent Circuit Model (ECM). Subsequently, battery modeling is performed, and various operating conditions such as terminal voltage, load current, and temperature are measured to obtain initial values for the filtering method used in SOC estimation. These operating conditions are crucial for ensuring safe and efficient charging and discharging of lithium-ion batteries. Based on the identified ECM parameters, SOC estimation error and bound error are then minimized using Kalman Filter (KF), Extended Kalman Filter (EKF), and Unscented Kalman Filter (UKF) techniques. These filtering methods are employed to accurately estimate the SOC of the battery. The results demonstrate that the proposed model based on KF and EKF algorithms estimates SOC bound error within 2.5 % - –2 % and estimation error <1.5 % - –0.7 %. On the other hand, the UKF estimates a SOC bound error of 1.5 % and an estimation error of 0.5 %, proving the algorithm's efficiency and reliability. Particularly, this estimation error rejects measurement noise and parametric uncertainties for lithium-ion batteries to drive EVs with efficacy using UKF. Hence, the UKF algorithm estimated SOC has low estimation error, ensuring more accurate results. Finally, data-driven, DFNN method is implemented for accuracy enhancement of SOC estimation with trained 20 iterations and epochs data. Using this method, the SOC estimation accuracy is satisfactory with only 0.04 % Root Mean Squared Error (RMSE). The validation results indicate that the model-based filtering method is an effective method for SOC estimation to be applicable. In contrast, in a novel data-driven approach, SOC estimation accuracy is improved by approximately 0.46 %.