2019
|
48. | Menéndez, Héctor D; Bhattacharya, Sukriti; Clark, David; Barr, Earl T The arms race: Adversarial search defeats entropy used to detect malware Journal Article Expert Systems with Applications, 118 , pp. 246 - 260, 2019, ISSN: 0957-4174. Abstract | Links | BibTeX | Tags: Adversarial learning, Entropy, Information theory, Malware, Packing, Time Series @article{MENENDEZ2019246,
title = {The arms race: Adversarial search defeats entropy used to detect malware},
author = {Héctor D Menéndez and Sukriti Bhattacharya and David Clark and Earl T Barr},
url = {http://www.sciencedirect.com/science/article/pii/S0957417418306535},
doi = {https://doi.org/10.1016/j.eswa.2018.10.011},
issn = {0957-4174},
year = {2019},
date = {2019-01-01},
journal = {Expert Systems with Applications},
volume = {118},
pages = {246 - 260},
abstract = {Malware creators have been getting their way for too long now. String-based similarity measures can leverage ground truth in a scalable way and can operate at a level of abstraction that is difficult to combat from the code level. At the string level, information theory and, specifically, entropy play an important role related to detecting patterns altered by concealment strategies, such as polymorphism or encryption. Controlling the entropy levels in different parts of a disk resident executable allows an analyst to detect malware or a black hat to evade the detection. This paper shows these two perspectives into two scalable entropy-based tools: EnTS and EEE. EnTS, the detection tool, shows the effectiveness of detecting entropy patterns, achieving 100% precision with 82% accuracy. It outperforms VirusTotal for accuracy on combined Kaggle and VirusShare malware. EEE, the evasion tool, shows the effectiveness of entropy as a concealment strategy, attacking binary-based state of the art detectors. It learns their detection patterns in up to 8 generations of its search process, and increments their false negative rate from range 0–9%, up to the range 90–98.7%.},
keywords = {Adversarial learning, Entropy, Information theory, Malware, Packing, Time Series},
pubstate = {published},
tppubtype = {article}
}
Malware creators have been getting their way for too long now. String-based similarity measures can leverage ground truth in a scalable way and can operate at a level of abstraction that is difficult to combat from the code level. At the string level, information theory and, specifically, entropy play an important role related to detecting patterns altered by concealment strategies, such as polymorphism or encryption. Controlling the entropy levels in different parts of a disk resident executable allows an analyst to detect malware or a black hat to evade the detection. This paper shows these two perspectives into two scalable entropy-based tools: EnTS and EEE. EnTS, the detection tool, shows the effectiveness of detecting entropy patterns, achieving 100% precision with 82% accuracy. It outperforms VirusTotal for accuracy on combined Kaggle and VirusShare malware. EEE, the evasion tool, shows the effectiveness of entropy as a concealment strategy, attacking binary-based state of the art detectors. It learns their detection patterns in up to 8 generations of its search process, and increments their false negative rate from range 0–9%, up to the range 90–98.7%. |
2018
|
47. | Calleja Alejandro, Mart'in Alejandro Men'endez H'ector Tapiador Juan Clark David D Picking on the family: Disrupting android malware triage by forcing misclassification Journal Article Expert Systems with Applications, 95 , pp. 113 - 126, 2018, ISSN: 0957-4174. Abstract | Links | BibTeX | Tags: Adversarial learning, Genetic Algorithms, Iagodroid, Malware classification @article{CALLEJA2018113,
title = {Picking on the family: Disrupting android malware triage by forcing misclassification},
author = {Calleja, Alejandro, Mart'in, Alejandro, Men'endez, H'ector D, Tapiador, Juan, Clark, David},
url = {http://www.sciencedirect.com/science/article/pii/S0957417417307881},
doi = {https://doi.org/10.1016/j.eswa.2017.11.032},
issn = {0957-4174},
year = {2018},
date = {2018-01-01},
journal = {Expert Systems with Applications},
volume = {95},
pages = {113 - 126},
