Detecting fraud in financial transactions is crucial for guaranteeing the integrity and security of financial systems. This paper presents an integrated approach for detecting fraudulent activities that incorporates Support Vector Machines (SVM) and Feedforward Neural Networks (FFNN). The proposed methodology utilizes the strengths of SVM and FFNN to distinguish between classes and capture complex patterns and relationships, respectively. The SVM model functions as a feature extractor, supplying the FFNN with high-level representations as inputs. Through an exhaustive evaluation utilizing labeled financial transaction data, the integrated SVM-FFNN model shows promise in detecting fraud with increased accuracy and precision. This research contributes to the development of innovative techniques for enhancing financial fraud detection systems.
{"title":"Integrated SVM-FFNN for Fraud Detection in Banking Financial Transactions","authors":"Udayakumar Dr.R., Dr.P. Bharath Kumar Chowdary, Devi Dr.T., Sugumar Dr.R.","doi":"10.58346/jisis.2023.i4.002","DOIUrl":"https://doi.org/10.58346/jisis.2023.i4.002","url":null,"abstract":"Detecting fraud in financial transactions is crucial for guaranteeing the integrity and security of financial systems. This paper presents an integrated approach for detecting fraudulent activities that incorporates Support Vector Machines (SVM) and Feedforward Neural Networks (FFNN). The proposed methodology utilizes the strengths of SVM and FFNN to distinguish between classes and capture complex patterns and relationships, respectively. The SVM model functions as a feature extractor, supplying the FFNN with high-level representations as inputs. Through an exhaustive evaluation utilizing labeled financial transaction data, the integrated SVM-FFNN model shows promise in detecting fraud with increased accuracy and precision. This research contributes to the development of innovative techniques for enhancing financial fraud detection systems.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":"86 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-02DOI: 10.58346/jisis.2023.i4.003
Miguel Jiménez-Carrión, Gustavo A. Flores-Fernandez, Alejandro B. Jiménez-Panta
The main objective of this study was to implement a computational prototype in two stages: the first stage primarily focused on generating efficient routes based on an evolutionary algorithm. In other words, the complex computational problem was solved in the first stage. The second stage then shifted its focus towards determining the fleet size and frequencies using an allocation algorithm. This approach was designed to address the complex combinatorial search problem within a public transportation network. In the first stage, the prototype utilizes the metaheuristic known as Genetic Algorithms (GA). Within the GA operators, an innovative method called "aggregated crossover" is employed, with an additional mutation procedure that maintains feasible descendants. In the second stage, an allocation algorithm is used, taking into account the routes generated in the first stage. The results demonstrate that in the first stage, the GA metaheuristic consistently delivers highly efficient routes in each run, confirming that the combinatorial complexity of the problem is effectively resolved in this initial phase. These results were validated on Mandl's Swiss Road network, showing superior solutions compared to those presented in previous studies. Notably, the execution time for this process is only 35 minutes.
{"title":"Efficient Transit Network Design, Frequency Adjustment, and Fleet Calculation Using Genetic Algorithms","authors":"Miguel Jiménez-Carrión, Gustavo A. Flores-Fernandez, Alejandro B. Jiménez-Panta","doi":"10.58346/jisis.2023.i4.003","DOIUrl":"https://doi.org/10.58346/jisis.2023.i4.003","url":null,"abstract":"The main objective of this study was to implement a computational prototype in two stages: the first stage primarily focused on generating efficient routes based on an evolutionary algorithm. In other words, the complex computational problem was solved in the first stage. The second stage then shifted its focus towards determining the fleet size and frequencies using an allocation algorithm. This approach was designed to address the complex combinatorial search problem within a public transportation network. In the first stage, the prototype utilizes the metaheuristic known as Genetic Algorithms (GA). Within the GA operators, an innovative method called \"aggregated crossover\" is employed, with an additional mutation procedure that maintains feasible descendants. In the second stage, an allocation algorithm is used, taking into account the routes generated in the first stage. The results demonstrate that in the first stage, the GA metaheuristic consistently delivers highly efficient routes in each run, confirming that the combinatorial complexity of the problem is effectively resolved in this initial phase. These results were validated on Mandl's Swiss Road network, showing superior solutions compared to those presented in previous studies. Notably, the execution time for this process is only 35 minutes.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":"115 33","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138607338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-02DOI: 10.58346/jisis.2023.i4.004
SenthilKumar Ilango, Ravichandran Dr.K.
