Статьи журнала - International Journal of Wireless and Microwave Technologies
Все статьи: 454
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 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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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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Estimate BER Distributions of Turbo Codes
Статья научная
Based on the union bound, formulas to estimate the BER distribution of channel codes are derived. By using these formulas, the BER for every position in the information sequence can be estimated. Appling the formulas to Turbo codes, several examples were given, and the results are also compared with simulation results. The results show that the derived formulas can give out good estimations of the BER distributions for Turbo codes. Therefore this would be helpful for the BER analysis, especially the unequal error protection analysis of Turbo codes.
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Evaluation of Performance for Wireless Sensor Networks Based on Gray Theory
Статья научная
A performance evaluation method of wireless sensor networks based on gray theory is proposed. Firstly the influence factors of performance are analyzed, and the index set in evaluation of wireless sensor networks' performance is built which include index of key performance and reliable characteristics. Based on AHP and gray theory, a model of evaluation of wireless sensor networks performance is given. Finally the results of example show that the evaluation model is rationality and feasibility.
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Evaluation the performance of DMZ
Статья научная
Local area networks are built mainly for two essential goals, the first one is to support the framework’s business functionality such as email, file transferring, procurement systems, internet browsing, and so forth. Second, these common networks should be built using secure strategies to protect their components. Recent developments in network communication have heightened the need for both secure and high performance network. However, the performance of network sometime is effected by applying security rules. Actually, network security is an essential priority for protecting applications, data, and network resources. Applying resources isolation rules are very important to prevent any possible attack. This isolation can be achieved by applying DMZ (Demilitarized Zone) design. A DMZ extremely enhance the security of a network. A DMZ is used to add an extra layer of protection to the network. It is also used to protect a private information. A DMZ should be properly configured to increase the network’s security. This work reviewed DMZ with regard to its importance, its design, and its effect on the network performance. The main focus of this work was to explore a means of assessing DMZ effectiveness related to network performance with simulation under OpNet simulator.
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Статья научная
The demand for cloud computing systems has increased tremendously in the IT sector and various business applications due to their high computation and cost-effective solutions to various computing problems. This increased demand has raised several challenges such as load balancing and security in cloud systems. Numerous approaches have been presented for load balancing but providing security and maintaining integrity and privacy remains a less explored research area. Intrusion detection systems have emerged as a promising solution to predict attacks. In this work, we develop a deep learning-based scheme that contains data pre-processing, convolution operations, BiLSTM model, attention layer, and CRF modeling. The current study employs a machine learning-based approach to detect intrusions based on the attackers' historical behavior. Deep learning algorithms were used to extract features from the image and determine the significance of dense packets to generate the salient fine-grained feature that can be used to detect malicious traffic and presents the final classification using fused features.
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Статья научная
Data aggregation is one of the core processing in wireless sensor network which ensures that environmental data being captured reaches the user via base station. In order to ensure proper data aggregation, there are many underlying principles that need more attention as compared to more frequently visited routing and energy problems. We reviewed existing data aggregation schemes with special focus on data correlation scheme and found that there is still a large scope of investigation in this area. We find that there are only less number of research publications towards existing techniques of data aggregation using correlational-based approach. It was also explored that such techniques still does not focus much on data quality, computational complexity, inappropriate benchmarking, etc. This paper elaborates about all the unsolved issues which require dedicate focus of investigation towards enhancing the data reliability and data quality in aggregation process in wireless sensor network.
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Extension of refinement algorithm for manually built Bayesian networks created by domain experts
Статья научная
Generally, Bayesian networks are constructed either from the available information or starting from a naïve Bayes. In the medical domain, some systems refine Bayesian network manually created by domain experts. However, existing techniques verify the relation of a node with every other node in the network. In our previous work, we define a Refinement algorithm that verifies the relation of a node only with the set of its independent nodes using Markov Assumption. In this work, we did propose Extension of Refinement Algorithm that uses both Markov Blanket and Markov Assumption to find the list of independent nodes and adhere to the property of considering minimal updates to the original network and proves that less number of comparisons is needed to find the best network structure.