abstract = {Machine learning classification algorithms are widely applied to different malware analysis problems because of their proven abilities to learn from examples and perform relatively well with little human input. Use cases include the labelling of malicious samples according to families during triage of suspected malware. However, automated algorithms are vulnerable to attacks. An attacker could carefully manipulate the sample to force the algorithm to produce a particular output. In this paper we discuss one such attack on Android malware classifiers. We design and implement a prototype tool, called IagoDroid, that takes as input a malware sample and a target family, and modifies the sample to cause it to be classified as belonging to this family while preserving its original semantics. Our technique relies on a search process that generates variants of the original sample without modifying their semantics. We tested IagoDroid against RevealDroid, a recent, open source, Android malware classifier based on a variety of static features. IagoDroid successfully forces misclassification for 28 of the 29 representative malware families present in the DREBIN dataset. Remarkably, it does so by modifying just a single feature of the original malware. On average, it finds the first evasive sample in the first search iteration, and converges to a 100% evasive population within 4 iterations. Finally, we introduce RevealDroid*, a more robust classifier that implements several techniques proposed in other adversarial learning domains. Our experiments suggest that RevealDroid* can correctly detect up to 99% of the variants generated by IagoDroid.},
keywords = {Adversarial learning, Genetic Algorithms, Iagodroid, Malware classification},
pubstate = {published},
tppubtype = {article}
}
Machine learning classification algorithms are widely applied to different malware analysis problems because of their proven abilities to learn from examples and perform relatively well with little human input. Use cases include the labelling of malicious samples according to families during triage of suspected malware. However, automated algorithms are vulnerable to attacks. An attacker could carefully manipulate the sample to force the algorithm to produce a particular output. In this paper we discuss one such attack on Android malware classifiers. We design and implement a prototype tool, called IagoDroid, that takes as input a malware sample and a target family, and modifies the sample to cause it to be classified as belonging to this family while preserving its original semantics. Our technique relies on a search process that generates variants of the original sample without modifying their semantics. We tested IagoDroid against RevealDroid, a recent, open source, Android malware classifier based on a variety of static features. IagoDroid successfully forces misclassification for 28 of the 29 representative malware families present in the DREBIN dataset. Remarkably, it does so by modifying just a single feature of the original malware. On average, it finds the first evasive sample in the first search iteration, and converges to a 100% evasive population within 4 iterations. Finally, we introduce RevealDroid*, a more robust classifier that implements several techniques proposed in other adversarial learning domains. Our experiments suggest that RevealDroid* can correctly detect up to 99% of the variants generated by IagoDroid. |
2017
|
46. | Men'endez, H'ector D; Otero, Fernando EB ; Camacho, David Extending the SACOC algorithm through the Nystrom Journal Article International Journal of Bio-Inspired Computation, 10 (2), pp. 127–135, 2017. BibTeX | Tags: ACO, Clustering @article{menendez2017extending,
title = {Extending the SACOC algorithm through the Nystrom},
author = {Men'endez, H'ector D and Otero, Fernando EB and Camacho, David},
year = {2017},
date = {2017-01-01},
journal = {International Journal of Bio-Inspired Computation},
volume = {10},
number = {2},
pages = {127--135},
publisher = {Inderscience Publishers (IEL)},
keywords = {ACO, Clustering},
pubstate = {published},
tppubtype = {article}
}
|