This Exploration dives into the complex exchange between social networks, zeroing in on their design, security measures, and the impact of human factors. As social networks keep on molding present day correspondence and connection, understanding their elements turns out to be progressively pivotal. The examination investigates the architecture and user-focused design rules that improve user experiences, encourage community associations, and empower self-expression. All the while, the review tends to the squeezing security challenges presented by these platforms, dissecting risks like identity theft and misinformation dispersal, and proposing techniques for powerful encryption and data protection. Moreover, the review digs into the domain of human behavior and brain research, clarifying how individual inspirations, cognitive biases, and social standards add to content creation, sharing, and commitment inside social networks. The bits of knowledge acquired give a complete perspective on what user activities mean for network elements and the development of online networks. By exploring these aspects, the review expects to illuminate platform developers and policymakers, offering important direction on upgrading design, carrying out powerful security measures, and figuring out user behavior. Eventually, this examination adds to an all-encompassing comprehension of social networks, introducing a diverse investigation of design, security, and human factors. The discoveries guide the advancement of more user-centric, secure, and socially significant social organization platforms that line up with user inclinations and contribute decidedly to the digital landscape.
{"title":"Exploring the Convergence of Design, Security, and Human Dynamics in Social Networks in India","authors":"SenthilKumar Ilango, Ravichandran Dr.K.","doi":"10.58346/jisis.2023.i4.004","DOIUrl":"https://doi.org/10.58346/jisis.2023.i4.004","url":null,"abstract":"This Exploration dives into the complex exchange between social networks, zeroing in on their design, security measures, and the impact of human factors. As social networks keep on molding present day correspondence and connection, understanding their elements turns out to be progressively pivotal. The examination investigates the architecture and user-focused design rules that improve user experiences, encourage community associations, and empower self-expression. All the while, the review tends to the squeezing security challenges presented by these platforms, dissecting risks like identity theft and misinformation dispersal, and proposing techniques for powerful encryption and data protection. Moreover, the review digs into the domain of human behavior and brain research, clarifying how individual inspirations, cognitive biases, and social standards add to content creation, sharing, and commitment inside social networks. The bits of knowledge acquired give a complete perspective on what user activities mean for network elements and the development of online networks. By exploring these aspects, the review expects to illuminate platform developers and policymakers, offering important direction on upgrading design, carrying out powerful security measures, and figuring out user behavior. Eventually, this examination adds to an all-encompassing comprehension of social networks, introducing a diverse investigation of design, security, and human factors. The discoveries guide the advancement of more user-centric, secure, and socially significant social organization platforms that line up with user inclinations and contribute decidedly to the digital landscape.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":"29 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-02DOI: 10.58346/jisis.2023.i4.005
B. Fakiha
This study examined the use of Raspberry Pi for forensic analysis and its potential for providing computer protection. It investigates its capability to identify suspicious patterns on USB drives and its compatibility with certain software. Furthermore, it examines the ability of the Raspberry Pi to generate reports and send email notifications upon detection of any malicious files such as worms, Trojans, and spyware. Additionally, it investigates Raspberry Pi's ability to move potentially malicious files to a secure trash folder for sanitization. The experiment was designed using an experimental method. The findings suggest that the Raspberry Pi can provide computer protection through automatic report generation and email notifications for malicious file detection. As a result, this study provides evidence that Raspberry Pi can effectively provide digital forensics services. Its quick file search capabilities make it a powerful tool that can help organizations gather crucial digital evidence that may otherwise remain undetected.
{"title":"The Role of Raspberry Pi in Forensic Computer Crimes","authors":"B. Fakiha","doi":"10.58346/jisis.2023.i4.005","DOIUrl":"https://doi.org/10.58346/jisis.2023.i4.005","url":null,"abstract":"This study examined the use of Raspberry Pi for forensic analysis and its potential for providing computer protection. It investigates its capability to identify suspicious patterns on USB drives and its compatibility with certain software. Furthermore, it examines the ability of the Raspberry Pi to generate reports and send email notifications upon detection of any malicious files such as worms, Trojans, and spyware. Additionally, it investigates Raspberry Pi's ability to move potentially malicious files to a secure trash folder for sanitization. The experiment was designed using an experimental method. The findings suggest that the Raspberry Pi can provide computer protection through automatic report generation and email notifications for malicious file detection. As a result, this study provides evidence that Raspberry Pi can effectively provide digital forensics services. Its quick file search capabilities make it a powerful tool that can help organizations gather crucial digital evidence that may otherwise remain undetected.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":"31 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-02DOI: 10.58346/jisis.2023.i4.006
