Pub Date : 2015-12-01DOI: 10.1109/INTELCIS.2015.7397263
Abdullah M. Sheneamer, J. Kalita
If two fragments of source code are identical to each other, they are called code clones. Code clones introduce difficulties in software maintenance and cause bug propagation. Coarse-grained clone detectors have higher precision than fine-grained, but fine-grained detectors have higher recall than coarse-grained. In this paper, we present a hybrid clone detection technique that first uses a coarse-grained technique to analyze clones effectively to improve precision. Subsequently, we use a fine-grained detector to obtain additional information about the clones and to improve recall. Our method detects Type-1 and Type-2 clones using hash values for blocks, and gapped code clones (Type-3) using block detection and subsequent comparison between them using Levenshtein distance and Cosine measures with varying thresholds.
{"title":"Code clone detection using coarse and fine-grained hybrid approaches","authors":"Abdullah M. Sheneamer, J. Kalita","doi":"10.1109/INTELCIS.2015.7397263","DOIUrl":"https://doi.org/10.1109/INTELCIS.2015.7397263","url":null,"abstract":"If two fragments of source code are identical to each other, they are called code clones. Code clones introduce difficulties in software maintenance and cause bug propagation. Coarse-grained clone detectors have higher precision than fine-grained, but fine-grained detectors have higher recall than coarse-grained. In this paper, we present a hybrid clone detection technique that first uses a coarse-grained technique to analyze clones effectively to improve precision. Subsequently, we use a fine-grained detector to obtain additional information about the clones and to improve recall. Our method detects Type-1 and Type-2 clones using hash values for blocks, and gapped code clones (Type-3) using block detection and subsequent comparison between them using Levenshtein distance and Cosine measures with varying thresholds.","PeriodicalId":6478,"journal":{"name":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88550403","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 : 2015-12-01DOI: 10.1109/INTELCIS.2015.7397191
Mahmoud Elbattah, Mohamed Roushdy, M. Aref, Abdel-badeeh M. Salem
Ontology has been increasingly recognised as an instrumental artifact to help make sense of large amounts of data. However, the challenges of Big Data significantly overburden the process of ontology storage and query particularly. In this respect, the paper aims to convey considerations in relation to improving the practice of storing or querying large-scale ontologies. Initially, a systematic literature review is conducted with the aim of thoroughly inspecting the state-of-the-art in literature. Subsequently, a graph database-oriented approach is proposed, considering ontology as a large graph. The approach endeavours to address the limitations encountered within traditional relational models. Furthermore, scalability and query efficiency of the approach are verified based on empirical experiments using a subset of Freebase data. The Freebase subset is utilised to build a large-scale ontology graph composed of more than 500K nodes, and 2M edges.
{"title":"Large-scale ontology storage and query using graph database-oriented approach: The case of Freebase","authors":"Mahmoud Elbattah, Mohamed Roushdy, M. Aref, Abdel-badeeh M. Salem","doi":"10.1109/INTELCIS.2015.7397191","DOIUrl":"https://doi.org/10.1109/INTELCIS.2015.7397191","url":null,"abstract":"Ontology has been increasingly recognised as an instrumental artifact to help make sense of large amounts of data. However, the challenges of Big Data significantly overburden the process of ontology storage and query particularly. In this respect, the paper aims to convey considerations in relation to improving the practice of storing or querying large-scale ontologies. Initially, a systematic literature review is conducted with the aim of thoroughly inspecting the state-of-the-art in literature. Subsequently, a graph database-oriented approach is proposed, considering ontology as a large graph. The approach endeavours to address the limitations encountered within traditional relational models. Furthermore, scalability and query efficiency of the approach are verified based on empirical experiments using a subset of Freebase data. The Freebase subset is utilised to build a large-scale ontology graph composed of more than 500K nodes, and 2M edges.","PeriodicalId":6478,"journal":{"name":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75588828","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 : 2015-12-01DOI: 10.1109/INTELCIS.2015.7397221
A. M. Salem
Researchers have been used the artificial intelligence (AI) area of research in education to develop a new generation of intelligent tutoring and learning systems. AI concepts, theories and approaches receive increasing attention within the educational technology community. This paper discusses the AI approaches, methodologies and techniques for developing the intelligent e-Learning and tutoring systems. In addition, the paper presents some examples of the developed systems by the author and his colleagues at Artificial intelligence and Knowledge Engineering Research Labs, Ain Shams University, Cairo, Egypt.