45. | Mart'in, Alejandro ; Men'endez, H'ector D; Camacho, David MOCDroid: multi-objective evolutionary classifier for Android malware detection Journal Article Soft Computing, 21 (24), pp. 7405–7415, 2017. BibTeX | Tags: Cybersecurity, Malware, Multi-Objective Algorithms @article{martin2017mocdroid,
title = {MOCDroid: multi-objective evolutionary classifier for Android malware detection},
author = {Mart'in, Alejandro and Men'endez, H'ector D and Camacho, David},
year = {2017},
date = {2017-01-01},
journal = {Soft Computing},
volume = {21},
number = {24},
pages = {7405--7415},
publisher = {Springer Berlin Heidelberg},
keywords = {Cybersecurity, Malware, Multi-Objective Algorithms},
pubstate = {published},
tppubtype = {article}
}
|
44. | Rodr'iguez-Fern'andez, V'ictor ; Men'endez, H'ector D; Camacho, David Analysing temporal performance profiles of UAV operators using time series clustering Journal Article Expert Systems with Applications, 70 , pp. 103–118, 2017. BibTeX | Tags: Clustering, UAV Simulator @article{rodriguez2017analysing,
title = {Analysing temporal performance profiles of UAV operators using time series clustering},
author = {Rodr'iguez-Fern'andez, V'ictor and Men'endez, H'ector D and Camacho, David},
year = {2017},
date = {2017-01-01},
journal = {Expert Systems with Applications},
volume = {70},
pages = {103--118},
publisher = {Pergamon},
keywords = {Clustering, UAV Simulator},
pubstate = {published},
tppubtype = {article}
}
|
43. | Rodr'iguez-Fern'andez, V'ictor ; Men'endez, H'ector D; Camacho, David A study on performance metrics and clustering methods for analyzing behavior in UAV operations Journal Article Journal of Intelligent & Fuzzy Systems, 32 (2), pp. 1307–1319, 2017. BibTeX | Tags: Clustering, UAV Simulator @article{rodriguez2017study,
title = {A study on performance metrics and clustering methods for analyzing behavior in UAV operations},
author = {Rodr'iguez-Fern'andez, V'ictor and Men'endez, H'ector D and Camacho, David},
year = {2017},
date = {2017-01-01},
journal = {Journal of Intelligent & Fuzzy Systems},
volume = {32},
number = {2},
pages = {1307--1319},
publisher = {IOS Press},
keywords = {Clustering, UAV Simulator},
pubstate = {published},
tppubtype = {article}
}
|
42. | Okazaki, Shintaro ; Menendez, Hector D Virtual Corporate Social Responsibility Dialog: Seeking a Gap Between Proposed Concepts and Actual Practices Incollection Handbook of Integrated CSR Communication, pp. 225–234, Springer, Cham, 2017. BibTeX | Tags: Corporate Social Responsibility, Social Mining, Twitter @incollection{okazaki2017virtual,
title = {Virtual Corporate Social Responsibility Dialog: Seeking a Gap Between Proposed Concepts and Actual Practices},
author = {Okazaki, Shintaro and Menendez, Hector D},
year = {2017},
date = {2017-01-01},
booktitle = {Handbook of Integrated CSR Communication},
pages = {225--234},
publisher = {Springer, Cham},
keywords = {Corporate Social Responsibility, Social Mining, Twitter},
pubstate = {published},
tppubtype = {incollection}
}
|
41. | Henninger, Claudia E; Alevizou, Panayiota J; Oates, Caroline J; Tourky, Marwa ; Kitchen, Philip J; Melewar, TC ; Shaalan, Ahmed S; Okazaki, Shintaro ; Plangger, Kirk ; West, Douglas ; others, Session A1: Corporate Brand Identity and Corporate Social Responsibility Journal Article Corporate identity in UK slow fashion micro-organisations and the impact on scaling, pp. 17, 2017. BibTeX | Tags: Clustering, Social Mining @article{henninger2017session,
title = {Session A1: Corporate Brand Identity and Corporate Social Responsibility},
author = {Henninger, Claudia E and Alevizou, Panayiota J and Oates, Caroline J and Tourky, Marwa and Kitchen, Philip J and Melewar, TC and Shaalan, Ahmed S and Okazaki, Shintaro and Plangger, Kirk and West, Douglas and others},
year = {2017},
date = {2017-01-01},
journal = {Corporate identity in UK slow fashion micro-organisations and the impact on scaling},
pages = {17},
keywords = {Clustering, Social Mining},
pubstate = {published},
tppubtype = {article}
}
|
2016
|
40. | Men'endez, H'ector D; Otero, Fernando EB ; Camacho, David Medoid-based clustering using ant colony optimization Journal Article Swarm Intelligence, 10 (2), pp. 123–145, 2016. BibTeX | Tags: ACO, Clustering, Medoids @article{menendez2016medoid,
title = {Medoid-based clustering using ant colony optimization},
author = {Men'endez, H'ector D and Otero, Fernando EB and Camacho, David},