S. T. Revathi, Gayathri A., Sathya A., Santhiya M.
Internet of Things (IoT) is an advanced applied science in recent years that enables communication among humans and smart components or among Internet-based components. Besides, IoT provides affiliation of physical and virtual elements that are fully controlled by different kinds of hardware, software, and interaction advancements. Though numerous methods of IoT offer many advantages to our day-to-day routine, it also possesses huge security weaknesses. The traditional methods are vulnerable to a huge range of attacks. Hence, establishing safe and effective security alternatives for the IoT environment remains as a main challenge and the major risk in this security solution is to transfer significant information in a secure manner. To address such limitations, an effective authentication approach named CHEK-based authentication methodology is devised for secure communication in IoT. The proposed authentication scheme consists of four steps and the authentication approach is developed by considering various security operations like hashing, encryption, secret key pairs, passwords, and so on. Moreover, the CHEK-based authentication scheme provides promising solution with minimum computational cost of 16.541 and minimum memory usage of 72.3MB.
物联网(Internet of Things, IoT)是近年来发展起来的一门先进的应用科学，它能够实现人与智能组件之间或基于互联网的组件之间的通信。此外，物联网提供了物理和虚拟元素的从属关系，这些元素完全由不同类型的硬件，软件和交互进步控制。尽管物联网的许多方法为我们的日常工作提供了许多优势，但它也具有巨大的安全弱点。传统的方法容易受到各种各样的攻击。因此，为物联网环境建立安全有效的安全替代方案仍然是一项主要挑战，这种安全解决方案的主要风险是以安全的方式传输重要信息。为了解决这些限制，设计了一种有效的身份验证方法，称为基于check的身份验证方法，用于物联网中的安全通信。提出的身份验证方案由四个步骤组成，并且通过考虑各种安全操作(如散列、加密、秘密密钥对、密码等)来开发身份验证方法。此外，基于check的认证方案以最小的计算成本(16.541)和最小的内存使用(72.3MB)提供了有前途的解决方案。
{"title":"ECC based Authentication Approach for Secure Communication in IoT Application","authors":"S. T. Revathi, Gayathri A., Sathya A., Santhiya M.","doi":"10.58346/jisis.2023.i4.006","DOIUrl":"https://doi.org/10.58346/jisis.2023.i4.006","url":null,"abstract":"Internet of Things (IoT) is an advanced applied science in recent years that enables communication among humans and smart components or among Internet-based components. Besides, IoT provides affiliation of physical and virtual elements that are fully controlled by different kinds of hardware, software, and interaction advancements. Though numerous methods of IoT offer many advantages to our day-to-day routine, it also possesses huge security weaknesses. The traditional methods are vulnerable to a huge range of attacks. Hence, establishing safe and effective security alternatives for the IoT environment remains as a main challenge and the major risk in this security solution is to transfer significant information in a secure manner. To address such limitations, an effective authentication approach named CHEK-based authentication methodology is devised for secure communication in IoT. The proposed authentication scheme consists of four steps and the authentication approach is developed by considering various security operations like hashing, encryption, secret key pairs, passwords, and so on. Moreover, the CHEK-based authentication scheme provides promising solution with minimum computational cost of 16.541 and minimum memory usage of 72.3MB.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":"42 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-02DOI: 10.58346/jisis.2023.i4.011
Veerasamy K., E.J. Thomson Fredrik
Meeting the current population's food demands has become challenging, given the rising population, frequent climate fluctuations, and limited resources. Smart farming, also known as precision agriculture, has emerged as an advanced approach to tackle modern challenges in crop production. At the heart of this cutting-edge technology is machine learning, serving as the driving force behind its implementation. Though, there are many algorithms are available in crop prediction process, the problem of predicting vague information is still a challenging issue. Unfortunately, existing algorithms mostly avoids the complicated instances in crop recommendation dataset by not handling them effectively, due to imbalance class distribution. Hence in this research work to conduct an intelligent farming, two different uncertain theories are adopted to handle the issue of vagueness in appropriate recommendation of crop by considering soil fertility and climatic condition. The proposed is developed based on uncertainty expert system with both neutrosophicalparaconsistent inference model. The neutrosophic inference model is integrated with the paraconsistent logic to overcome the problem of uncertainty in prediction of appropriate crop by representing the factors in terms of certainty degree and contradiction degree. The rule generated by paraconsistent model is validated to improve the accuracy of crop prediction by fusing the knowledge of butterfly optimization algorithm. The nectar searching behavior of the butterflies are used for searching potential rules as a validation process. With the pruned rules generated by uncertainty expert model, the suitable crop is predicted more accurately compared to the other existing prediction models.
