International Journal of Computer Network and Information Security @ijcnis
Статьи журнала - International Journal of Computer Network and Information Security
Все статьи: 1130
Cloud-based framework for efficient storage of unstructured patient health records
Статья научная
Recently, in healthcare sector, the data is steadily growing and becomes more vital. Most of this data is embedded in the medical record of the patient. In fact, Patient Health Records (PHRs) refer to those records that the patient can maintain, access and share among different specialists. Storing these PHRs to the cloud allow the patient to maintain and share them with different practitioners anywhere and anytime. However, he still suffers from some security and privacy issues. Hence, it is necessary to guarantee the security and privacy of this immense volume of patient's confidential data on the cloud. Anonymization and encryption are the two methods that can be adopted to ensure the security and privacy of PHRs on cloud. In this paper, a cloud-based framework for securing the storage and the retrieval of unstructured PHRs is proposed. This framework combines different encryption techniques to encrypt the different contents of the PHR, to compress medical images and to control the access to these records. In addition, the encrypted files are partitioned into a random number of files before being sent to the cloud storage server. These files are of variable number and variable size. When a user requests to access a PHR from the cloud, the proposed framework first controls access of this user before merging the partitioned files. The decryption of these files is performed on the client side not on the cloud using the secret key, which is owned by authorized user only. Finally, extensive analytical and experimental results are presented. It shows the security, scalability, and efficiency of the proposed framework.
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Статья научная
Mobile Ad-hoc Network (MANET) data transfer between nodes in a multi-hop way offers a wide variety of applications. The dynamic feature of ad hoc network mobile nodes is primarily influenced by safety issues, which limit data forwarding rate in multipath routing. As a supplementary method to improve safe data delivery in a MANET, this paper propose and analyse the cluster head (CH) selection and optimum multipath scheme. The CHs are chosen based on the possibility values of each node in MANET, which are considered from the residual energy of each node. During the present phase, the total remaining node energy is used to calculate the mean energy of the entire network. The most likely nodes are picked as the CH, which gathers packets from the cluster members through multi-hop communication. The fundamental idea is to partition a top-secret communication into several shares and then forward the shares via numerous routes to the destination. The Coral Reef Optimization method is used in this work to perform optimum multipath routing. The thorough simulation findings validate the feasibility and efficacy of the suggested strategy in comparison to Butterfly optimization algorithm (BA), Whale Optimization algorithm (WOA) and BAT algorithm techniques.
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Cluster based routing protocols for IOT application
Статья научная
Extending the battery lifetime and reducing the power consumption using ultra low power sensor nodes and energy harvesting systems is essential to realize 50 billion IOT devices. Development of efficient routing algorithm is a critical aspect for reducing energy consumption and enhancing network lifetime. Clustering is a key technique used to enhance network lifetime. The lifetime of a wireless sensor network for Daylight Artificial Light Integrated Scheme is enhanced using Self Organizing Map (SOM) based clustering algorithm. A simulation of cluster based routing protocols like LEACH (Low Energy Adaptive Clustering Hierarchy), Fuzzy based LEACH and ANFIS based LEACH is also carried out using MATLAB software.
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Clustering Method of Mobile Cloud Computing According to Technical Characteristics of Cloudlets
Статья научная
The rapid increase in the number of mobile phones and IoT devices connected to the network reduces the bandwidth of the Internet communication channel, and as a result, delays occur in the delivery of data processed in remote clouds. Edge computing systems (cloudlet, fog computing, etc.) are used to eliminate resource shortages, energy consumption, and communication channel delays in mobile devices. Edge computing systems place processing devices (computers) close to users. Cloudlet-based mobile cloud computing is widely used to reduce delays in communication channels and energy consumption in mobile devices. Selection of the most suitable cloudlet allowing users to run applications fast in cloud is still a considerable problem. This paper proposes a strategy for the selection of high-performance cloudlets providing fast solutions, considering the complexity of application (file type). It offers a method for cloudlet selection out of large number of cloudlets with different technical capabilities providing faster processing of user application. The timing of user applications in cloudlets with different technical capabilities (operating frequency, number of cores, volume of RAM, etc.) also varies. The proposed method provides faster solution for the user application. User applications are grouped by type of application, and a set of cloudlets are clustered by the number of groups. Clustering is performed first by the parameters corresponding to the operating frequency of the cloudlets, then by the number of cores and the volume of RAM. The proposed method reduces energy consumption of mobile devices by providing faster processing of applications. Thus, the proposed strategy provides an energy consumption reduction on mobile devices, faster processing of results and decrease of network delays.