year = {2016},
date = {2016-01-01},
journal = {Swarm Intelligence},
volume = {10},
number = {2},
pages = {123--145},
publisher = {Springer US},
keywords = {ACO, Clustering, Medoids},
pubstate = {published},
tppubtype = {article}
}
|
39. | Rodr'iguez-Fern'andez, V'ictor ; Men'endez, H'ector D; Camacho, David Automatic profile generation for UAV operators using a simulation-based training environment Journal Article Progress in Artificial Intelligence, 5 (1), pp. 37–46, 2016. BibTeX | Tags: Clustering, UAV Simulator @article{rodriguez2016automatic,
title = {Automatic profile generation for UAV operators using a simulation-based training environment},
author = {Rodr'iguez-Fern'andez, V'ictor and Men'endez, H'ector D and Camacho, David},
year = {2016},
date = {2016-01-01},
journal = {Progress in Artificial Intelligence},
volume = {5},
number = {1},
pages = {37--46},
publisher = {Springer Berlin Heidelberg},
keywords = {Clustering, UAV Simulator},
pubstate = {published},
tppubtype = {article}
}
|
38. | Mart'in, Alejandro ; Men'endez, H'ector D; Camacho, David Studying the Influence of Static API Calls for Hiding Malware Inproceedings Conference of the Spanish Association for Artificial Intelligence, pp. 363–372, Springer, Cham 2016. BibTeX | Tags: Cybersecurity, Malware @inproceedings{martin2016studying,
title = {Studying the Influence of Static API Calls for Hiding Malware},
author = {Mart'in, Alejandro and Men'endez, H'ector D and Camacho, David},
year = {2016},
date = {2016-01-01},
booktitle = {Conference of the Spanish Association for Artificial Intelligence},
pages = {363--372},
organization = {Springer, Cham},
keywords = {Cybersecurity, Malware},
pubstate = {published},
tppubtype = {inproceedings}
}
|
37. | Bhattacharya, Sukriti ; Men'endez, H'ector D; Barr, Earl ; Clark, David ITect: Scalable Information Theoretic Similarity for Malware Detection Journal Article arXiv preprint arXiv:1609.02404, 2016. BibTeX | Tags: Classification, Cybersecurity, Malware @article{bhattacharya2016itect,
title = {ITect: Scalable Information Theoretic Similarity for Malware Detection},
author = {Bhattacharya, Sukriti and Men'endez, H'ector D and Barr, Earl and Clark, David},
year = {2016},
date = {2016-01-01},
journal = {arXiv preprint arXiv:1609.02404},
keywords = {Classification, Cybersecurity, Malware},
pubstate = {published},
tppubtype = {article}
}
|
36. | Mart'in, Alejandro ; Men'endez, H'ector D; Camacho, David String-based malware detection for android environments Inproceedings International Symposium on Intelligent and Distributed Computing, pp. 99–108, Springer, Cham 2016. BibTeX | Tags: Classification, Cybersecurity, Malware @inproceedings{martin2016string,
title = {String-based malware detection for android environments},
author = {Mart'in, Alejandro and Men'endez, H'ector D and Camacho, David},
year = {2016},
date = {2016-01-01},
booktitle = {International Symposium on Intelligent and Distributed Computing},
pages = {99--108},
organization = {Springer, Cham},
keywords = {Classification, Cybersecurity, Malware},
pubstate = {published},
tppubtype = {inproceedings}
}
|
35. | Martin, Alejandro ; Men'endez, H'ector D; Camacho, David Genetic boosting classification for malware detection Inproceedings Evolutionary Computation (CEC), 2016 IEEE Congress on, pp. 1030–1037, IEEE 2016. BibTeX | Tags: Cybersecurity, Genetic Algorithms, Malware @inproceedings{martin2016genetic,
title = {Genetic boosting classification for malware detection},
author = {Martin, Alejandro and Men'endez, H'ector D and Camacho, David},
year = {2016},
date = {2016-01-01},
booktitle = {Evolutionary Computation (CEC), 2016 IEEE Congress on},
pages = {1030--1037},
organization = {IEEE},
keywords = {Cybersecurity, Genetic Algorithms, Malware},
pubstate = {published},
tppubtype = {inproceedings}
}
|
34. | Mart'in, Alejandro ; Calleja, Alejandro ; Men'endez, H'ector D; Tapiador, Juan ; Camacho, David ADROIT: Android malware detection using meta-information Inproceedings Computational Intelligence (SSCI), 2016 IEEE Symposium Series on, pp. 1–8, IEEE 2016. BibTeX | Tags: Android, Cybersecurity, Malware @inproceedings{martin2016adroit,
title = {ADROIT: Android malware detection using meta-information},