{"title":"Intelligent Farming based on Uncertainty Expert System with Butterfly Optimization Algorithm for Crop Recommendation","authors":"Veerasamy K., E.J. Thomson Fredrik","doi":"10.58346/jisis.2023.i4.011","DOIUrl":"https://doi.org/10.58346/jisis.2023.i4.011","url":null,"abstract":"Meeting the current population's food demands has become challenging, given the rising population, frequent climate fluctuations, and limited resources. Smart farming, also known as precision agriculture, has emerged as an advanced approach to tackle modern challenges in crop production. At the heart of this cutting-edge technology is machine learning, serving as the driving force behind its implementation. Though, there are many algorithms are available in crop prediction process, the problem of predicting vague information is still a challenging issue. Unfortunately, existing algorithms mostly avoids the complicated instances in crop recommendation dataset by not handling them effectively, due to imbalance class distribution. Hence in this research work to conduct an intelligent farming, two different uncertain theories are adopted to handle the issue of vagueness in appropriate recommendation of crop by considering soil fertility and climatic condition. The proposed is developed based on uncertainty expert system with both neutrosophicalparaconsistent inference model. The neutrosophic inference model is integrated with the paraconsistent logic to overcome the problem of uncertainty in prediction of appropriate crop by representing the factors in terms of certainty degree and contradiction degree. The rule generated by paraconsistent model is validated to improve the accuracy of crop prediction by fusing the knowledge of butterfly optimization algorithm. The nectar searching behavior of the butterflies are used for searching potential rules as a validation process. With the pruned rules generated by uncertainty expert model, the suitable crop is predicted more accurately compared to the other existing prediction models.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":"14 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138607127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-02DOI: 10.58346/jisis.2023.i4.009
Abeer A. Kadhim, Samir J. Mohammed, Qais Al-Gayem
DVB-T2 offers the best levels of efficiency, reliability, and flexibility of any digital terrestrial broadcast technology now available. It provides the most up-to-date coding and modulation techniques to make the valuable terrestrial spectrum extremely effectively usable for many types of transmission. The mobile configuration of DVBT2 also known as T2-Lite, employs a constrained set of possible modes that are suited for movable transmission and reduce the demands placed on the receiver. This study compares the T2-Lite system's performance before and after using constellation rotation and cyclic Quadrature (Q) delay methods among different types of constellations, coding rates, and fading channels. Results show a significant improvement in T2-Lite system performance while using a rotating constellation in a bad fading environment. Moreover, the utilization of this technique enhances DVB-T2 Lite gain. All simulation of system components and channels were carried out in MATLAB R2021a software.
{"title":"Digital Video Broadcasting T2 Lite Performance Evaluation Based on Rotated Constellation Rates","authors":"Abeer A. Kadhim, Samir J. Mohammed, Qais Al-Gayem","doi":"10.58346/jisis.2023.i4.009","DOIUrl":"https://doi.org/10.58346/jisis.2023.i4.009","url":null,"abstract":"DVB-T2 offers the best levels of efficiency, reliability, and flexibility of any digital terrestrial broadcast technology now available. It provides the most up-to-date coding and modulation techniques to make the valuable terrestrial spectrum extremely effectively usable for many types of transmission. The mobile configuration of DVBT2 also known as T2-Lite, employs a constrained set of possible modes that are suited for movable transmission and reduce the demands placed on the receiver. This study compares the T2-Lite system's performance before and after using constellation rotation and cyclic Quadrature (Q) delay methods among different types of constellations, coding rates, and fading channels. Results show a significant improvement in T2-Lite system performance while using a rotating constellation in a bad fading environment. Moreover, the utilization of this technique enhances DVB-T2 Lite gain. All simulation of system components and channels were carried out in MATLAB R2021a software.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":"9 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-02DOI: 10.58346/jisis.2023.i4.010
Udayakumar R., Joshi A., Boomiga S.S., Sugumar R.