{"title":"Towards of intelligence education and learning","authors":"A. M. Salem","doi":"10.1109/INTELCIS.2015.7397221","DOIUrl":"https://doi.org/10.1109/INTELCIS.2015.7397221","url":null,"abstract":"Researchers have been used the artificial intelligence (AI) area of research in education to develop a new generation of intelligent tutoring and learning systems. AI concepts, theories and approaches receive increasing attention within the educational technology community. This paper discusses the AI approaches, methodologies and techniques for developing the intelligent e-Learning and tutoring systems. In addition, the paper presents some examples of the developed systems by the author and his colleagues at Artificial intelligence and Knowledge Engineering Research Labs, Ain Shams University, Cairo, Egypt.","PeriodicalId":6478,"journal":{"name":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83290648","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 : 2015-12-01DOI: 10.1109/INTELCIS.2015.7397192
Safi Ibrahim, M. Hamdy, E. Shaaban
In Vehicular Ad Hoc Networks (VANETs), nodes are represented by Vehicles. Communication in VANETs can take place either between vehicles Vehicle-to-Vehicle (V2V), or between Vehicle and Infrastructure (V2I). Securing exchanged messages between Vehicles is of great importance, especially when they are life critical messages. Some of the Previous security researches discussed how to enable secure communication depending on the support of Infrastructure. In this work, security supported by infrastructure is defined by Services Oriented. Service Oriented Architecture (SOA) can be a novel alternative to satisfy all security requirements. We show the completeness of the proposed system by comparing it with previous security researches.
{"title":"A proposed security service set for VANET SOA","authors":"Safi Ibrahim, M. Hamdy, E. Shaaban","doi":"10.1109/INTELCIS.2015.7397192","DOIUrl":"https://doi.org/10.1109/INTELCIS.2015.7397192","url":null,"abstract":"In Vehicular Ad Hoc Networks (VANETs), nodes are represented by Vehicles. Communication in VANETs can take place either between vehicles Vehicle-to-Vehicle (V2V), or between Vehicle and Infrastructure (V2I). Securing exchanged messages between Vehicles is of great importance, especially when they are life critical messages. Some of the Previous security researches discussed how to enable secure communication depending on the support of Infrastructure. In this work, security supported by infrastructure is defined by Services Oriented. Service Oriented Architecture (SOA) can be a novel alternative to satisfy all security requirements. We show the completeness of the proposed system by comparing it with previous security researches.","PeriodicalId":6478,"journal":{"name":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83070932","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 : 2015-12-01DOI: 10.1109/INTELCIS.2015.7397258
M. Aly, M. Aref, M.I. Hassan
Real-time strategy games are strategic war games where two or more players operate on a virtual battlefield, controlling resources, buildings, units and technologies to achieve victory by destroying others. Achieving victory depends on selecting a suitable plan (set of actions), selecting a suitable plan depends on building an imagination (building a model) of the opponent to know how to deal with. This imagination is the opponent model, the stronger the opponent modelling process is, the more accurate the selected suitable plan is and consequently the higher probability achieving the victory is. One of the environment's challenges in real-time strategy games is that classifying the opponent model is game specific. This paper introduces a new methodology through which we can classify the observed opponent model in a way that is not game specific. Our methodology includes two paths, only one of them is executed per real-time strategy game type (per opponent models trained), which means that different type of real-time strategy games will execute different paths of the two paths of our methodology.
