Pub Date : 2020-02-16DOI: 10.1109/IACS.2016.7476111
N. Benletaief, H. Rezig, A. Bouallègue
This paper investigates a reconciliation method in order to establish an errorless secret key in a QKD protocol. Classical key distribution protocols are no longer unconditionally secure because computational complexity of mathematical problems forced hardships. In this context, QKD protocols offer a highest level of security because they are based on the quantum laws of physics. But, the protocol performances can be lowered by multiples errors. It appears clearly that reconciliation should be performed in such a situation in order to remove the errors as for the legitimate partners. The proposed method accomplishes reconciliation by using QTC in the special problem of side-information source coding ("Slepian-Wolf" coding model). Our theoretical hypothesis are sustained by experimental results that confirm the advantage of our method in resolving reconciliation problem compared to a recent related work. Indeed, the integration of our method generates an important progess in security and a large decrease of the QBER. The gain is obtained with a reasonable complexity increase. Also, the novelty of our work is that it tested the reconciliation method on a real photonic system under VPItransmissionMaker.
{"title":"Experimental study and praticai realization of a reconciliation method for quantum key distribution system","authors":"N. Benletaief, H. Rezig, A. Bouallègue","doi":"10.1109/IACS.2016.7476111","DOIUrl":"https://doi.org/10.1109/IACS.2016.7476111","url":null,"abstract":"This paper investigates a reconciliation method in order to establish an errorless secret key in a QKD protocol. Classical key distribution protocols are no longer unconditionally secure because computational complexity of mathematical problems forced hardships. In this context, QKD protocols offer a highest level of security because they are based on the quantum laws of physics. But, the protocol performances can be lowered by multiples errors. It appears clearly that reconciliation should be performed in such a situation in order to remove the errors as for the legitimate partners. The proposed method accomplishes reconciliation by using QTC in the special problem of side-information source coding (\"Slepian-Wolf\" coding model). Our theoretical hypothesis are sustained by experimental results that confirm the advantage of our method in resolving reconciliation problem compared to a recent related work. Indeed, the integration of our method generates an important progess in security and a large decrease of the QBER. The gain is obtained with a reasonable complexity increase. Also, the novelty of our work is that it tested the reconciliation method on a real photonic system under VPItransmissionMaker.","PeriodicalId":6579,"journal":{"name":"2016 7th International Conference on Information and Communication Systems (ICICS)","volume":"1 1","pages":"201-206"},"PeriodicalIF":0.0,"publicationDate":"2020-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90844140","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}
Pub Date : 2016-05-23DOI: 10.1109/IACS.2016.7476080
Ramzi Alqrainy, Sherenaz W. Al-Haj Baddar
In this paper, we introduce the fault-tolerant Distributed Analytics System (DAS) for analyzing big data collected from search engines in Arabic. This system consists of three main subsystems: Logging and Archiving Subsystem (LAS), Analytics Subsystem (AS), and a User Interface (UI). We used the data provided by opensooq.com, an online market with Arabic content, and compiled four datasets with sizes: 50 Million, 100 Million, 150 Million, and 200 Million events, in order to assess DAS. The experiments showed that DAS outperformed its sequential counterpart at datasets of 100 Million events and more, with the best speedup being 3.5 at 200 Million events. Additionally, DAS outperformed the well-known analytics system ElasticSearch (ES) in terms of response time for input sizes of 70 Million events and more, as the time per request achieved by DAS was 21% faster than ES's time. Moreover, DAS turned out to be more energy-efficient in terms of CPU utilization, as ES's CPU utilization was 2.4 times more than DAS's utilization, on average.
