2021 12th International Conference on Information and Communication Systems (ICICS)最新文献_第3页

A Secure Switch Migration Scheduling based on Prediction for Load Balancing in SDN 基于SDN负载均衡预测的安全交换机迁移调度

2021 12th International Conference on Information and Communication Systems (ICICS) Pub Date : 2021-05-24 DOI: 10.1109/ICICS52457.2021.9464560

Rawaa Al-quraan, A. Alma'aitah

{"title":"A Secure Switch Migration Scheduling based on Prediction for Load Balancing in SDN","authors":"Rawaa Al-quraan, A. Alma'aitah","doi":"10.1109/ICICS52457.2021.9464560","DOIUrl":"https://doi.org/10.1109/ICICS52457.2021.9464560","url":null,"abstract":"The control plane of Software Defined Networking (SDN) Featured in the distributed architecture to achieve the scalability, thus the load is divided between the controllers. each controller must have the appropriate load. so, the control plane needs an accurate and beneficial design to meet the load balancing between the controllers. Thus, the switch migration is the most proposed solution for load balancing in SDN. Most of the proposed algorithms are implemented to produce efficient switch migration. In this paper, we propose a secure switch migration scheduling algorithm to enhance the load balancing and achieve the security between the switch and the destination controller. Our algorithm uses an ARIMA prediction approach to predict the load of the controllers and then according to the prediction, the switch migration operation is performed. It reduces the load for the controller which has a very large load by offloading it quickly and it makes the open-flow switch distinguishes if the destination controller is malicious or not. The results show that our algorithm enhances the load balancing compared to [10] and it confirms the security between the switch and the destination controller.","PeriodicalId":421803,"journal":{"name":"2021 12th International Conference on Information and Communication Systems (ICICS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129499457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Team Wa’ed Al-Shrida at the Mowjaz Multi-Topic Labelling Task Wa 'ed Al-Shrida团队在Mowjaz多主题标签任务

2021 12th International Conference on Information and Communication Systems (ICICS) Pub Date : 2021-05-24 DOI: 10.1109/ICICS52457.2021.9464574

Wa’ed Al-Shrida

引用次数: 0

URL Phishing Detection using Machine Learning Techniques based on URLs Lexical Analysis 基于URL词法分析的机器学习技术的URL钓鱼检测

2021 12th International Conference on Information and Communication Systems (ICICS) Pub Date : 2021-05-24 DOI: 10.1109/ICICS52457.2021.9464539

Mohammed AbuTaha, M. Ababneh, Khaled W. Mahmoud, Sherenaz W. Al-Haj Baddar

{"title":"URL Phishing Detection using Machine Learning Techniques based on URLs Lexical Analysis","authors":"Mohammed AbuTaha, M. Ababneh, Khaled W. Mahmoud, Sherenaz W. Al-Haj Baddar","doi":"10.1109/ICICS52457.2021.9464539","DOIUrl":"https://doi.org/10.1109/ICICS52457.2021.9464539","url":null,"abstract":"Phishing URLs mainly target individuals and/or organizations through social engineering attacks by exploiting the humans’ weaknesses in information security awareness. These URLs lure online users to access fake websites, and harvest their confidential information, such as debit/credit card numbers and other sensitive information. In this work, we introduce a phishing detection technique based on URL lexical analysis and machine learning classifiers. The experiments were carried out on a dataset that originally contained 1056937 labeled URLs (phishing and legitimate). This dataset was processed to generate 22 different features that were reduced further to a smaller set using different features reduction techniques. Random Forest, Gradient Boosting, Neural Network and Support Vector Machine (SVM) classifiers were all evaluated, and results show the superiority of SVMs, which achieved the highest accuracy in detecting the analyzed URLs with a rate of 99.89%. Our approach can be incorporated within add-on/middleware features in Internet browsers for alerting online users whenever they try to access a phishing website using only its URL.","PeriodicalId":421803,"journal":{"name":"2021 12th International Conference on Information and Communication Systems (ICICS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131293324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Multi-Topic Labelling Classification Based on LSTM 基于LSTM的多主题标签分类

2021 12th International Conference on Information and Communication Systems (ICICS) Pub Date : 2021-05-24 DOI: 10.1109/ICICS52457.2021.9464531

Duha AlBatayha

引用次数: 4

Credit Card Fraud Detection Based on Deep Neural Network Approach 基于深度神经网络的信用卡欺诈检测

2021 12th International Conference on Information and Communication Systems (ICICS) Pub Date : 2021-05-24 DOI: 10.1109/ICICS52457.2021.9464555