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Fast Matching Algorithm Based on Fingerprint Classification Information
Статья научная
This paper focuses on fingerprint minutia matching algorithm. A special minutia neighbor structure is proposed during the matching process in this algorithm. It can locate fingerprints using the singular from classification information. In addition, minutia structure can be used to save the time of matching minutia in a simple but effective way. Then, the matching of minutia is based on the changeable sized boundary box. At the same time, possible reference position is computed to make sure the algorithm more robust to nonlinear deformation from fingerprint images. Experimental results on Fingerprint verification competition FVC2004 databases show that this algorithm can speed up the matching of fingerprint database with a preferable performance.
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Feature Dimension Reduction Algorithm Based Prediction Method for Protein Quaternary Structure
Статья научная
Knowing the quaternary structure of an uncharacterized protein often provides useful clues for finding its biological function and interaction process with other molecules in a biological system. Here, dimensionality reduction algorithm is introduced to predict the quaternary structure of proteins. Our jackknife test results indicate that it is very promising to use the dimensionality reduction approaches to cope with complicated problems in biological systems, such as predicting the quaternary structure of proteins.
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Feature Engineering for Cyber-attack detection in Internet of Things
Статья научная
Internet of Things (IoT) consists of group of devices which communicates information over private networks. One of the key challenges faced by IoT networks is the security breaches. With the objective of automating the detection of possible security breaches in five categories, IoT traffic created with Message Queue Telemetry Transport (MQTT) protocol is analyzed. The five categories of cyber-attacks considered are brute force, denial of service (DoS), flooding, malformed data, and SlowITe attacks along with legitimate traffic. The popular five machine learning (ML) models, LightGBM, Random Forest, MLP, AdaBoost, and Decision Tree Classifiers are trained to predict cyber-attacks. In traditional traffic analysis all the available features of MQTT traffic were utilized for the ML modeling and in this work, we challenge the practice by showing that automated feature selection improves the performance of the overall ML models. The average accuracy, precision, recall and the F1 score are used as performance evaluation metrics. It is observed that all models in average are able to achieve 90% of accuracy in classification, while MLP model is trained 10 times faster than the other models. Further the optimal number of features for correct classification is identified as 10 features through Monte Carlo analysis. With the reduced features, it is possible to detect DoS, flooding, and SlowITe attacks with more than 90% accuracy and precision. Yet, it is difficult to tell apart brute force and malformed data attacks.
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Fixed Cluster Formations with Nearest Cluster Heads in Wsns
Статья научная
The limited battery usage of a sensor node is one of the significant issues in WSNs. Therefore, extending the lifetime of WSNs through energy efficient mechanisms has become a challenging research area. Previous studies have shown that clustering can decrease the transmission distance of the sensor nodes thus, prolongs the lifetime of the network. In literature, most of the LEACH variants aim to set-up clusters in each round by changing CHs randomly. These formations cause to spend high amount of energy and induce additional network costs. In this paper, an energy-efficient nearest constant clustering approach is proposed to solve the problems of LEACH based protocols. The proposed approach uses constant clusters which are formed only once when algorithm starts. The cluster formation remains fixed until the energies of the all sensors are finished. Proposed approach aims to select nearest CHs in each cluster randomly without changing the cluster formations.
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Format-Compliant Encryption of JPEG2000 Codestreams
Статья научная
In this paper, we propose two format-compliant encryption schemes for JPEG2000, which preserve the syntax of the original codestream and do not introduce superfluous markers into the encrypted bitstream. The proposed efficient scheme randomly encrypts either low or upper half bytes of those randomly selected bytes in Codeblock Contribution to Packets (CCPs). The secure scheme encrypts both low and upper half bytes and can protect the nearly whole codestream except for the header information. The proposed schemes can provide efficient, secure, scalable and completely format-compliant protection of JPEG2000, which is proved by lots of experiments.
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