Given the growing dependence on digital systems and the escalation of financial fraud occurrences, it is imperative to implement efficient cyber security protocols and fraud detection methodologies. The threat's dynamic nature often challenges conventional methods, necessitating the adoption of more sophisticated strategies. Individuals depend on pre-established regulations or problem-solving processes, which possess constraints in identifying novel and intricate fraudulent trends. Conventional techniques need help handling noise data and the substantial expenses incurred by false positives and true positives. To tackle these obstacles, the present study introduces Deep Fraud Net, a framework that utilizes deep learning to detect and classify instances of financial fraud and cyber security threats. The Deep Fraud Net system model entails the utilization of a deep neural network to acquire intricate patterns and characteristics from extensive datasets through training. The framework integrates noise reduction methods to enhance the precision of fraud detection and improve the quality of input data. The Deep Fraud Net method attains a precision of 98.85%, accuracy of 93.35%, sensitivity of 99.05%, specificity of 93.16%, false positive rate of 7.34%, and true positive rate of 89.58%. The findings suggest that Deep Fraud Net can effectively detect and categorize instances of fraudulent behavior with a reduced occurrence of misclassifications. The method exhibits potential implications for diverse domains that prioritize robust security and fraud detection, including but not limited to banking, e-commerce, and online transactions.
{"title":"Deep Fraud Net: A Deep Learning Approach for Cyber Security and Financial Fraud Detection and Classification","authors":"Udayakumar R., Joshi A., Boomiga S.S., Sugumar R.","doi":"10.58346/jisis.2023.i4.010","DOIUrl":"https://doi.org/10.58346/jisis.2023.i4.010","url":null,"abstract":"Given the growing dependence on digital systems and the escalation of financial fraud occurrences, it is imperative to implement efficient cyber security protocols and fraud detection methodologies. The threat's dynamic nature often challenges conventional methods, necessitating the adoption of more sophisticated strategies. Individuals depend on pre-established regulations or problem-solving processes, which possess constraints in identifying novel and intricate fraudulent trends. Conventional techniques need help handling noise data and the substantial expenses incurred by false positives and true positives. To tackle these obstacles, the present study introduces Deep Fraud Net, a framework that utilizes deep learning to detect and classify instances of financial fraud and cyber security threats. The Deep Fraud Net system model entails the utilization of a deep neural network to acquire intricate patterns and characteristics from extensive datasets through training. The framework integrates noise reduction methods to enhance the precision of fraud detection and improve the quality of input data. The Deep Fraud Net method attains a precision of 98.85%, accuracy of 93.35%, sensitivity of 99.05%, specificity of 93.16%, false positive rate of 7.34%, and true positive rate of 89.58%. The findings suggest that Deep Fraud Net can effectively detect and categorize instances of fraudulent behavior with a reduced occurrence of misclassifications. The method exhibits potential implications for diverse domains that prioritize robust security and fraud detection, including but not limited to banking, e-commerce, and online transactions.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":"112 47","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138607495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-02DOI: 10.58346/jisis.2023.i4.008
Aswathy R.H., Srithar S., K. R. Dayana, Padmavathi Padmavathi, Suresh P.
Internet of Things (IoT) provides an imminent floor to exchange information and enhance communication technology using embedded devices that are too sophisticated daily and deployed in diverse fields of life. The colossal volume of sensors employed within IoT application leads to disperse an enormous amount of data in the open air. The rudimentary facet of IoT enabled technologies having the pitfall, security. It is a practical problem in terms of networking, application and communication. Since the resource constraint feature of IoT enabled technology, both security and efficiency can be balanced. The effective algorithm builds over Elliptic Curve Cryptography (ECC) provides an effective solution due to its small key size. The sensor node in this scheme is incorporated with TPM to protect the system in crucial IoT applications. In this proposed work, a three-way authentication factor with key agreement protocol proposed with consecutive phases such as registration, login, authentication, and access control. The security assessment of the proposed scheme with diverse attacks are elaborated and the computation overhead compared with related schemes.
