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29,922 Article Results

A hybrid of CNN and LSTM methods for securing web application against cross-site scripting attack

10.11591/ijeecs.v21.i2.pp1022-1029
Raed Waheed Kadhim , Methaq Talib Gaata
Cross-site scripting (XSS) is today one of the biggest threatthat could targeting the Web application. Based on study published by the open web applications security project (OWASP), XSS vulnerability has been present among the TOP 10 Web application vulnerabilities.Still,an important security-related issue remains how to effectively protect web applications from XSS attacks.In first part of this paper, a method for detecting XSS attack was proposed by combining convolutional neural network (CNN) with long short term memories (LSTM), Initially, pre-processing was applied to XSS Data Set by decoding, generalization and tokanization, and then word2vec was applied to convert words into word vectors in XSS payloads. And then we use the combination CNN with LSTM to train and test word vectors to produce a model that can be used in a web application. Based on the obtaned results, it is observed that the proposed model achevied an excellent result with accuracy of 99.4%.
Volume: 21
Issue: 2
Page: 1022-1029
Publish at: 2021-02-01

Comparative investigation of 15 Level and 17 level cascaded h-bridge MLI with cross h-bridge MLI fed permanent magnet synchronous motor

10.11591/ijeecs.v21.i2.pp723-734
J. Srinivas Rao , Suresh Kumar Tummala , Narasimha Raju Kuthuri
Multilevel inverters offers eminent solutions to high voltage high power applications due to the association of several devices in a series configuration. In this paper, a comparative investigation of both 15 and 17 level cascaded h-bridge multi level inverter with cross h-bridge fed permanent magnet synchronous motor are presented by appropriate simulations and mathematical analysis. Comparative analysis includes Inverter output voltage and current, number of switching devices, stator current and speed of PMSM and total harmonic distortion levels. Limitation of several switching devices, which can afford high voltage in the inverter is the major problems raised in this study. The advantage of this analysis is to figure out the appropriate inverter that can be used for real time application by considering the factors via. Harmonic distortion, output voltage, current, number of switching devices etc. Validation of the analysis is processed through matlab/simulink platform.
Volume: 21
Issue: 2
Page: 723-734
Publish at: 2021-02-01

Dialogue state tracking accuracy improvement by distinguishing slot-value pairs and dialogue behaviour

10.11591/ijeecs.v21.i2.pp1057-1064
Khaldoon H. Alhussayni , Alexander Zamyatin , S. Eman Alshamery
Dialog state tracking (DST) plays a critical role in cycle life of a task-oriented dialogue system. DST represents the goals of the consumer at each step by dialogue and describes such objectives as a conceptual structure comprising slot-value pairs and dialogue actions that specifically improve the performance and effectiveness of dialogue systems. DST faces several challenges: diversity of linguistics, dynamic social context and the dissemination of the state of dialogue over candidate values both in slot values and in dialogue acts determined in ontology. In many turns during the dialogue, users indirectly refer to the previous utterances, and that produce a challenge to distinguishing and use of related dialogue history, Recent methods used and popular for that are ineffective. In this paper, we propose a dialogue historical context self-Attention framework for DST that recognizes relevant historical context by including previous user utterance beside current user utterances and previous system actions where specific slot-value piers variations and uses that together with weighted system utterance to outperform existing models by recognizing the related context and the relevance of a system utterance. For the evaluation of the proposed model the WoZ dataset was used. The implementation was attempted with the prior user utterance as a dialogue encoder and second by the additional score combined with all the candidate slot-value pairs in the context of previous user utterances and current utterances. The proposed model obtained 0.8 per cent better results than all state-of-the-art methods in the combined precision of the target, but this is not the turnaround challenge for the submission.
Volume: 21
Issue: 2
Page: 1057-1064
Publish at: 2021-02-01