author = {Mart'in, Alejandro and Calleja, Alejandro and Men'endez, H'ector D and Tapiador, Juan and Camacho, David},
year = {2016},
date = {2016-01-01},
booktitle = {Computational Intelligence (SSCI), 2016 IEEE Symposium Series on},
pages = {1--8},
organization = {IEEE},
keywords = {Android, Cybersecurity, Malware},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2015
|
33. | Okazaki, Shintaro ; D'iaz-Mart'in, Ana M; Rozano, Mercedes ; Men'endez-Benito, H'ector David Using Twitter to engage with customers: a data mining approach Journal Article Internet Research, 25 (3), 2015. BibTeX | Tags: Classification, Marketing, Social Mining, Twitter @article{okazaki2015using,
title = {Using Twitter to engage with customers: a data mining approach},
author = {Okazaki, Shintaro and D'iaz-Mart'in, Ana M and Rozano, Mercedes and Men'endez-Benito, H'ector David},
year = {2015},
date = {2015-01-01},
journal = {Internet Research},
volume = {25},
number = {3},
publisher = {Emerald Group Publishing Limited},
keywords = {Classification, Marketing, Social Mining, Twitter},
pubstate = {published},
tppubtype = {article}
}
|
32. | Men'endez, H'ector David ; Camacho, David MOGCLA: A Multi-Objective Genetic Clustering Algorithm for Large Data Analysis. Inproceedings Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference, pp. 1437–1438, ACM 2015. BibTeX | Tags: Clustering, Genetic Algorithms, Graph-based, Large Data, MOGCLA, Multi-Objective Algorithms @inproceedings{menendez2015mogcla,
title = {MOGCLA: A Multi-Objective Genetic Clustering Algorithm for Large Data Analysis.},
author = {Men'endez, H'ector David and Camacho, David},
year = {2015},
date = {2015-01-01},
booktitle = {Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference},
pages = {1437--1438},
organization = {ACM},
keywords = {Clustering, Genetic Algorithms, Graph-based, Large Data, MOGCLA, Multi-Objective Algorithms},
pubstate = {published},
tppubtype = {inproceedings}
}
|
31. | Rodriguez-Fernandez, Victor ; Menendez, Hector D; Camacho, David Design and development of a lightweight multi-UAV simulator Inproceedings Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on, pp. 255–260, IEEE 2015. BibTeX | Tags: Behaviour, Clustering, UAV Simulator @inproceedings{rodriguez2015design,
title = {Design and development of a lightweight multi-UAV simulator},
author = {Rodriguez-Fernandez, Victor and Menendez, Hector D and Camacho, David},
year = {2015},
date = {2015-01-01},
booktitle = {Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on},
pages = {255--260},
organization = {IEEE},
keywords = {Behaviour, Clustering, UAV Simulator},
pubstate = {published},
tppubtype = {inproceedings}
}
|
30. | Menendez, Hector D; Camacho, David GANY: A genetic spectral-based Clustering algorithm for Large Data Analysis Inproceedings Evolutionary Computation (CEC), 2015 IEEE Congress on, pp. 640–647, IEEE 2015. BibTeX | Tags: Clustering, GANY, Genetic Algorithms, Graph-based, Manifold, Spectral Clustering @inproceedings{menendez2015gany,
title = {GANY: A genetic spectral-based Clustering algorithm for Large Data Analysis},
author = {Menendez, Hector D and Camacho, David},
year = {2015},
date = {2015-01-01},
booktitle = {Evolutionary Computation (CEC), 2015 IEEE Congress on},
pages = {640--647},
organization = {IEEE},
keywords = {Clustering, GANY, Genetic Algorithms, Graph-based, Manifold, Spectral Clustering},
pubstate = {published},
tppubtype = {inproceedings}
}
|
29. | Menendez, Hector D A tutorial on manifold clustering using genetic algorithms Inproceedings Innovations in Intelligent SysTems and Applications (INISTA), 2015 International Symposium on, pp. 1–6, IEEE 2015. BibTeX | Tags: Clustering, Genetic Algorithms, Manifold, Tutorial @inproceedings{menendez2015tutorial,
title = {A tutorial on manifold clustering using genetic algorithms},
author = { Hector D Menendez},
year = {2015},
date = {2015-01-01},
booktitle = {Innovations in Intelligent SysTems and Applications (INISTA), 2015 International Symposium on},
pages = {1--6},
organization = {IEEE},
keywords = {Clustering, Genetic Algorithms, Manifold, Tutorial},
pubstate = {published},
tppubtype = {inproceedings}
}
|