Khalid Alkhatib, Ahmad Al-Aiad, Mothanna Almahmoud, Omar N. Elayan

引用次数: 7

Alive+: A Private Cloud Messaging System for Android Devices Alive+: Android设备的私有云消息系统

2021 12th International Conference on Information and Communication Systems (ICICS) Pub Date : 2021-05-24 DOI: 10.1109/ICICS52457.2021.9464542

Amjad Bashayreh, Nida’a Alsalman, A. Alzu’bi

{"title":"Alive+: A Private Cloud Messaging System for Android Devices","authors":"Amjad Bashayreh, Nida’a Alsalman, A. Alzu’bi","doi":"10.1109/ICICS52457.2021.9464542","DOIUrl":"https://doi.org/10.1109/ICICS52457.2021.9464542","url":null,"abstract":"Conventional private messaging systems over the network often focus on the privacy problem but pay little attention to important performance qualities such as system reliability, scalability and fault tolerance. The existing systems usually meet the security requirements using verifiable shuffles to prevent a message loss or by generating an efficient noise across many servers using bloom filters. This paper introduces Alive+ system as a private cloud messaging to forward messages over the Android devices securely. Alive+ employs a cryptography scheme to guarantee the confidentiality of messaging process. Messages are encrypted and decrypted over the cloud server using AES algorithm and SHA-256 hash function to generate unique secret keys, thus strengthening Alive+ against possible network attacks. Alive+ is connected to a reliable cloud-based database designed to handle the user requests and communications efficiently. We evaluate the performance of Alive+ in terms of reliability, latency, and scalability under various scenarios and settings. The performance of Alive+ is also evaluated in terms of fault tolerance, CPU utilization, memory usage, and network traffic. The experimental results show that Alive+ is secure, reliable, and error-tolerant with high scalability levels, thereby serving a large number of users simultaneously.","PeriodicalId":421803,"journal":{"name":"2021 12th International Conference on Information and Communication Systems (ICICS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134558862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Arabic Topic Labeling using Naïve Bayes (NB) 使用Naïve贝叶斯(NB)的阿拉伯语主题标注

2021 12th International Conference on Information and Communication Systems (ICICS) Pub Date : 2021-05-24 DOI: 10.1109/ICICS52457.2021.9464537

Asseel S. Hourani

引用次数: 1

Sentiment Analysis Based on Deep Learning Methods for Explainable Recommendations with Reviews 基于深度学习方法的可解释推荐情感分析

2021 12th International Conference on Information and Communication Systems (ICICS) Pub Date : 2021-05-24 DOI: 10.1109/ICICS52457.2021.9464601

Hafed Zarzour, Bashar Al shboul, M. Al-Ayyoub, Y. Jararweh

{"title":"Sentiment Analysis Based on Deep Learning Methods for Explainable Recommendations with Reviews","authors":"Hafed Zarzour, Bashar Al shboul, M. Al-Ayyoub, Y. Jararweh","doi":"10.1109/ICICS52457.2021.9464601","DOIUrl":"https://doi.org/10.1109/ICICS52457.2021.9464601","url":null,"abstract":"Explainable recommendation systems have gained much attention in the last few years. Most of them use textual reviews to provide users with interpretability about why services or products are liked by users or recommended for them. Sentiment analysis has potential advantages to determine the attitudes of users in online communities using websites such as Twitter, Facebook, and YouTube. However, sentiment analysis of textual reviews in explainable recommendation systems seems to be a really challenging task. In this paper, we present a deep learning-based architecture for sentiment analysis to automatically predict the sentiment of reviews, which are considered as explanations of recommendations. It consists of two instances of the prediction model, one with the Long Short-Term Memory (LSTM) method and the other with the Gated Recurrent Unit (GRU) method. We evaluate their performance on one real-world dataset from Amazon and compare them with one state-of-the-art method. The experimental results show that our methods perform better than the baseline approach.","PeriodicalId":421803,"journal":{"name":"2021 12th International Conference on Information and Communication Systems (ICICS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115199752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

The Intention to Use E-wallet During Covid-19 Pandemic in Developing Country 新冠疫情期间发展中国家使用电子钱包的意向

2021 12th International Conference on Information and Communication Systems (ICICS) Pub Date : 2021-05-24 DOI: 10.1109/ICICS52457.2021.9464554

Hala Abushamleh, Narmeen Al-Hiyari, A. Qusef

引用次数: 5

A Probability Based Topology Control Algorithm For WSN-based-IoT 一种基于概率的无线网络物联网拓扑控制算法

2021 12th International Conference on Information and Communication Systems (ICICS) Pub Date : 2021-05-24 DOI: 10.1109/ICICS52457.2021.9464559

A. R. Yateem, A. Alma'aitah

引用次数: 1