{"title":"DAS: Distributed analytics system for Arabic search engines","authors":"Ramzi Alqrainy, Sherenaz W. Al-Haj Baddar","doi":"10.1109/IACS.2016.7476080","DOIUrl":"https://doi.org/10.1109/IACS.2016.7476080","url":null,"abstract":"In this paper, we introduce the fault-tolerant Distributed Analytics System (DAS) for analyzing big data collected from search engines in Arabic. This system consists of three main subsystems: Logging and Archiving Subsystem (LAS), Analytics Subsystem (AS), and a User Interface (UI). We used the data provided by opensooq.com, an online market with Arabic content, and compiled four datasets with sizes: 50 Million, 100 Million, 150 Million, and 200 Million events, in order to assess DAS. The experiments showed that DAS outperformed its sequential counterpart at datasets of 100 Million events and more, with the best speedup being 3.5 at 200 Million events. Additionally, DAS outperformed the well-known analytics system ElasticSearch (ES) in terms of response time for input sizes of 70 Million events and more, as the time per request achieved by DAS was 21% faster than ES's time. Moreover, DAS turned out to be more energy-efficient in terms of CPU utilization, as ES's CPU utilization was 2.4 times more than DAS's utilization, on average.","PeriodicalId":6579,"journal":{"name":"2016 7th International Conference on Information and Communication Systems (ICICS)","volume":"73 1","pages":"20-26"},"PeriodicalIF":0.0,"publicationDate":"2016-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85812836","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}
Pub Date : 2016-04-05DOI: 10.1109/IACS.2016.7476072
M. A. Abou-Of, Ahmed Taha, Amr Sedky
Microprocessor architecture and its hardware implementation have a great influence on computer performance, power consumption, and energy efficiency. Nowadays, energy efficiency is a key point of Green Computing. However improving the performance by rising the CPU clock rate usually increases both the power and the energy consumptions. In this paper, we formulate experiments to study the relation between the CPU execution time, the power consumption, and the dissipated energy over a 0.2 GHz to 1.7 GHz range of CPU frequencies. These experiments are implemented on battery-powered mobile systems, for specific Dynamic Voltage and Frequency Scaling (DVFS) settings, by executing custom-made and standard benchmark tools for Intel and ARM processors. We report the results of the experiments and we demonstrate that we can achieve a minimum energy consumption but with a limited performance improvement. On the other hand, the performance optimization always increases the power. So other design factors, rather than clock speed, have to be considered for a low-power achievement.
{"title":"Trade-off between low power and energy efficiency in benchmarking","authors":"M. A. Abou-Of, Ahmed Taha, Amr Sedky","doi":"10.1109/IACS.2016.7476072","DOIUrl":"https://doi.org/10.1109/IACS.2016.7476072","url":null,"abstract":"Microprocessor architecture and its hardware implementation have a great influence on computer performance, power consumption, and energy efficiency. Nowadays, energy efficiency is a key point of Green Computing. However improving the performance by rising the CPU clock rate usually increases both the power and the energy consumptions. In this paper, we formulate experiments to study the relation between the CPU execution time, the power consumption, and the dissipated energy over a 0.2 GHz to 1.7 GHz range of CPU frequencies. These experiments are implemented on battery-powered mobile systems, for specific Dynamic Voltage and Frequency Scaling (DVFS) settings, by executing custom-made and standard benchmark tools for Intel and ARM processors. We report the results of the experiments and we demonstrate that we can achieve a minimum energy consumption but with a limited performance improvement. On the other hand, the performance optimization always increases the power. So other design factors, rather than clock speed, have to be considered for a low-power achievement.","PeriodicalId":6579,"journal":{"name":"2016 7th International Conference on Information and Communication Systems (ICICS)","volume":"11 1","pages":"322-326"},"PeriodicalIF":0.0,"publicationDate":"2016-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75874997","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}
Pub Date : 2016-04-05DOI: 10.1109/IACS.2016.7476098
R. Duwairi, Mosab Alfaqeh, Mohammad Wardat, Areen Alrabadi
This paper has used supervised learning to assign sentiment or polarity labels to tweets written in Arabizi. Arabizi is a form of writing Arabic text which relies on using Latin letters rather than Arabic letters. This form of writing is common with the Arab youth. A rule-based converter was designed and applied on the tweets to convert them from Arabizi to Arabic. Subsequently, the resultant tweets were annotated with their respective sentiment labels using crowdsourcing. This ArabiziDataset consists of 3206 tweets. Results obtained by this work reveal that SVM accuracies are higher than Naive Bayes accuracies. Secondly, removal of stopwords and mapping emoticons to their corresponding words did not greatly improve the accuracies for Arabizi data. Thirdly, eliminating neutral tweets at early stage in the classification improves Precision for both Naive Bayes and SVM. However, Recall values fluctuated, sometimes they got improved; on other times they did not improve.