Optimized architecture for SNOW 3G

10.11591/ijece.v11i1.pp545-557
N. B. Hulle , Prathiba B. , Sarika R. Khope , K. Anuradha , Yogini Borole , D. Kotambkar
SNOW 3G is a synchronous, word-oriented stream cipher used by the 3GPP standards as a confidentiality and integrity algorithms. It is used as first set in long term evolution (LTE) and as a second set in universal mobile telecommunications system (UMTS) networks. The cipher uses 128-bit key and 128 bit IV to produce 32-bit ciphertext. The paper presents two techniques for performance enhancement. The first technique uses novel CLA architecture to minimize the propagation delay of the 232 modulo adders. The second technique uses novel architecture for S-box to minimize the chip area. The presented work uses VHDL language for coding. The same is implemented on the FPGA device Virtex xc5vfx100e manufactured by Xilinx. The presented architecture achieved a maximum frequency of 254.9 MHz and throughput of 7.2235 Gbps.
Volume: 11
Issue: 1
Page: 545-557
Publish at: 2021-02-01

Parameters estimation of BLDC motor based on physical approach and weighted recursive least square algorithm

10.11591/ijece.v11i1.pp133-145
Rania Majdoubi , Lhoussaine Masmoudi , Mohammed Bakhti , Abderrahmane Elharif , Bouazza Jabri
Brushless DC motors (BLDCM) are widely used when high precision converters are required. Model based torque control schemes rely on a precise representation of their dynamics, which in turn expect reliable system parameters estimation. In this paper, we propose two procedures for BLDCM parameters identification used in an agriculture mobile robot’s wheel. The first one is based on the physical approach or equations using experimentation data to find the electrical and mechanical parameters of the BLDCM. The parameters are then used to elaborate the model of the motor established in Park’s reference frame. The second procedure is an online identification based on recursive least square algorithm. The procedure is implemented in a closed-loop scheme to guarantee the stability of the system, and it provide parameter matrices obtained by transforming electrical equations, established in Parks reference frame, and mechanical equation to discrete-time domain. From these matrices, and using well formulated intermediate variables, all desired parameters are deduced simultaneously. The identification procedures are being verified using simulation under Matlab-Simulink software.
Volume: 11
Issue: 1
Page: 133-145
Publish at: 2021-02-01

Design an expert system for students graduation projects in Iraq universities: Basrah University

10.11591/ijece.v11i1.pp602-610
Maysaa Abd Ulkareem Naser , Sajad Mohammed Hasen
A graduation project is a form or work that the study authority requests from the student to measure what he made during the study. Designed an expert system for students’ graduation projects at the University of Basrah for students who are obligated to submit a project that qualifies them to graduate from the university. The system works according to a set of requirements, the most important is first: The student's possession of a high rate that qualifies him for the project. Second: he must possess half of the skills required for the project provided that it includes at least one programming language example (c ++, java, PHP, c #, etc ...). The system has many features that help the Supervisors and Students Committee to manage students' projects efficiently. System is built as a web-based system, with access limited only to the university's local network.
Volume: 11
Issue: 1
Page: 602-610
Publish at: 2021-02-01

Secured node detection technique based on artificial neural network for wireless sensor network

10.11591/ijece.v11i1.pp536-544
Bassam Hasan , Sameer Alani , Mohammed Ayad Saad
The wireless sensor network is becoming the most popular network in the last recent years as it can measure the environmental conditions and send them to process purposes. Many vital challenges face the deployment of WSNs such as energy consumption and security issues. Various attacks could be subjects against WSNs and cause damage either in the stability of communication or in the destruction of the sensitive data. Thus, the demands of intrusion detection-based energy-efficient techniques rise dramatically as the network deployment becomes vast and complicated. Qualnet simulation is used to measure the performance of the networks. This paper aims to optimize the energy-based intrusion detection technique using the artificial neural network by using MATLAB Simulink. The results show how the optimized method based on the biological nervous systems improves intrusion detection in WSN. In addition to that, the unsecured nodes are affected the network performance negatively and trouble its behavior. The regress analysis for both methods detects the variations when all nodes are secured and when some are unsecured. Thus, Node detection based on packet delivery ratio and energy consumption could efficiently be implemented in an artificial neural network.
Volume: 11
Issue: 1
Page: 536-544
Publish at: 2021-02-01

