International Journal of Wireless and Microwave Technologies @ijwmt
Статьи журнала - International Journal of Wireless and Microwave Technologies
Все статьи: 544
Effect on System Performance due to Upgradation of 2G/3G System to LTE
Статья научная
In the current environment of burgeoning demand for mobile broadband, Long Term Evolution (LTE) is the most preferred wireless technology for the mobile operators. Considering the legacy multi-technology networks, operators need to strategically work upon maximizing their revenue while minimizing their cost and satisfying the subscriber's requirements as well. Operators have a choice between 2 network strategies- LTE overlay and single radio access network (SRAN). A survey carried out proved SRAN to be the optimum LTE deployment strategy considering the total cost of ownership (TCO). This paper discusses the effect on the system performance due to the up gradation of network from second generation (2G) to third generation (3G) to long term evolution (LTE) systems using Nokia Siemens Network Flexi multi-radio base stations. Measurements of RSRP (Reference Signal Received Power), SINR (Signal to Interference plus Noise Ratio) and throughput were carried out by a drive test within 2Km of the deployed site area which indicated that all the 3 parameters were affected as the user equipment moved away from the site area and towards the cell edges. This problem can be addressed by deployment of low power relay nodes, one of the promising techniques, for increasing the coverage of LTE advanced networks (the future of LTE systems).
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Effects of Superstrate on Electromagnetically and Gap Coupled Patch Antennas
Статья научная
In this paper the effects of water loading (termed as superstrate) on the characteristics of an electromagnetically (EM) and coupled pentagonal patch antennas operating in the ISM band have been described. The proposed antenna structures are analyzed using HFSS and the influence of the superstrate on resonant frequency, bandwidth, VSWR and radiation characteristics have also been analyzed. The obtained results also reveal that a larger bandwidth can be found in case the dielectric substrate is separated by air gap spacing. In addition, though impedance matching is little deteriorated due to loading, however the operating frequency band (BW) shifted to lower side significantly.
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Статья научная
Mobile nodes in a mobile ad hoc network communicate with each other. In order to facilitate communication of mobile nodes with fixed nodes in the Internet, gateways are used. The resultant integrated heterogeneous architecture is called Integrated Internet MANET in the literature. Such heterogeneous architectures are needed in order to realize the potential of, and to achieve the stated objectives of proposed 5G networks of the future. Gateways in Integrated Internet-MANET may be fixed or mobile. Several issues arise in Integrated Internet-MANET. In this paper, three critical issues encountered in Integrated Internet-MANET are addressed together. These issues are, efficient gateway selection mechanism, adjusting the gateway advertisement range and dynamically adapting the periodicity of gateway advertisements. Three strategies are proposed which use a path load balancing mechanism for efficient gateway selection. These strategies address the issues of adjusting the gateway advertisement range and dynamically adapting the periodicity of gateway advertisements in different ways. The proposed strategies have been simulated in a two-tier as well as a hybrid architecture using network simulation tool ns-2. The simulation results are presented and the scenarios, under which each of the proposed strategies is useful, are discussed.