{"title":"Sentiment analysis for Arabizi text","authors":"R. Duwairi, Mosab Alfaqeh, Mohammad Wardat, Areen Alrabadi","doi":"10.1109/IACS.2016.7476098","DOIUrl":"https://doi.org/10.1109/IACS.2016.7476098","url":null,"abstract":"This paper has used supervised learning to assign sentiment or polarity labels to tweets written in Arabizi. Arabizi is a form of writing Arabic text which relies on using Latin letters rather than Arabic letters. This form of writing is common with the Arab youth. A rule-based converter was designed and applied on the tweets to convert them from Arabizi to Arabic. Subsequently, the resultant tweets were annotated with their respective sentiment labels using crowdsourcing. This ArabiziDataset consists of 3206 tweets. Results obtained by this work reveal that SVM accuracies are higher than Naive Bayes accuracies. Secondly, removal of stopwords and mapping emoticons to their corresponding words did not greatly improve the accuracies for Arabizi data. Thirdly, eliminating neutral tweets at early stage in the classification improves Precision for both Naive Bayes and SVM. However, Recall values fluctuated, sometimes they got improved; on other times they did not improve.","PeriodicalId":6579,"journal":{"name":"2016 7th International Conference on Information and Communication Systems (ICICS)","volume":"105 1","pages":"127-132"},"PeriodicalIF":0.0,"publicationDate":"2016-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77733289","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}
Pub Date : 2016-04-05DOI: 10.1109/IACS.2016.7476096
Hatoon S. AlSagri, M. Ykhlef
Online social networks are being a powerful platform for the spread of negative emotion contagion which is affecting users from different perspectives i.e. psychology, economics, marketing and neuroscience. Online social networks have huge amount of data and knowledge that need to be studied through the use of data mining techniques. This paper focuses on presenting a new framework for analyzing and detracting negative emotional contagion through the use of clustering for detecting the community where the negative emotions may spread. Also, classification of nodes in the network is used to analyze the negativity in the nodes to help decide on the best treatment. Moreover, Prominent Actors (PAs) in the network must be determined to help in the treatment. Finally, through the use of recommender system and positive contagion the best treatment will be introduced. This framework is important to find the negative emotional contagion in different online communities and try to cure it or immunize the community against it.
{"title":"A framework for analyzing and detracting negative emotional contagion in online social networks","authors":"Hatoon S. AlSagri, M. Ykhlef","doi":"10.1109/IACS.2016.7476096","DOIUrl":"https://doi.org/10.1109/IACS.2016.7476096","url":null,"abstract":"Online social networks are being a powerful platform for the spread of negative emotion contagion which is affecting users from different perspectives i.e. psychology, economics, marketing and neuroscience. Online social networks have huge amount of data and knowledge that need to be studied through the use of data mining techniques. This paper focuses on presenting a new framework for analyzing and detracting negative emotional contagion through the use of clustering for detecting the community where the negative emotions may spread. Also, classification of nodes in the network is used to analyze the negativity in the nodes to help decide on the best treatment. Moreover, Prominent Actors (PAs) in the network must be determined to help in the treatment. Finally, through the use of recommender system and positive contagion the best treatment will be introduced. This framework is important to find the negative emotional contagion in different online communities and try to cure it or immunize the community against it.","PeriodicalId":6579,"journal":{"name":"2016 7th International Conference on Information and Communication Systems (ICICS)","volume":"137 1","pages":"115-120"},"PeriodicalIF":0.0,"publicationDate":"2016-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78510583","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}
Pub Date : 2016-04-05DOI: 10.1109/IACS.2016.7476100
M. Al-Khawaldeh, I. Al-Naimi, Xi Chen, P. Moore
The wide availability of services and devices within contemporary smart home environments make their management a challenging and rewarding task. Maintaining complex smart home systems throughout their lifecycle entails considerable resources and effort. These challenges have stimulated the need for dynamic auto-configurable services amongst such distributed systems. Although significant research has been directed towards achieving auto-configuration, none of the existing solutions is sufficient to achieve auto-configuration within smart home environments. This research aims to devise methods to automate the activities associated with customised service delivery for dynamic home environments by exploiting recent advances in the field of ubiquitous robotics and Semantic Web technologies. It introduces a novel approach called the Knowledge-based Auto-configuration Ubiquitous Robotics for Smart Home Environments, which utilises the Sobot to achieve auto-configuration of the system. A proof-of-concept testbed has been designed, implemented and validated via several case studies.