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Clustering in Wireless Sensor Networks- A Survey
Статья научная
Increased demand of Wireless Sensor Networks (WSN) in various applications has made it a hot research area. Several challenges imposed which include energy conservation, scalability, limited network resources etc. with energy conservation being the most important. Clustering improves the energy efficiency by making high power nodes as cluster heads (CHs) which reduces the chance of energy depletion of nodes. Scalability, fault tolerance, data aggregation, energy efficiency are some of the main objectives of clustering. This paper discusses various challenges associated with clustering and different methods or techniques developed to overcome these challenges. Various clustering approaches have been summarized and few prominent Quality of service (QoS) based clustering routing protocols for WSN have been identified. Comparison of these approaches and protocols is discussed based on some parameters.
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Code Formal Verification of Operation System
Статья научная
With the increasing pressure on non-function attributes (security, safety and reliability) requirements of an operation system, high–confidence operation system is becoming more important. Formal verification is the only known way to guarantee that a system is free of programming errors. We research on formal verification of operation system kernel in system code level and take theorem proving and model checking as the main technical methods to resolve the key techniques of verifying operation system kernel in C code level. We present a case study to the verification of real-world C systems code derived from an implementation of μC/OS – II in the end.
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Communication Architecture for Underwater Wireless Sensor Network
Статья научная
Investigations in hydrologic sciences are bounded because most of existing water surveillance methods are manual. Such systems are incapable to gather information at spatial and temporal level due to location constraints. In this paper, we present a new communication architecture for Underwater Wireless Sensor Network (UWSN) based on acoustic communication. However, unique challenges offered by underwater environment are main hindrance in deployment of UWSN in real life applications. So, we discuss various communication methodologies to figure out which one suits best to the requirements of UWSN. Our simulation results illustrate change in data transmission rate, energy consumption and transmission time w.r.t transmission range and number of nodes in network. Results prove that multi-hop communication offer high transmission rate, large bandwidth. Moreover, multi-hop communication is much more energy and time efficient than direct communication.
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Communication Centrality in Dynamic Networks Using Time-Ordered Weighted Graph
Статья научная
Centrality is an important concept in the study of social network analysis (SNA), which is used to measure the importance of a node in a network. While many different centrality measures exist, most of them are proposed and applied to static networks. However, most types of networks are dynamic that their topology changes over time. A popular approach to represent such networks is to construct a sequence of time windows with a single aggregated static graph that aggregates all edges observed over some time period. In this paper, an approach which overcomes the limitation of this representation is proposed based on the notion of the time-ordered graph, to measure the communication centrality of a node in dynamic networks.
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Comparative Analysis of AODV, OLSR, TORA, DSR and DSDV Routing Protocols in Mobile Ad-Hoc Networks
Статья научная
Mobile Ad-Hoc Networks (MANETs) are autonomous and decentralized wireless systems. Mobile Ad hoc Network is a collection of mobile nodes in which the wireless links are frequently broken down due to mobility and dynamic infrastructure. Routing is a significant issue and challenge in ad hoc networks. Many Routing protocols have been proposed so far to improve the routing performance and reliability. This research paper describes the characteristics of ad hoc routing protocols Ad-hoc On Demand Distance Vector Routing (AODV), Optimized link State Routing (OLSR), Temporally Ordered Routing Algorithm (TORA), Dynamic Source Routing (DSR), Destination-Sequenced Distance-Vector Routing (DSDV) based on the performance metrics like packet delivery fraction, Average delay, Normalized Routing load, Throughput and Jitter under low mobility and low traffic network as well as under high mobility and high traffic network. Results show that AODV has maximum throughput under low traffic and DSDV has maximum throughput under high traffic. As network becomes dense OLSR, DSR and DSDV perform well in terms of Throughput than AODV and TORA. TORA performs well in dense networks in terms of packet delivery fraction but at the same time Normalized Routing load of TORA is maximum among all the protocols in both the networks. DSDV has least Normalized Routing load in both low and high traffic. OLSR and DSDV give the least Jitter and Average Delay in both networks.