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Статья научная
This paper proposes a novel approach for tuning the parameters of 6th generation (6G) extremely large-scale MIMO (Multiple Input Multiple Output) systems using the Firefly optimization algorithm. The main objective is to achieve accurate estimation of the hybrid field in the MIMO system. The proposed method optimizes MIMO system parameters by minimizing the cost function through a hybrid pre-coding and combining technique. This optimization problem is formulated as a nonlinear programming problem and solved using the Firefly algorithm. Experimental results demonstrate that the proposed approach provides accurate hybrid field estimation with improved system performance compared to existing state-of-the-art methods. The Firefly optimization algorithm proves to be an efficient and effective method for tuning 6G MIMO system parameters, with potential applications in future wireless communication systems. In addition to the Firefly optimization algorithm, this paper introduces a complementary machine learning-assisted resource allocation strategy to optimize network resource utilization. By leveraging machine learning algorithms, dynamic resource allocation based on real-time network conditions is ensured, enhancing overall system performance. The integration of the Firefly optimization algorithm for parameter tuning and machine learning-assisted resource allocation aims to achieve holistic optimization in 6G networks. Experimental results demonstrate that this integrated approach not only refines parameter tuning but also dynamically adapts resource allocation, leading to superior system efficiency and throughput compared to conventional methods. This comprehensive strategy addresses the evolving demands of future wireless communication systems. Results showed that using a sparsity value of 8, with 600 beams and 300 pilots, minimizes the mean square error of estimation to less than -13 dB
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Efficient Homomorphic Hashing Approach for Secure Reprogramming in Wireless Sensor Networks
Статья научная
While existing solutions can provide authentication services, they are insufficient for a new generation of network coding-based reprogramming protocols in wireless sensor networks. We present a security approach that is able to defend pollution attack against reprogramming protocols based on network coding. It employs a homomorphic hashing function and an identity-based aggregate signature to allow sensor nodes to check packets on-the-fly before they accept incoming encoded packets, and introduces an efficient mechanism to reduce the computation overhead at each node and to eliminate bad packets quickly. Castalia simulations show that when the 5% of the nodes in a network of 100 nodes are rogue, using our approach, the efficiency of the secure reprogramming protocol based on network coding improves almost ten-fold for a checking probability of 2%.
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Efficient Proxy Re-encryption with Private Searching in the Untrusted Cloud
Статья научная
As promising as cloud computing is, this paradigm brings forth new security and privacy challenges when operating in the untrusted cloud scenarios. In this paper, we propose a new cryptographic primitive Proxy Re-encryption with Private Searching (PRPS for short). The PRPS scheme enables the data users and owners efficiently query and access files storaged in untrusted cloud, while keeping query privacy and data privacy from the cloud providers. The concrete construction is based on proxy re-encryption, public key encryption with keyword search and the dual receiver cryptosystem. The scheme is semantically secure under the BDH assumption.
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Статья научная
The formation of P2P logical networks oblivious to the structure of physical topology results in large amount of redundant network traffic. In addition to this mismatch problem, there exists a skew in properties of the participating peers which degrade the performance of P2P networks. So the current P2P systems call for effective overlay formation taking into consideration the underlying physical network topological properties and also inbuilt heterogeneity in participating peers. The heterogeneity of peers in the network can effectively used to bias neighbor selection and improve network performance by assigning more responsibility to nodes with higher capabilities. This paper presents two techniques to solve the problems of topology mismatch and heterogeneity. The proposed methods make use of bandwidth of peers and distance measures for overlay formation in the Gnutella network. The designed systems are tested with proper analysis and simulations to verify the correctness of the methods.
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Efficient low-overhead channel estimation for 5g lens based millimeter-wave massive MIMO systems
Статья научная
Beamspace MIMO performs beam-selection which can substantially reduce the number of power-consuming radio frequency (RF) chains without perceptible performance deterioration. However, for capacity-approaching performance, accurate information of the beamspace-channel of large-size is required for beam-selection, which is contesting in case of little number of RF-chains. To overcome such problem, I proposed an efficient support-detection (SD) algorithm for channel-estimation with low pilot-overhead and short number of RF chains. The key idea of SD-algorithm is to divide the whole issue of beamspace channel-estimation into a series of sub-issues, where each of them considers only one sparse channel-component. The support of each channel component is detected reliably by deploying the sparse structure attributes of the beamspace-channel. The effect of this channel-component is eliminated from the whole channel-estimation issue. Thus, the sparse beamspace-channel can be estimated with low pilot-overhead. Simulation Results shows that the proposed schemes perform much better than the conventional compressed-sensing (CS) schemes.
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Empirical Network Performance Evaluation of Security Protocols on Operating Systems
Статья научная
Securing data transmission is currently a widely researched topic. There are numerous facades in data security. Virtual Private Network (VPN) is one such strand that provides security for data that is in motion. Performance of a network that has VPN implementation is at the forefront of network design and choice of the operating systems and cryptographic algorithms is critical to enhancing network performance. In this research undertaking, three VPN techniques, namely DES, 3DES and AES, which are commonly used to implement IPSec VPNs, are performance analyzed on test-bed setup. These are implemented on a network with Linux Fedora and a router and Windows desktop operating systems on another node. The VPN algorithms tested show that there may be performance differences when implemented with different operating system combinations.