28. | Rodr'iguez-Fern'andez, V'ictor ; Men'endez, H'ector D; Camacho, David User Profile Analysis for UAV Operators in a Simulation Environment Incollection Computational Collective Intelligence, pp. 338–347, Springer International Publishing, 2015. BibTeX | Tags: Behaviour, Clustering, UAV Simulator @incollection{rodriguez2015user,
title = {User Profile Analysis for UAV Operators in a Simulation Environment},
author = {Rodr'iguez-Fern'andez, V'ictor and Men'endez, H'ector D and Camacho, David},
year = {2015},
date = {2015-01-01},
booktitle = {Computational Collective Intelligence},
pages = {338--347},
publisher = {Springer International Publishing},
keywords = {Behaviour, Clustering, UAV Simulator},
pubstate = {published},
tppubtype = {incollection}
}
|
27. | Rodr'iguez-Fern'andez, V'ictor ; Men'endez, H'ector D; Camacho, David Analyzing planning and monitoring skills of users in a multi-UAV simulation environment Inproceedings Conference of the Spanish Association for Artificial Intelligence, pp. 255–264, Springer International Publishing 2015. BibTeX | Tags: Clustering, UAV Simulator @inproceedings{rodriguez2015analyzing,
title = {Analyzing planning and monitoring skills of users in a multi-UAV simulation environment},
author = {Rodr'iguez-Fern'andez, V'ictor and Men'endez, H'ector D and Camacho, David},
year = {2015},
date = {2015-01-01},
booktitle = {Conference of the Spanish Association for Artificial Intelligence},
pages = {255--264},
organization = {Springer International Publishing},
keywords = {Clustering, UAV Simulator},
pubstate = {published},
tppubtype = {inproceedings}
}
|
26. | Menendez, Hector ; Otero, Fernando Esteban Barril ; Camacho, David Extending the SACOC algorithm through the Nystrom method for Dense Manifold Data Analysis Journal Article International Journal of Bio-Inspired Computation, 2015. BibTeX | Tags: ACO, Clustering @article{menendez2015extending,
title = {Extending the SACOC algorithm through the Nystrom method for Dense Manifold Data Analysis},
author = {Menendez, Hector and Otero, Fernando Esteban Barril and Camacho, David},
year = {2015},
date = {2015-01-01},
journal = {International Journal of Bio-Inspired Computation},
publisher = {Inderscience},
keywords = {ACO, Clustering},
pubstate = {published},
tppubtype = {article}
}
|
2014
|
25. | Men'endez, H'ector D; Barrero, David F; Camacho, David A Genetic Graph-based Approach for Partitional Clustering Journal Article International journal of neural systems, 24 (03), 2014. BibTeX | Tags: Clustering, Genetic Algorithms, Graph-based @article{menendez2014genetic,
title = {A Genetic Graph-based Approach for Partitional Clustering},
author = {Men'endez, H'ector D and Barrero, David F and Camacho, David},
year = {2014},
date = {2014-01-01},
journal = {International journal of neural systems},
volume = {24},
number = {03},
publisher = {World Scientific Publishing Company},
keywords = {Clustering, Genetic Algorithms, Graph-based},
pubstate = {published},
tppubtype = {article}
}
|
24. | Bello-Orgaz, Gema ; Men'endez, H'ector ; Okazaki, Shintaro ; Camacho, David Combining Social-Based Data Mining Techniques To Extract Collective Trends From Twitter Journal Article Malaysian Journal of Computer Science, 27 (2), pp. 95–111, 2014. BibTeX | Tags: Classification, Clustering, Marketing, Social Mining @article{bello2014combining,
title = {Combining Social-Based Data Mining Techniques To Extract Collective Trends From Twitter},
author = {Bello-Orgaz, Gema and Men'endez, H'ector and Okazaki, Shintaro and Camacho, David},
year = {2014},
date = {2014-01-01},
journal = {Malaysian Journal of Computer Science},
volume = {27},
number = {2},
pages = {95--111},
publisher = {Electronic Journal of University of Malaya},
keywords = {Classification, Clustering, Marketing, Social Mining},
pubstate = {published},
tppubtype = {article}
}
|
23. | Men'endez, H'ector D; Plaza, Laura ; Camacho, David Combining graph connectivity and genetic clustering to improve biomedical summarization Inproceedings Evolutionary Computation (CEC), 2014 IEEE Congress on, pp. 2740–2747, IEEE 2014. BibTeX | Tags: Automatic Summarization, Clustering, Genetic Algorithms, Graph-based @inproceedings{menendez2014combining,
title = {Combining graph connectivity and genetic clustering to improve biomedical summarization},
author = {Men'endez, H'ector D and Plaza, Laura and Camacho, David},