{"title":"Ubiquitous robotics for knowledge-based auto-configuration system within smart home environment","authors":"M. Al-Khawaldeh, I. Al-Naimi, Xi Chen, P. Moore","doi":"10.1109/IACS.2016.7476100","DOIUrl":"https://doi.org/10.1109/IACS.2016.7476100","url":null,"abstract":"The wide availability of services and devices within contemporary smart home environments make their management a challenging and rewarding task. Maintaining complex smart home systems throughout their lifecycle entails considerable resources and effort. These challenges have stimulated the need for dynamic auto-configurable services amongst such distributed systems. Although significant research has been directed towards achieving auto-configuration, none of the existing solutions is sufficient to achieve auto-configuration within smart home environments. This research aims to devise methods to automate the activities associated with customised service delivery for dynamic home environments by exploiting recent advances in the field of ubiquitous robotics and Semantic Web technologies. It introduces a novel approach called the Knowledge-based Auto-configuration Ubiquitous Robotics for Smart Home Environments, which utilises the Sobot to achieve auto-configuration of the system. A proof-of-concept testbed has been designed, implemented and validated via several case studies.","PeriodicalId":6579,"journal":{"name":"2016 7th International Conference on Information and Communication Systems (ICICS)","volume":"62 1","pages":"139-144"},"PeriodicalIF":0.0,"publicationDate":"2016-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83995282","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}
Pub Date : 2016-04-05DOI: 10.1109/IACS.2016.7476083
M. Allaymoun, Stefan Trausan-Matu
Chat is considered one of the most important and popular tools that are widely used in collaborative processes. Although various applications are used in Computer-Supported Collaborative Learning (CSCL), only few applications can help teachers in assessing the chats produced by learners. The fact that chats are rarely used in the official educational context may be explained by the difficulty of their grading. To find a solution for this problem, this paper presents a model that is assumed to enable teachers in assessing chats semi-automatically. It also includes the results of the analysis of three chats in the form of statistics and graphics, which can help teachers in easily assessing. Therefore, this model served the analysis of the contents of the chats, giving an example of how to assess the collaborative and individual participations. These conversations were conducted between a group of learners who were discussing predefined subjects in educational sessions. Moreover, the proposed model is based on assessing individual participations through identifying the most important threads discussed by each participant in the chat, relying on Mikhail Bakhtin's dialogism theory and Stefan Trausan-Matu's polyphonic model. The model used an effective way to find associative relationships among the important threads discussed by students and the rhetorical structures, considering linking cue phrases (`but', `therefore', `and', `or', ...). Starting from it, collaboration is assessed by studying the relations resulted from linking the important threads using cue phrases.