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Comparative Analysis of Classification Algorithms on KDD'99 Data Set
Статья научная
Due to the enormous growth of network based services and the need for secure communications over the network there is an increasing emphasis on improving intrusion detection systems so as to detect the growing network attacks. A lot of data mining techniques have been proposed to detect intrusions in the network. In this paper study of two different classification algorithms has been carried out: Naïve Bayes and J48. Results obtained after applying these algorithms on 10% of the KDD'99 dataset and on 10% of the filtered KDD'99 dataset are compared and analyzed based on several performance metrics. Comparison between these two algorithms is also done on the basis of the percentage of correctly classified instances of different attack categories present in both the datasets as well as the time they take to build their classification models.Overall J48 is a better classifier compared to Naïve Bayes on both the datasets but it is slow in building the classification model.
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Comparative Performance Analysis between nRF24L01+ and XBEE ZB Module Based Wireless Ad-hoc Networks
Статья научная
Among the common wireless communication modules like Bluetooth and Wi-Fi, XBee modules are embedded solutions providing wireless communication standard with self-healing mesh networks, which has longer range than Bluetooth and lower power consumption than Wi-Fi. An alternative to the XBee radio modules is nRF24L01+ radio modules which are cheap and powerful, highly integrated, ultra-low power (ULP) 2Mbps RF transceiver ICs for the 2.4GHz ISM (Industrial, Scientific, and Medical) band. In this paper, performances of nRF24L01+ modules have been analyzed and compared with that of XBee ZB modules in wireless ad-hoc networks. The performance metrics for the analytical study are - 1) Throughput measurement, 2) Mesh routing recovery time and 3) Power consumption. This work has revolved around an open source library released by the developer, tmrh20 which builds a complete TCP/IP suite on top of the nRF24L01+ modules.
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Comparative Performance Analysis of AODV and AODV-MIMC Routing Protocols for Mobile Ad hoc Networks
Статья научная
Bandwidth Scarcity is a major drawback in multi-hop ad hoc networks. When a single-interface single-channel (SISC) approach is used for both incoming and outgoing traffic the bandwidth contention between nodes along the path has occurred as well as throughput is degraded. This drawback is overwhelmed by using MIMC approach as well as some of the Quality of Service (QoS) requirements has been enhanced. In this paper we applied multi-interface muti-channel approach to AODV routing protocol, called AODV-MIMC routing protocol and its performance is compared with AODV routing protocol. The simulation results show the Network Life Time, Throughput, and Packet Delivery Ratio of AODV-MIMC routing protocol has been tremendously improved than the AODV routing protocol.
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Comparative Risk Assessment of Cyber Threats Based on Average and Fuzzy Sets Theory
Статья научная
Applied results of scientific analysis should be the key focus of modern security research. A comparative analysis of research results obtained using different methods, as an applied task, forms a broader basis for interpreting the results and substantiating the conclusions. A social survey and expert opinion research were conducted to implement the general concept of strategic analysis of cybersecurity in Ukraine. Using the method based on determining the average value in a certain set of estimates, as well as the method based on the theory of fuzzy sets, the risks of spreading certain cyber threats in Ukraine were assessed. The results were compared. Although the use of different measurement methods led to some differences in quantitative risk indicators, the comparative analysis of the ratio of the level of different cyber threats did not change significantly. At the same time, the fuzzy set method provided more flexible interpretation of the results to characterize cyber threats in terms of their upward or downward trend. In general, the combined approach to cyber threat risk assessment can become an important risk management tool, as it takes advantage of different methods and allows for a deeper understanding of the current situation and the formation of more informed management decisions.