{"title":"MIAS: An IoT based Multiphase Identity Authentication Server for Enabling Secure Communication","authors":"Aswathy R.H., Srithar S., K. R. Dayana, Padmavathi Padmavathi, Suresh P.","doi":"10.58346/jisis.2023.i4.008","DOIUrl":"https://doi.org/10.58346/jisis.2023.i4.008","url":null,"abstract":"Internet of Things (IoT) provides an imminent floor to exchange information and enhance communication technology using embedded devices that are too sophisticated daily and deployed in diverse fields of life. The colossal volume of sensors employed within IoT application leads to disperse an enormous amount of data in the open air. The rudimentary facet of IoT enabled technologies having the pitfall, security. It is a practical problem in terms of networking, application and communication. Since the resource constraint feature of IoT enabled technology, both security and efficiency can be balanced. The effective algorithm builds over Elliptic Curve Cryptography (ECC) provides an effective solution due to its small key size. The sensor node in this scheme is incorporated with TPM to protect the system in crucial IoT applications. In this proposed work, a three-way authentication factor with key agreement protocol proposed with consecutive phases such as registration, login, authentication, and access control. The security assessment of the proposed scheme with diverse attacks are elaborated and the computation overhead compared with related schemes.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":"13 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138607000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-02DOI: 10.58346/jisis.2023.i4.012
A. Mohammed, Hassan Mostafa, Abd El-Hady. A. Ammar
One of the most significant obstacles facing the Internet of Things (IoT) is how to offer support for communication to an expanding number of linked items. Narrow-band Internet of Things (NB-IoT), which is currently an aspect of fifth-generation (5G), is a new narrow-band wireless communication technology that has evolved in recent years to address this issue. To save power, NB-IoT currently exploits modulation schemes that are characterized by low order to deliver low data rate. However, as the number of applications dependent on data rate increases, NB-IoT needs to use data rate improvement technologies that do not consume additional power. This paper proposes a design for quadrupling the total number of linked items in the NB-IoT system using a symbol time compression methodology. A modified symbol time compression (MSTC) approach is specifically suggested, which could preserve 75% of the bandwidth (BW) by reducing the symbol time to a quarter (25%). This study suggests a design that uses the MSTC method four times in orthogonal frequency division multiplexing (4-MSTC-OFDM) to take advantage of the unused bandwidth and has the capability to deliver a quadruple quantity of information in comparison to the standard OFDM system. Simulations show that the suggested design (4-MSTC-OFDM) lowers the signal-to-noise ratio (SNR) by 3.9 dB (at BER = 10-6) and 4.4 dB (at BER = 10-4) compared to the OFDM system with 16-QAM (16-QAM-OFDM) when sending the same amount of data over the Rayleigh fading channel and additive white Gaussian noise channel (AWGN). Moreover, the results of simulations indicate that the proposed design possesses an identical BER as the conventional OFDM technique, implying that using the suggested method does not degrade the BER.
物联网(IoT)面临的最大障碍之一是如何为越来越多的连接项目提供通信支持。窄带物联网(NB-IoT)是近年来为解决这一问题而发展起来的一种新的窄带无线通信技术，目前是第五代(5G)的一个方面。为了节省功耗，NB-IoT目前利用低阶调制方案来提供低数据速率。然而，随着依赖数据速率的应用数量的增加，NB-IoT需要使用不消耗额外功率的数据速率改进技术。本文提出了一种使用符号时间压缩方法将NB-IoT系统中链接项目总数增加四倍的设计。特别提出了一种改进的符号时间压缩(MSTC)方法，通过将符号时间减少到四分之一(25%)，可以保留75%的带宽(BW)。本研究提出了一种在正交频分复用(4-MSTC-OFDM)中使用四次MSTC方法的设计，以利用未使用的带宽，并且与标准OFDM系统相比，能够提供四倍的信息量。仿真结果表明，与采用16-QAM (16-QAM-OFDM)的OFDM系统相比，在瑞利衰落信道和加性高斯白噪声信道(AWGN)上发送相同数量的数据时，该设计(4-MSTC-OFDM)的信噪比(SNR)分别降低3.9 dB (BER = 10-6)和4.4 dB (BER = 10-4)。此外，仿真结果表明，该设计具有与传统OFDM技术相同的误码率，这意味着使用该方法不会降低误码率。
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