year = {2014},
date = {2014-01-01},
booktitle = {Evolutionary Computation (CEC), 2014 IEEE Congress on},
pages = {2740--2747},
organization = {IEEE},
keywords = {Automatic Summarization, Clustering, Genetic Algorithms, Graph-based},
pubstate = {published},
tppubtype = {inproceedings}
}
|
22. | Men'endez, H'ector D; Otero, Fernando EB ; Camacho, David SACOC: A spectral-based ACO clustering algorithm Incollection Intelligent Distributed Computing VIII, pp. 185–194, Springer International Publishing, 2014. BibTeX | Tags: ACO, Clustering, Manifold, Spectral Clustering @incollection{menendez2014sacoc,
title = {SACOC: A spectral-based ACO clustering algorithm},
author = {Men'endez, H'ector D and Otero, Fernando EB and Camacho, David},
year = {2014},
date = {2014-01-01},
booktitle = {Intelligent Distributed Computing VIII},
pages = {185--194},
publisher = {Springer International Publishing},
keywords = {ACO, Clustering, Manifold, Spectral Clustering},
pubstate = {published},
tppubtype = {incollection}
}
|
21. | Men'endez, H'ector D; Otero, Fernando EB ; Camacho, David MACOC: a medoid-based ACO clustering algorithm Incollection Swarm Intelligence, pp. 122–133, Springer International Publishing, 2014. BibTeX | Tags: ACO, Clustering, Medoids @incollection{menendez2014macoc,
title = {MACOC: a medoid-based ACO clustering algorithm},
author = {Men'endez, H'ector D and Otero, Fernando EB and Camacho, David},
year = {2014},
date = {2014-01-01},
booktitle = {Swarm Intelligence},
pages = {122--133},
publisher = {Springer International Publishing},
keywords = {ACO, Clustering, Medoids},
pubstate = {published},
tppubtype = {incollection}
}
|
20. | Menendez, Hector D; Camacho, David A Multi-Objective Graph-based Genetic Algorithm for Image Segmentation Inproceedings Innovations in Intelligent Systems and Applications (INISTA) Proceedings, 2014 IEEE International Symposium on, pp. 234–241, IEEE 2014. BibTeX | Tags: Clustering, Genetic Algorithms, Graph-based, Image Segmentation, Manifold, Multi-Objective Algorithms @inproceedings{menendez2014multi,
title = {A Multi-Objective Graph-based Genetic Algorithm for Image Segmentation},
author = {Menendez, Hector D and Camacho, David},
year = {2014},
date = {2014-01-01},
booktitle = {Innovations in Intelligent Systems and Applications (INISTA) Proceedings, 2014 IEEE International Symposium on},
pages = {234--241},
organization = {IEEE},
keywords = {Clustering, Genetic Algorithms, Graph-based, Image Segmentation, Manifold, Multi-Objective Algorithms},
pubstate = {published},
tppubtype = {inproceedings}
}
|
19. | Men'endez, H'ector D; Delgado-Calle, Carlos ; Camacho, David TweetSemMiner: A Meta-Topic Identification Model for Twitter Using Semantic Analysis Incollection Intelligent Data Engineering and Automated Learning--IDEAL 2014, pp. 69–76, Springer International Publishing, 2014. BibTeX | Tags: Meta-topics, Semantics, Twitter @incollection{menendez2014tweetsemminer,
title = {TweetSemMiner: A Meta-Topic Identification Model for Twitter Using Semantic Analysis},
author = {Men'endez, H'ector D and Delgado-Calle, Carlos and Camacho, David},
year = {2014},
date = {2014-01-01},
booktitle = {Intelligent Data Engineering and Automated Learning--IDEAL 2014},
pages = {69--76},
publisher = {Springer International Publishing},
keywords = {Meta-topics, Semantics, Twitter},
pubstate = {published},
tppubtype = {incollection}
}
|
18. | Men'endez, H'ector D; V'azquez, Miguel ; Camacho, David Mixed Clustering Methods to Forecast Baseball Trends Incollection Intelligent Distributed Computing VIII, pp. 175–184, Springer International Publishing, 2014. BibTeX | Tags: Baseball, Clustering, Forecasting, Sports @incollection{menendez2014mixed,
title = {Mixed Clustering Methods to Forecast Baseball Trends},
author = {Men'endez, H'ector D and V'azquez, Miguel and Camacho, David},
year = {2014},
date = {2014-01-01},
booktitle = {Intelligent Distributed Computing VIII},
pages = {175--184},
publisher = {Springer International Publishing},
keywords = {Baseball, Clustering, Forecasting, Sports},
pubstate = {published},
tppubtype = {incollection}
}
|