{"title":"Analysis of collaboration in CSCL chat using rhetorical schemas","authors":"M. Allaymoun, Stefan Trausan-Matu","doi":"10.1109/IACS.2016.7476083","DOIUrl":"https://doi.org/10.1109/IACS.2016.7476083","url":null,"abstract":"Chat is considered one of the most important and popular tools that are widely used in collaborative processes. Although various applications are used in Computer-Supported Collaborative Learning (CSCL), only few applications can help teachers in assessing the chats produced by learners. The fact that chats are rarely used in the official educational context may be explained by the difficulty of their grading. To find a solution for this problem, this paper presents a model that is assumed to enable teachers in assessing chats semi-automatically. It also includes the results of the analysis of three chats in the form of statistics and graphics, which can help teachers in easily assessing. Therefore, this model served the analysis of the contents of the chats, giving an example of how to assess the collaborative and individual participations. These conversations were conducted between a group of learners who were discussing predefined subjects in educational sessions. Moreover, the proposed model is based on assessing individual participations through identifying the most important threads discussed by each participant in the chat, relying on Mikhail Bakhtin's dialogism theory and Stefan Trausan-Matu's polyphonic model. The model used an effective way to find associative relationships among the important threads discussed by students and the rhetorical structures, considering linking cue phrases (`but', `therefore', `and', `or', ...). Starting from it, collaboration is assessed by studying the relations resulted from linking the important threads using cue phrases.","PeriodicalId":6579,"journal":{"name":"2016 7th International Conference on Information and Communication Systems (ICICS)","volume":"198 1","pages":"39-44"},"PeriodicalIF":0.0,"publicationDate":"2016-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88138591","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}
Pub Date : 2016-04-05DOI: 10.1109/IACS.2016.7476079
P. Mukherjee, B. Jansen
We evaluate the change in social media postings of Super Bowl 2015 on three social media platforms (Twitter, Instagram and Tumblr) for three categories (commercials, musicals and game) during three phrases (Pre, During, and Post). We perform statistical analysis on more than 3,000,000, 800,000 and 50,000 social media posts from Twitter, Instagram and Tumblr, respectively, identifying significant differences among categories. We identify the predominant category of conversations across the three social networks in phases. Findings show the volume of posts in the During phase is surprisingly less than the Pre and Post phases; however, the hourly mean in the During phase is considerably higher than that in other two phases. We then explore the significance of phase-wide change in second screen conversations across the Super Bowl categories for all three social media platforms. We identify the game category is prominent in Twitter, and Instagram for all phases, but not Tumblr. There are dominant peaks for musicals and/or commercials relative to game in all three phases. No category is predominant on Twitter in During phase. These results are important in identifying the interplay of technology has on social interactions for information sharing via second screen especially across disparate social platforms.
{"title":"Second screen interaction analysis for IRL events: Phase-category investigation of the super bowl 2015 social soundtrack","authors":"P. Mukherjee, B. Jansen","doi":"10.1109/IACS.2016.7476079","DOIUrl":"https://doi.org/10.1109/IACS.2016.7476079","url":null,"abstract":"We evaluate the change in social media postings of Super Bowl 2015 on three social media platforms (Twitter, Instagram and Tumblr) for three categories (commercials, musicals and game) during three phrases (Pre, During, and Post). We perform statistical analysis on more than 3,000,000, 800,000 and 50,000 social media posts from Twitter, Instagram and Tumblr, respectively, identifying significant differences among categories. We identify the predominant category of conversations across the three social networks in phases. Findings show the volume of posts in the During phase is surprisingly less than the Pre and Post phases; however, the hourly mean in the During phase is considerably higher than that in other two phases. We then explore the significance of phase-wide change in second screen conversations across the Super Bowl categories for all three social media platforms. We identify the game category is prominent in Twitter, and Instagram for all phases, but not Tumblr. There are dominant peaks for musicals and/or commercials relative to game in all three phases. No category is predominant on Twitter in During phase. These results are important in identifying the interplay of technology has on social interactions for information sharing via second screen especially across disparate social platforms.","PeriodicalId":6579,"journal":{"name":"2016 7th International Conference on Information and Communication Systems (ICICS)","volume":"47 1","pages":"13-19"},"PeriodicalIF":0.0,"publicationDate":"2016-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76879865","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}
Pub Date : 2016-04-05DOI: 10.1109/IACS.2016.7476097
Abdullateef Rabab'ah, M. Al-Ayyoub, Y. Jararweh, M. Al-Kabi
Social micro-blogging systems like Twitter are used today as a platform that enables its users to write down about different topics. One important aspect of such human interactions is the existence of debate and disagreement. The most heated debates are found on controversial topics. Detecting such topics can be very beneficial in understanding the behavior of online social networks users and the dynamics of their interactions. Such an understanding leads to better ways of handling and predicting how the "online crowds" will act. Several approaches have been proposed for detecting controversy in online communication. Some of them represent the interactions in the form of graphs and study their properties in order to determine whether the topic of interaction is controversial or not. Other approaches rely on the content of the exchanged messages. In this study, we focus on the former approach in identifying the controversy level of the trending topics on Twitter. Unlike many previous works, we do not limit ourselves to a certain domain. Moreover, we focus on social content written in Arabic about hot events occurring in the Middle East. To the best of our knowledge, ours is the first work to undertake this approach in studying controversy in general topics written in Arabic. We collect a large dataset of tweets on different trending topics from different domains. We apply several approaches for controversy detection and compare their outcomes to determine which one is the most consistent measure.