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Enabling Trust in Single Sign-On Using DNS Based Authentication of Named Entities
Статья научная
Single Sign-On (SSO) allows the client to access multiple partner e-services through a single login session. SSO is convenient for the users as the user neither needs to set multiple login credentials nor login separately for individual services every time. SSO (single sign-on) authentication is a password-authentication approach that permits end users to login into multiple systems and websites with a single set of login credentials. SSO authentication is mainly useful for IT organizations that consist of many different commercial applications. The outstanding feature of SSO is that it gives organizations centralized control of their systems by giving different levels of access to each individual. It reduces password fatigue and increases security because users only need to remember a single username/password that grants them access to multiple systems. However, the Single Sign-on poses risks related to a single point of attack which may lead to a path for cybercrimes. This paper proposes a trust model to increase the security of Single Sign-on systems against the vulnerabilities discussed in the subsequent sections. The proposed Trust model is named as DANE-based Trust Plugin (DTP) which acts as an added security layer over DNS Based Authentication of Named entities(DANE). The DTP proposes the modified SAML XML schema which enables the DTP to counter the attacks.
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Статья научная
Cloud computing is a rapidly growing technology in this new era. Cloud is a platform where users get charged on the basis of the services and resources they have used. It enables its users to access the cloud resources from the remote locations i.e. from anywhere at any time. It needs only a working internet connection to access the cloud services. Cloud users have always been victim to the security issues and attacks which leads to the data loss. The data is not saved on the hard disk of the computer so it is highly prone to security risks. Identifying the attacks on cloud platform is a difficult task because everything on cloud is in virtual form. EDoS (Economic Denial of Sustainability) attack is a form of DDoS attacks; carried out for a long span of time and intended to put a financial burden and cause economical loss to the users of cloud. Such attacks do not exhaust the bandwidth of the user; their main aim is to put a huge financial loss or burden on the user. A technique named as SPART (Supervised Pattern Attack Recognition Technique) implemented to mitigate the EDoS attacks in cloud computing which consumes lesser energy as compared to the existing models. The experimental results have shown the less energy consumption in proposed model.
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Enhanced Image Encryption Scheme Utilizing Charlier Moments and Modified Chaotic Mapping
Статья научная
The integration of chaos theory and orthogonal moments has gained significant traction in contemporary image analysis. This paper presents a novel approach to image encryption and decryption, leveraging a modified logistic chaotic map and discrete orthogonal moments. The coefficients derived from Charlier polynomials and the image function are utilized to obfuscate the plaintext image. Furthermore, to bolster security measures, the pixel values of the obfuscated image are shuffled employing a modified logistic chaotic map. The encryption key is constructed from the parameters of both the chaotic map and Charlier polynomials, enhancing the robustness of the encryption scheme. Extensive experimental validation is conducted to assess the security of the proposed image encryption algorithm. Results demonstrate a considerable deviation in pixel values following diffusion via Charlier moments’ coefficients. Statistical tests and comprehensive security analyses affirm the resilience of the proposed algorithm against data loss attacks. The experimental result with Pearson correlation coefficient is almost 0, key space is greater than 2^210, and information entropy can reach 7.8404, which establish its superior security posture relative to existing algorithms within the domain of image encryption. The findings underscore the efficacy and reliability of the proposed scheme, positioning it as a viable solution for safeguarding sensitive image data in various applications.
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Enhanced Phishing URLs Detection using Feature Selection and Machine Learning Approaches
Статья научная
Phishing threats continue to compromise online security by using deceptive URLs to lure users and extract sensitive information. This paper presents a method for detecting phishing URLs that employs optimal feature selection techniques to improve detection system accuracy and efficiency. The proposed approach aims to enhance performance by identifying the most relevant features from a comprehensive set and applying various machine learning algorithms, including Decision Trees, XGBoost, Random Forest, Extra Trees, Logistic Regression, AdaBoost, and K-Nearest Neighbors. Key features are selected from an extensive feature set using techniques such as information gain, information gain ratio, and chi-square (χ2). Evaluation results indicate promising outcomes, with the potential to surpass existing methods. The Extra Trees classifier, combined with the chi-square feature selection method, achieved an accuracy, precision, recall, and F-measure of 98.23% using a subset of 28 features out of a total of 48. Integrating optimal feature selection not only reduces computational demands but also enhances the effectiveness of phishing URL detection systems.