{"title":"Dimensions-based classifier for strategy classification of opponent models in real-time strategy games","authors":"M. Aly, M. Aref, M.I. Hassan","doi":"10.1109/INTELCIS.2015.7397258","DOIUrl":"https://doi.org/10.1109/INTELCIS.2015.7397258","url":null,"abstract":"Real-time strategy games are strategic war games where two or more players operate on a virtual battlefield, controlling resources, buildings, units and technologies to achieve victory by destroying others. Achieving victory depends on selecting a suitable plan (set of actions), selecting a suitable plan depends on building an imagination (building a model) of the opponent to know how to deal with. This imagination is the opponent model, the stronger the opponent modelling process is, the more accurate the selected suitable plan is and consequently the higher probability achieving the victory is. One of the environment's challenges in real-time strategy games is that classifying the opponent model is game specific. This paper introduces a new methodology through which we can classify the observed opponent model in a way that is not game specific. Our methodology includes two paths, only one of them is executed per real-time strategy game type (per opponent models trained), which means that different type of real-time strategy games will execute different paths of the two paths of our methodology.","PeriodicalId":6478,"journal":{"name":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89971134","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 : 2015-12-01DOI: 10.1109/INTELCIS.2015.7397230
E. Hossny, S. Khattab, F. Omara, H. Hassan
Cloud computing permits customers to host their data and applications to the cloud with an interesting economic cost-benefit tradeoff. However, the low price of cloud computing resources encourages attackers to rent a bulk of their botnets on the cloud and launch their attacks from there, which makes customers worry about using cloud computing. Therefore, in this paper, we propose a Bot Traceback (BTB) service for reporting and tracing back the presence of a bot inside an IaaS cloud provider. BTB aims to identify the virtual machine on which a bot runs either inside the same provider or inside a federated provider. The BTB service has been implemented as a part of the security tools in the EASI-CLOUDS project and has been deployed online. We present the implementation details of the BTB service and its main components (the BTB reporting service and BTB detection service). The BTB detection service will start running after a BTB report is received either from the same provider or from another federated provider.
{"title":"Finding the pin in the haystack: A Bot Traceback service for public clouds","authors":"E. Hossny, S. Khattab, F. Omara, H. Hassan","doi":"10.1109/INTELCIS.2015.7397230","DOIUrl":"https://doi.org/10.1109/INTELCIS.2015.7397230","url":null,"abstract":"Cloud computing permits customers to host their data and applications to the cloud with an interesting economic cost-benefit tradeoff. However, the low price of cloud computing resources encourages attackers to rent a bulk of their botnets on the cloud and launch their attacks from there, which makes customers worry about using cloud computing. Therefore, in this paper, we propose a Bot Traceback (BTB) service for reporting and tracing back the presence of a bot inside an IaaS cloud provider. BTB aims to identify the virtual machine on which a bot runs either inside the same provider or inside a federated provider. The BTB service has been implemented as a part of the security tools in the EASI-CLOUDS project and has been deployed online. We present the implementation details of the BTB service and its main components (the BTB reporting service and BTB detection service). The BTB detection service will start running after a BTB report is received either from the same provider or from another federated provider.","PeriodicalId":6478,"journal":{"name":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73612394","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 : 2015-12-01DOI: 10.1109/INTELCIS.2015.7397265
Rayane El Sibai, Yousra Chabchoub, J. Demerjian, Zakia Kazi-Aoul, Kabalan Barbar
On-line data stream analysis is an important challenge today because of the always-increasing rates of the streams issued from multiple heterogeneous sources, in many application domains. To reduce the amount of the data stream, several sampling methods were designed by the data stream research community. We focus in this paper, on the chain sampling algorithm proposed by Babcock et al. The aim of this algorithm is to select randomly and at any time, a given fixed proportion from the most recent items of the stream contained in the last sliding window. This algorithm is well adapted to the stream context, as only one pass over the data is performed. Moreover it uses a small memory, as it does not store all the items of the current sliding window. We show in this paper that the chain sampling algorithm suffers from some collision or redundancy problems. The collision occurs when the same item is selected as a sample more than once during the execution of the algorithm. We propose two approaches to overcome this weakness and improve the chain sampling algorithm. The first one is called “inverting the selection for a high sampling rate” and the second one is inspired from the “divide to conquer strategy”. Different experimentations are performed to show the efficiency of these two improvements, in particular their impact on the execution time of the algorithm.