{"title":"Measuring the controversy level of Arabic trending topics on Twitter","authors":"Abdullateef Rabab'ah, M. Al-Ayyoub, Y. Jararweh, M. Al-Kabi","doi":"10.1109/IACS.2016.7476097","DOIUrl":"https://doi.org/10.1109/IACS.2016.7476097","url":null,"abstract":"Social micro-blogging systems like Twitter are used today as a platform that enables its users to write down about different topics. One important aspect of such human interactions is the existence of debate and disagreement. The most heated debates are found on controversial topics. Detecting such topics can be very beneficial in understanding the behavior of online social networks users and the dynamics of their interactions. Such an understanding leads to better ways of handling and predicting how the \"online crowds\" will act. Several approaches have been proposed for detecting controversy in online communication. Some of them represent the interactions in the form of graphs and study their properties in order to determine whether the topic of interaction is controversial or not. Other approaches rely on the content of the exchanged messages. In this study, we focus on the former approach in identifying the controversy level of the trending topics on Twitter. Unlike many previous works, we do not limit ourselves to a certain domain. Moreover, we focus on social content written in Arabic about hot events occurring in the Middle East. To the best of our knowledge, ours is the first work to undertake this approach in studying controversy in general topics written in Arabic. We collect a large dataset of tweets on different trending topics from different domains. We apply several approaches for controversy detection and compare their outcomes to determine which one is the most consistent measure.","PeriodicalId":6579,"journal":{"name":"2016 7th International Conference on Information and Communication Systems (ICICS)","volume":"128 1","pages":"121-126"},"PeriodicalIF":0.0,"publicationDate":"2016-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76958058","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}
Pub Date : 2016-04-05DOI: 10.1109/IACS.2016.7476116
Raad S. Al-Qassas, Malik Qasaimeh, Hassan Al-Nouri
In this paper, we propose a new DES variant named Hashed Data Encryption Standard (or HDES for short), with an objective to enhance the limitation of static S-boxes arrangement in DES. The proposed HDES combines several techniques and components into one new algorithm to enhance the original DES. The HDES uses a hash function at the beginning of each block encryption process to produce a fingerprint for the plaintext, which will be used later to produce a seed that will coordinate the generation of the S-boxes during the sixteen rounds of the encryption process. The performance of the HDES has been evaluated and compared against DES and DESX. The evaluation has been conducted using the cipher data randomness and the encryption time.
{"title":"A fingerprint featured data encryption algorithm","authors":"Raad S. Al-Qassas, Malik Qasaimeh, Hassan Al-Nouri","doi":"10.1109/IACS.2016.7476116","DOIUrl":"https://doi.org/10.1109/IACS.2016.7476116","url":null,"abstract":"In this paper, we propose a new DES variant named Hashed Data Encryption Standard (or HDES for short), with an objective to enhance the limitation of static S-boxes arrangement in DES. The proposed HDES combines several techniques and components into one new algorithm to enhance the original DES. The HDES uses a hash function at the beginning of each block encryption process to produce a fingerprint for the plaintext, which will be used later to produce a seed that will coordinate the generation of the S-boxes during the sixteen rounds of the encryption process. The performance of the HDES has been evaluated and compared against DES and DESX. The evaluation has been conducted using the cipher data randomness and the encryption time.","PeriodicalId":6579,"journal":{"name":"2016 7th International Conference on Information and Communication Systems (ICICS)","volume":"24 1","pages":"227-232"},"PeriodicalIF":0.0,"publicationDate":"2016-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82163212","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}
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