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Comparative analysis of KNN algorithm using various normalization techniques
Статья научная
Classification is the technique of identifying and assigning individual quantities to a group or a set. In pattern recognition, K-Nearest Neighbors algorithm is a non-parametric method for classification and regression. The K-Nearest Neighbor (kNN) technique has been widely used in data mining and machine learning because it is simple yet very useful with distinguished performance. Classification is used to predict the labels of test data points after training sample data. Over the past few decades, researchers have proposed many classification methods, but still, KNN (K-Nearest Neighbor) is one of the most popular methods to classify the data set. The input consists of k closest examples in each space, the neighbors are picked up from a set of objects or objects having same properties or value, this can be considered as a training dataset. In this paper, we have used two normalization techniques to classify the IRIS Dataset and measure the accuracy of classification using Cross-Validation method using R-Programming. The two approaches considered in this paper are - Data with Z-Score Normalization and Data with Min-Max Normalization.
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Comparative analysis of classification algorithms for email spam detection
Статья научная
The increase in the use of email in every day transactions for a lot of businesses or general communication due to its cost effectiveness and efficiency has made emails vulnerable to attacks including spamming. Spam emails also called junk emails are unsolicited messages that are almost identical and sent to multiple recipients randomly. In this study, a performance analysis is done on some classification algorithms including: Bayesian Logistic Regression, Hidden Na?ve Bayes, Radial Basis Function (RBF) Network, Voted Perceptron, Lazy Bayesian Rule, Logit Boost, Rotation Forest, NNge, Logistic Model Tree, REP Tree, Na?ve Bayes, Multilayer Perceptron, Random Tree and J48. The performance of the algorithms were measured in terms of Accuracy, Precision, Recall, F-Measure, Root Mean Squared Error, Receiver Operator Characteristics Area and Root Relative Squared Error using WEKA data mining tool. To have a balanced view on the classification algorithms’ performance, no feature selection or performance boosting method was employed. The research showed that a number of classification algorithms exist that if properly explored through feature selection means will yield more accurate results for email classification. Rotation Forest is found to be the classifier that gives the best accuracy of 94.2%. Though none of the algorithms did not achieve 100% accuracy in sorting spam emails, Rotation Forest has shown a near degree to achieving most accurate result.
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Component importance measures based risk and reliability analysis of Vehicular Ad Hoc Networks
Статья научная
Recent year’s development in communication technologies have been able to deploy a whole new range of ad hoc networks of moving vehicles namely Vehicular Ad hoc Network (VANET). The key component of Intelligent Transportation Systems (ITS) is VANET only. The Vehicular communication systems is one of the critical complex infrastructure system of any nation. Thus, reliability i.e. having a low failure probability of such critical systems is the main concern of the academia and the industry. This paper primarily focuses on the reliability modelling of VANET. The main objective of the research is to address the issue of quantifying the importance of components in contributing to the reliability and maintenance of a VANET. Reliability Block diagrams (RBD)s have been modelled for the architecture of VANET. Out of various Component Importance Measures (CIM)s available in literature, Birnbaum measure, Improvement measure and Criticality Importance measures have been used to prioritize the system components. The research work is successful in identifying the most critical and the least critical component of the Vehicular Ad Hoc Network and thus provides a solution for the design improvement, maintenance and failure diagnosis.