{"title":"A performance study of the chain sampling algorithm","authors":"Rayane El Sibai, Yousra Chabchoub, J. Demerjian, Zakia Kazi-Aoul, Kabalan Barbar","doi":"10.1109/INTELCIS.2015.7397265","DOIUrl":"https://doi.org/10.1109/INTELCIS.2015.7397265","url":null,"abstract":"On-line data stream analysis is an important challenge today because of the always-increasing rates of the streams issued from multiple heterogeneous sources, in many application domains. To reduce the amount of the data stream, several sampling methods were designed by the data stream research community. We focus in this paper, on the chain sampling algorithm proposed by Babcock et al. The aim of this algorithm is to select randomly and at any time, a given fixed proportion from the most recent items of the stream contained in the last sliding window. This algorithm is well adapted to the stream context, as only one pass over the data is performed. Moreover it uses a small memory, as it does not store all the items of the current sliding window. We show in this paper that the chain sampling algorithm suffers from some collision or redundancy problems. The collision occurs when the same item is selected as a sample more than once during the execution of the algorithm. We propose two approaches to overcome this weakness and improve the chain sampling algorithm. The first one is called “inverting the selection for a high sampling rate” and the second one is inspired from the “divide to conquer strategy”. Different experimentations are performed to show the efficiency of these two improvements, in particular their impact on the execution time of the algorithm.","PeriodicalId":6478,"journal":{"name":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78245454","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 : 2015-12-01DOI: 10.1109/INTELCIS.2015.7397189
M. Voskoglou
The assessment of a system's performance is a very important task for its operation, because the results obtained by this action help the designer/user of the system to correct its weaknesses, thus making it more effective. The assessment methods usually utilized in practice are based on the principles of classical, bivalent logic (yes-no). However, in our everyday life they frequently appear assessment situations involving a degree of uncertainty and (or) ambiguity. Fuzzy logic, due to its nature of characterizing a case with multiple values, offers rich resources for dealing with such kind of situations. This gave us several times in past the impulse to apply principles of fuzzy logic for assessment purposes using as tools the corresponding system's total uncertainty (e.g. see [2] and its relevant references, Section of [3], etc) the Center of Gravity (COG) defuzzification technique (e.g. Section of [3], [4], etc) as well as the Triangular (TFAM) (e.g. [1]) and Trapezoidal (TRFAM) (e.g. [5]) Fuzzy Assessment Models, which are recently developed variations of the COG technique. In this presentation we shall use the Fuzzy Numbers (FNs), and in particular the Triangular (TFN) (e.g. [6]) and Trapezoidal (TpFN) Fuzzy Numbers, as an alternative assessment tool. FNs play a fundamental role in fuzzy mathematics, analogous to the role played by the ordinary numbers in classical mathematics. Our results are illustrated by an example, while this alternative assessment approach is compared with the assessment methods of the bivalent (calculation of the means, GPA index) and fuzzy logic (see above) that we have already used in earlier works.
{"title":"Cyber fuzzy assessment methods","authors":"M. Voskoglou","doi":"10.1109/INTELCIS.2015.7397189","DOIUrl":"https://doi.org/10.1109/INTELCIS.2015.7397189","url":null,"abstract":"The assessment of a system's performance is a very important task for its operation, because the results obtained by this action help the designer/user of the system to correct its weaknesses, thus making it more effective. The assessment methods usually utilized in practice are based on the principles of classical, bivalent logic (yes-no). However, in our everyday life they frequently appear assessment situations involving a degree of uncertainty and (or) ambiguity. Fuzzy logic, due to its nature of characterizing a case with multiple values, offers rich resources for dealing with such kind of situations. This gave us several times in past the impulse to apply principles of fuzzy logic for assessment purposes using as tools the corresponding system's total uncertainty (e.g. see [2] and its relevant references, Section of [3], etc) the Center of Gravity (COG) defuzzification technique (e.g. Section of [3], [4], etc) as well as the Triangular (TFAM) (e.g. [1]) and Trapezoidal (TRFAM) (e.g. [5]) Fuzzy Assessment Models, which are recently developed variations of the COG technique. In this presentation we shall use the Fuzzy Numbers (FNs), and in particular the Triangular (TFN) (e.g. [6]) and Trapezoidal (TpFN) Fuzzy Numbers, as an alternative assessment tool. FNs play a fundamental role in fuzzy mathematics, analogous to the role played by the ordinary numbers in classical mathematics. Our results are illustrated by an example, while this alternative assessment approach is compared with the assessment methods of the bivalent (calculation of the means, GPA index) and fuzzy logic (see above) that we have already used in earlier works.","PeriodicalId":6478,"journal":{"name":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79836326","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 : 2015-12-01DOI: 10.1109/INTELCIS.2015.7397272
T. Kokul, A. Ramanan, U. Pinidiyaarachchi
Automatically detecting and tracking multiple persons in videos is one of the main research interest in computer vision based applications. This paper presents a tracking-by-detection approach for tracking people in dynamic backgrounds with frequent occlusions by combining pre-trained generic person detector, online trained person-specific detector and a motion tracker. The popular aggregate channel features (ACF) are used to train the detectors and target specific particle filter is used as motion tracker. In order to learn right appearance of a target person, person-specific detector learns positive samples from prior frames which are detected by both generic person detector and person-specific detector. Data associations among the coincident detections of the detectors and tracker are used to update the person-specific detector and motion tracker. The person-specific detector searches the target person in a reduced region, which is defined by the associate motion tracker. A careful combination of detections of both detectors and tracker are used to locate the correct target person in the video sequence. Experiments have been carried out on Caltech pedestrian benchmark dataset. The proposed method shows better performance against state-of-the-art tracker while maintaining the tracking speed in real-time.