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Enhanced Techniques for Filtering of Wall Messages over Online Social Networks (OSN) User Profiles
Статья научная
Online Social Networks enables various users to connect and share their messages publicly and privately. On one hand it provides advantages to the users to connect and share but on the other hand it provides disadvantage of being attacks or post messages which contains negative or abuse words. Hence OSN provides various filtering rules for security against these wall messages. Although there are various filtering rules and classifiers implemented for the filtering of these users wall messages in popular OSN such as Twitter and Facebook. But in the proposed methodology not only filtering of these wall messages is done but the categorization of normal or negative messages are identified and hence on the basis users can be blacklisted. The proposed methodology is compared with FCM and SVM for clustering and classification of messages. This approach efficiently categorizes the messages but restricts for generating filtering rules and blacklist management. Thus the approach with FCM and J48 first initializes clustering using FCM followed by generation of rules using J48 based decision tree. Hence on the basis of the rules generated message are classified and message which doesn't contain attacks is then filtered on the basis of dictionary which contains a list of abuse words. The methodology is implemented by applying FCM and SVM and a comparison is done with FCM and J48 for the performance on the basis of accuracy to detect abnormal messages.
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Статья научная
Quantum cryptography is the most convenient resolution for information security systems that presents an ultimate approach for key distribution. Today, the most viable key distribution resolutions for information security systems are those based on quantum cryptography. It is based on the quantum rules of physics rather than the assumed computational complexity of mathematical problems. But, the initial BB84 quantum key distribution protocol which is the raw key exchange of S13 quantum key distribution protocol has weakness of disclosure of large portion of secrete key or eavesdropping. Also, it cannot make use of most of the generated random bit. This paper enhanced S13 quantum key distribution protocol by employing polarization, secrete key disclosure and non-repudiation. The use of biometric or MAC address ensures non-repudiation. The row key exchange part of the S13 quantum key distribution which is the same as BB84 is enhanced by employing polarization techniques to make use of most of the generated random bit. Then, the tentative final key generated at the end of error estimation phase should be divided into blocks, padding, inverting the last bit of each block and XORing the block to generate a totally different key from the tentative one. Also, the random bits will be from biometric or serve MAC address respectively. The enhanced S13 quantum key is evaluated using cryptanalysis which shows that the enhanced protocol ensures disclosures of large portion of secrete key to prevent eavesdropping, utilization of most of the chosen binary strings to generate strong key and safeguarding against impersonation attack.
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Enhancing Cybersecurity through Bayesian Node Profiling and Attack Classification
Статья научная
Due to the epidemic, the majority of users and businesses turned to the internet, necessitating the necessity to preserve the populace and safeguard their data. However, after being attacked, the expense of data protection runs into the millions of dollars. The phrase "Protection is better than cure" is true. The paper deals with profiling the node for safeguarding against the cyberattack. There is a lot of research on network nodes. Here, we address the requirement to profile the node before utilizing machine learning to separate the data. In order to scan the nodes for risks and save the nature of threat as a database, node profiling is being investigated. The data is then classified using a machine learning algorithm utilizing the database. This research focuses on the application of machine learning methods, specifically Gaussian Naive Bayes and Decision Trees, for the segmentation of cyberattacks in streaming data. Given the continuous nature of cyberattack data, Gaussian Naive Bayes is introduced as a suitable approach. The research methodology involves the development and comparison of these methods in classifying detected attacks. The Bayesian method is employed to classify detected attacks, emphasizing the use of Gaussian Naive Bayes due to its adaptability to streaming data. Decision Trees are also discussed and used for comparison in the results section. The research explores the theoretical foundations of these methods and their practical implementation in the context of cyberattack classification. After classification, the paper delves into the crucial task of identifying intrusions in the streaming data. The effectiveness of intrusion detection is highlighted, emphasizing the importance of minimizing false negatives and false positives in a real-world cybersecurity setting. The implementation and results section presents empirical findings based on the application of Gaussian Naive Bayes and Decision Trees to a dataset. Precision, recall, and accuracy metrics are used to evaluate the performance of these methods. The research concludes by discussing the implications of the findings and suggests that Gaussian Naive Bayes is a suitable choice for streaming data due to its adaptability and efficiency. It also emphasizes the need for continuous monitoring and detection of cyberattacks to enhance overall cybersecurity. The paper provides insights into the practical applicability of these methods and suggests future work in the field of intrusion detection.