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Comprehensive Methods of Evaluation of Distance Learning System Functioning
Статья научная
Given recent events, training during quarantine can only take place remotely. To ensure quality training, communication must be seamless. To do this, the network must function smoothly. The solution to this problem is functionally stable networks that allow uninterrupted transmission of information due to redundancy. An important issue is the definition of redundancy. To solve this problem, the article considers the method of synthesis of the structure of the distance learning system. The method of synthesis of network structure used for providing distance learning by the criterion of maximum functional stability on the basis of the introduction of correcting communication lines is offered. With this method, you can develop tools for self-recovery of distributed software, taking into account the characteristics of disparate computer resources through the use of redundancy. This will allow you to develop functionally stable software systems, significantly reduce the recovery time of such systems after or in the event of possible failures. To increase the efficiency of the developed method, the mathematical model of the hyper network based on two hypergraphs was improved, which allows taking into account different requirements for the quality of the network.
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Comprehensive Methods of Evaluation of Efficiency of Distance Learning System Functioning
Статья научная
The current pace of development of information technology has created the preconditions for the emergence of a wide range of tools for providing educational services using distance learning technologies. This is confirmed by the intensification of the use of distance learning systems in the conditions of sanitary and epidemiological restrictions and the need for acute cost savings. The existing scientific and methodological apparatus for studying the quality of functioning of distance learning systems is mostly based on approaches to separate assessment of the effectiveness of their elements and the relevant quality indicators. This limits the ability to take into account important factors in the decision-making process and requires comprehensive consideration of the contributions of relevant subsystems to the functioning of the distance learning system. In order to solve this problem, the article presents a comprehensive methodology for assessing the effectiveness of distance learning system, based on methods of probability theory and hierarchy analysis and describes the patterns of influence on the effectiveness of distance learning system of importance and contributions of its subsystems. Comparative analysis of the data obtained by monitoring and forecasting performance indicators based on the proposed method, shows an increase in the reliability of the assessment within 15-18%, which in contrast to the existing reduction of standard deviation of performance indicators by an average of 26% and ensures the adequacy of the results within certain assumptions and hypotheses. In such conditions, the choice of an appropriate option for the construction of the DN system is ensured by the reliability of the forecast of the results of its operation in the range of 82-85%, which is high enough to make appropriate decisions. The value of this study lies in the possibility of using the tested scientific and methodological apparatus in forecasting the outcome of the system and saving material, financial and human resources in the process of implementing the relevant recommendations in practice. This fact makes it possible to eliminate limitations in the practice of building distance learning systems and creates a new opportunity to cover a wider range of factors that affect the quality of operation.The application of this technique makes it possible to predict the results of the joint operation of the relevant subsystems of the distance learning system, taking into account their contribution to the overall result.
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Comprehensive Study of Selective Forwarding Attack in Wireless Sensor Networks
Статья научная
Sensor networks are becoming closer towards wide-spread deployment so security issues become a vital concern. Selective forwarding attack is one of the harmful attacks against sensor networks and can affect the whole sensor network communication. The variety of defense approaches against selective forwarding attack is overwhelming. In this paper we have described all the existing defensive schemes according to our best knowledge against this attack along with their drawbacks, thus providing researchers a better understanding of the attack and current solution space. This paper also classifies proposed schemes according to their nature and defense. Nature of scheme classifies into Distributed and Centralized. Defense of scheme classifies into detection and prevention.
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Статья научная
The use of wireless sensor networks has been increasing tremendously in the past decades mainly because of its applications in military, medicine, under water survey and various other fields. Depending on the applications the sensor nodes are placed in different areas and the data sensed will be sent to the base station. The process of transmitting and receiving data sensed by the sensor nodes continues till the sensors have battery life. This leads to generate data redundancy and reduces efficiency of the network. In order to overcome the limitations faced by the wireless sensor networks, the fusion of data known as data aggregation is introduced. In data aggregation, the data sensed by the various nodes are aggregated and sent to the base station as a single data packet. In this paper, a brief review on various data aggregation methods, challenges and issues are addressed. In addition to this, performance parameters of various data fusion methods to measure the efficiency of the network are discussed. The design of single aggregator models are easy compared to the multiple aggregator models. However, the security to most of the data fusion schemes is provided by using message authentication code. It also uses public keys and symmetric to achieve end to end or hop by hop encryptions.
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