{"title":"Online multi-person tracking-by-detection method using ACF and particle filter","authors":"T. Kokul, A. Ramanan, U. Pinidiyaarachchi","doi":"10.1109/INTELCIS.2015.7397272","DOIUrl":"https://doi.org/10.1109/INTELCIS.2015.7397272","url":null,"abstract":"Automatically detecting and tracking multiple persons in videos is one of the main research interest in computer vision based applications. This paper presents a tracking-by-detection approach for tracking people in dynamic backgrounds with frequent occlusions by combining pre-trained generic person detector, online trained person-specific detector and a motion tracker. The popular aggregate channel features (ACF) are used to train the detectors and target specific particle filter is used as motion tracker. In order to learn right appearance of a target person, person-specific detector learns positive samples from prior frames which are detected by both generic person detector and person-specific detector. Data associations among the coincident detections of the detectors and tracker are used to update the person-specific detector and motion tracker. The person-specific detector searches the target person in a reduced region, which is defined by the associate motion tracker. A careful combination of detections of both detectors and tracker are used to locate the correct target person in the video sequence. Experiments have been carried out on Caltech pedestrian benchmark dataset. The proposed method shows better performance against state-of-the-art tracker while maintaining the tracking speed in real-time.","PeriodicalId":6478,"journal":{"name":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89008483","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}
The need for good security systems in banking, e-commerce and other applications is ever increasing. The proposed project makes the security system more robust and less prone to attacks. Brain Computer Interface (BCI) is used in order to obtain the password from the user by using their brain waves. This paper describes the current trend in BCI technologies and then the Hardware implementation of the proposed solution has been described. The Electro-Encephalogram (EEG) waves are obtained with the help of active dry electrodes and processed using signal conditioning circuits. These EEG signals are then interpreted to obtain the thought pattern of the user to match them to the stored password in the system. Finally a Transmitter-Receiver model has been used with a lock interface system is used to indicate the opening or closing of the lock.
{"title":"Development of a novel EEG wave controlled security system","authors":"Pritham Gajakumar Shah, Krishna Chaithanya Vastare, Xu Huang, Ajithkumar Srikumar, Suraj Mademur Sreenivasa, Adarsh Puvvadi Ram Mohan Kumar, Karthik Rajashekhar Kodada","doi":"10.1109/INTELCIS.2015.7397207","DOIUrl":"https://doi.org/10.1109/INTELCIS.2015.7397207","url":null,"abstract":"The need for good security systems in banking, e-commerce and other applications is ever increasing. The proposed project makes the security system more robust and less prone to attacks. Brain Computer Interface (BCI) is used in order to obtain the password from the user by using their brain waves. This paper describes the current trend in BCI technologies and then the Hardware implementation of the proposed solution has been described. The Electro-Encephalogram (EEG) waves are obtained with the help of active dry electrodes and processed using signal conditioning circuits. These EEG signals are then interpreted to obtain the thought pattern of the user to match them to the stored password in the system. Finally a Transmitter-Receiver model has been used with a lock interface system is used to indicate the opening or closing of the lock.","PeriodicalId":6478,"journal":{"name":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88550219","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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