Categorizing and measurement satellite image processing of fire in the forest greece using remote sensing

10.11591/ijeecs.v21.i2.pp846-853
Ali Abdul Wahhab Mohammed , Hussein Thary Khamees
This paper has been utilized satellite Sentinel-2A imagery, this satellite is a polar-orbiting, multispectral high-resolution to cover Athens city, Greece that located at latitude (37° 58′ 46″) N, (23° 42′ 58″) E.,the work aims to measurement and study the wildfires natural resourcesbefore and after fire break out that happenedin forests of Athens city in Greece for a year (2007, 2018) and analysis the damage caused by these wildfiresand their impact on environment  and soil  by categorize the satellite images for the interested region before and after wildfires for a year (2007) and  a year (2018) and Discuss techniques that compute the area covered of each class and lessen  or limit the rapidly spreading wildfires damage.The categorizing utilizing the moments with (K-Means) grouping algorithm in RS (remote sensing). And the categorizing results show five unique classes (water, trees, buildings without tree, buildings with tree, bare lands) where, it can be notice that the region secured by each class before and after wildfires and the changed pixels for all classes.The experimental resulted of categorizing technique shows that the good performance exactness with a good categorizing and result analysisa bout the harms resulted from the fires in the forest Greece for a years (2007 and 2018).
Volume: 21
Issue: 2
Page: 846-853
Publish at: 2021-02-01

Evaluation of load balancing algorithms on overlappiing wireless accesspoints

10.11591/ijeecs.v21.i2.pp895-902
Marion Olubunmi Adebiyi , Egbe Egbe Adeka , Florence A. Oladeji , Roseline Oluwaseun Ogundokun , Micheal Olaolu Arowolo , Ayodele Ariyo Adebiyi
Wireless networks came into the computing world replacing the costlier and more complex wired method of connecting numerous equipment in the same or different location via the use of cables. It provides the user devices a connection to one another and the greater internet via connections to access points. Generally, 802.11 access point products follow a default strongest signal first approach in selecting user devices or nodes to connect to the access point or overlapping access points. This standard does not make provisions for even distribution of load and hence the quality of service and the throughput in areas of congestion would be reduced. This article brings forward two algorithms used in load balancing and they include round-robin technique and the weighted round-robin technique to be used in the simulation of the distribution of the load amongst the access points with the results collated and compared to clearly show which algorithm is best suited to be used as a standard for access point load distribution.
Volume: 21
Issue: 2
Page: 895-902
Publish at: 2021-02-01

Contactless digital tachometer using microcontroller

10.11591/ijece.v11i1.pp293-299
R. Palanisamy , S. Vidyasagar , V. Kalyanasundaram , R. Sridhar
Tachometer is a device that used for counting or for the measuring purpose of the number of revolutions (that is the total number rotations made by the device in unit of measuring time) of an object in unit time. It is expressed in the unit of RPS or RPM, the model uses a set of infrared transducer receiver to count the RPM pulses, and the Arduino microcontroller is used for the implementation of the project. The individual pulses are counted by the microcontroller to give the final output of the RPM.
Volume: 11
Issue: 1
Page: 293-299
Publish at: 2021-02-01

Improving signal detection accuracy at FC of a CRN using machine learning and fuzzy rules

10.11591/ijeecs.v21.i2.pp1140-1150
Md Abul Kalam Azad , Anup Majumder , Jugal Krishna Das , Md Imdadul Islam
The performance of a cognitive radio network (CRN) mainly depends on the faithful signal detection at fusion center (FC). In this paper, the concept of weighted Fuzzy rule in Iris data classification, as well as, four machine learning techniques named fuzzy inference system (FIS), fuzzy c-means clustering (FCMC), support vector machine (SVM) and convolutional neural network (CNN) are applied in signal detection at FC taking signal-to-interference plus noise ratio of secondary users as parameter. The weighted Fuzzy rule gave the detection accuracy of 86.6%, which resembles the energy detection model of majority rule of FC; however, CNN gave an accuracy of 91.3% at the expense of more decision time. The FIS, FCMC and SVM gave some intermediate results; however, the combined method gave the best result compared to that of any individual technique.
Volume: 21
Issue: 2
Page: 1140-1150
Publish at: 2021-02-01