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Enhancing the Cloud Security through RC6 and 3DES Algorithms while Achieving Low-Cost Encryption
Статья научная
Cloud computing is a cutting-edge system that's widely considered the future of data processing, making cloud computing one of the widely used platforms worldwide. Cloud computing raises problems around privacy, security, anonymity, and availability. Because of this, it is crucial that all data transfers be encrypted. The overwhelming majority of files stored on the cloud are of little to no significance while the data of certain users may be crucial. To solve the problems around security, privacy, anonymity, and availability, so we propose a novel method for protecting the confidentiality and security of data while it is being processed by a cloud platform. The primary objective of this study is to enhance the cloud security with RC6 and 3DES algorithms while attained low cost encryption, and explore variety of information safety strategies. Inside the proposed system, RC6 and 3DES algorithms have been used to enhance data security and privacy. The 3DES has been used to data with a high level of sensitivity to encrypt the key of RC6 and this method is significant improve over the status quo since it increases data security while reduce the amount of time needed for sending and receiving data. Consequently, several metrics, such as encryption time, false positive rate, and P-value, have been determined by analyzing the data. According to the findings, the suggested system attained less encryption time in different file size by securely encrypting data in a short amount of time and it gives outperformance as compared to other methods.
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Enlightenment on Computer Network Reliability From Transportation Network Reliability
Статья научная
Referring to transportation network reliability problem, five new computer network reliability definitions are proposed and discussed. They are computer network connectivity reliability, computer network time reliability, computer network capacity reliability, computer network behavior reliability and computer network potential reliability. Finally strategies are suggested to enhance network reliability.
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Enterprise Private Cloud Platforms: A Systematic Review of Key Vendors
Статья научная
Cloud computing has revolutionized the way organizations manage and deploy their Information Technology infrastructure. With an increasing emphasis on data security and residency, regulatory compliance, and the need for customization, private cloud platforms have emerged as a pivotal solution in the enterprise Information Technology landscape. This paper presents a comprehensive review of private cloud technologies, delineating their key features, advantages, and capabilities. Through an exhaustive research methodology, we explore various private cloud solutions, ranging from open-source offerings to proprietary systems. A reference architecture is formulated to provide a holistic understanding of the essential components and interactions inherent to a private cloud platform. Furthermore, 18 categories and 43 subcategories of features and capabilities for the 13 most popular private cloud solutions are identified to assist organizations in evaluating and selecting the most suitable platform based on their specific requirements. This study aims to offer valuable insights to enterprises navigating their cloud adoption journey, emphasizing the significance of making informed decisions in the rapidly evolving cloud computing domain.
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Статья научная
Wireless Sensor Network (WSN) is a group of sensors connected within a geographical area to communicate with each other through wireless media. Although WSN is very important in data collection in the world today, error may occur at any stage of data processing and transmission within WSNs due to its architecture. This study presents error detection and correction in WSNs using a proposed ‘pair wise’ Residue Number System (RNS) reverse converter in a health care delivery system. The proposed RNS reverse converter required (10n+3)_FAbit hardware resources for its implementation making it suitable for sensors. The proposed scheme outperformed Weighted Function and Base Extension algorithms and Field Programmable Analog Arrays using Kalman-filter algorithm schemes in terms of its hardware requirements.
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