APMorph: finite-state transducer for Amazigh pronominal morphology

10.11591/ijece.v11i1.pp699-706
Rachid Ammari , Ahbib Zenkoua
Our work aims to present an amazigh pronominal morphological analyzer (APMorph) based on xerox’s finite-state transducer (XFST). Our system revolves around a large lexicon named “APlex” including the affixed pronoun to the noun and to the verb and the characteristics relating to each lemma. A set of rules are added to define the inflectional behavior and morphosyntactic links of each entry as well as the relationship between the different lexical units. The implementation and the evaluation of our approach will be detailed within this article. The use of XFST remains a relevant choice in the sense that this platform allows both analysis and generation. The robustness of our system makes it able to be integrated in other applications of natural language processing (NLP) especially spellchecking, machine translation, and machine learning. This paper presents a continuation of our previous works on the automatic processing of Amazigh nouns and verbs.
Volume: 11
Issue: 1
Page: 699-706
Publish at: 2021-02-01

IoT based implemented comparison analysis of two well-known network platforms for smart home automation

10.11591/ijece.v11i1.pp442-450
Sameer Alani , Sarmad Nozad Mahmood , Sarah Zaeead Attaallah , Haneen Sameer Mhmood , Zeena Abdulsattar Khudhur , Azzam Amer Dhannoon
The developments of the internet of things (IoT) technologies fascinated the universe and provided great opportunities to introduce these innovations in smart house networks. Smart home automation is highly required these days. Smart home automation is a collection of electronic devices connected to monitor and control in the market home appliance remotely. However, it is still needed to design a friendly and reliable system since the system mainly depends on the devices used and the environment of the network. NETPI and BLYNK are IoT frameworks used for hardware-agnostic with smartphones, websites, private clouds, system security, data mining, and deep learning. The results confirmed that NETPI provides flexibility to deal with several NODEMCU controllers in a single control framework. The proposed system shows its applicability in monitoring and controlling home appliances remotely.
Volume: 11
Issue: 1
Page: 442-450
Publish at: 2021-02-01

Fingerprint positioning of users devices in long term evolution cellular network using K nearest neighbour algorithm

10.11591/ijece.v11i1.pp528-535
Mohammed J. Alhasan , Sarmad Muneer Abdulhussein , Ali H. K. Khwayyir
The rapid exponential growth in wireless technologies and the need for public safety has led to increasing demand for location-based services. Terrestrial cellular networks can offer acceptable position estimation for users that can meet the statutory requirements set by the Federal Communications Commission in case of network-based positioning, for safety regulations. In this study, the proposed radio frequency pattern matching (RFPM) method is implemented and tested to determine a user’s location effectively. The RFPM method has been tested and validated in two different environment. The evaluations show remarkable results especially in the Micro cell scenario, at 67% of positioning error 15m and at 90% 31.78m for Micro cell scenario, with results of 75.66m at 67% and 141.4m at 90% for Macro cell scenario.
Volume: 11
Issue: 1
Page: 528-535
Publish at: 2021-02-01

Improved feature exctraction process to detect seizure using CHBMIT-dataset

10.11591/ijece.v11i1.pp827-843
Raveendra Kumar T. H. , C. K. Narayanappa
One of the most dangerous neurological disease, which is occupying worldwide, is epilepsy. Fraction of second nerves in the brain starts impulsion i.e. electrical discharge, which is higher than the normal pulsing. So many researches have done the investigation and proposed the numerous methodology. However, our methodology will give effective result in feature extraction. Moreover, we used numerous number of statistical moments features. Existing approaches are implemented on few statistical moments with respect to time and frequency. Our proposed system will give the way to find out the seizure-effected part of the brain very easily using TDS, FDS, Correlation and Graph presentation. The resultant value will give the huge difference between normal and seizure effected brain. It also explore the hidden features of the brain.
Volume: 11
Issue: 1
Page: 827-843
Publish at: 2021-02-01
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