17. | Men'endez, H'ector D; Vindel, Rafael ; Camacho, David Combining time series and clustering to extract gamer profile evolution Incollection Computational Collective Intelligence. Technologies and Applications, pp. 262–271, Springer International Publishing, 2014. BibTeX | Tags: Behaviour, Clustering, Time Series, Videogames @incollection{menendez2014combiningb,
title = {Combining time series and clustering to extract gamer profile evolution},
author = {Men'endez, H'ector D and Vindel, Rafael and Camacho, David},
year = {2014},
date = {2014-01-01},
booktitle = {Computational Collective Intelligence. Technologies and Applications},
pages = {262--271},
publisher = {Springer International Publishing},
keywords = {Behaviour, Clustering, Time Series, Videogames},
pubstate = {published},
tppubtype = {incollection}
}
|
16. | Menendez, Hector D; Barrero, David F; Camacho, David A Co-Evolutionary Multi-Objective approach for a K-adaptive graph-based clustering algorithm Inproceedings Evolutionary Computation (CEC), 2014 IEEE Congress on, pp. 2724–2731, IEEE 2014. BibTeX | Tags: Clustering, Co-Evolutionary Algorithms, Genetic Algorithms, Manifold, Multi-Objective Algorithms @inproceedings{menendez2014co,
title = {A Co-Evolutionary Multi-Objective approach for a K-adaptive graph-based clustering algorithm},
author = {Menendez, Hector D and Barrero, David F and Camacho, David},
year = {2014},
date = {2014-01-01},
booktitle = {Evolutionary Computation (CEC), 2014 IEEE Congress on},
pages = {2724--2731},
organization = {IEEE},
keywords = {Clustering, Co-Evolutionary Algorithms, Genetic Algorithms, Manifold, Multi-Objective Algorithms},
pubstate = {published},
tppubtype = {inproceedings}
}
|
15. | Okazaki, Shintaro ; D'iaz-Mart'in, Ana M; Rozano, Mercedes ; Men'endez-Benito, H'ector David How to mine brand Tweets: Procedural guidelines and pretest Journal Article International Journal of Market Research, 56 (4), pp. 467–488, 2014. BibTeX | Tags: Classification, Marketing, Twitter @article{okazaki2014mine,
title = {How to mine brand Tweets: Procedural guidelines and pretest},
author = {Okazaki, Shintaro and D'iaz-Mart'in, Ana M. and Rozano, Mercedes and Men'endez-Benito, H'ector David},
year = {2014},
date = {2014-01-01},
journal = {International Journal of Market Research},
volume = {56},
number = {4},
pages = {467--488},
publisher = {The Market Research Society},
keywords = {Classification, Marketing, Twitter},
pubstate = {published},
tppubtype = {article}
}
|
14. | Vindel, Rafael ; Men'endez, H'ector D; Camacho, David A survey in Convergence Technologies for Videogames using Data Mining Journal Article 2014. BibTeX | Tags: Convergence Technologies, Videogames @article{vindel2014survey,
title = {A survey in Convergence Technologies for Videogames using Data Mining},
author = {Vindel, Rafael and Men'endez, H'ector D and Camacho, David},
year = {2014},
date = {2014-01-01},
keywords = {Convergence Technologies, Videogames},
pubstate = {published},
tppubtype = {article}
}
|
13. | Men'endez, H'ector D Genetic graph-based in clustering applied to static and streaming data analysis PhD Thesis 2014. BibTeX | Tags: Clustering, Co-Evolutionary Algorithms, Genetic Algorithms, Multi-Objective Algorithms, Streaming Clustering @phdthesis{menendez2014geneticb,
title = {Genetic graph-based in clustering applied to static and streaming data analysis},
author = {Men'endez, H'ector D},
year = {2014},
date = {2014-01-01},
keywords = {Clustering, Co-Evolutionary Algorithms, Genetic Algorithms, Multi-Objective Algorithms, Streaming Clustering},
pubstate = {published},
tppubtype = {phdthesis}
}
|
2013
|
12. | Vindel, Rafael ; Men'endez, H'ector D; Camacho, David Combinando Series Temporales y Clustering para extraer Perfiles Evolutivos de Jugadores Journal Article 2013. BibTeX | Tags: Behaviour, Clustering, Time Series, Videogames @article{vindelcombinando,
title = {Combinando Series Temporales y Clustering para extraer Perfiles Evolutivos de Jugadores},
author = {Vindel, Rafael and Men'endez, H'ector D and Camacho, David},
year = {2013},
date = {2013-10-11},
keywords = {Behaviour, Clustering, Time Series, Videogames},
pubstate = {published},
tppubtype = {article}
}
|
11. | Men'endez, H'ector ; Bello-Orgaz, Gema ; Camacho, David Extracting behavioural models from 2010 fifa world cup Journal Article Journal of Systems Science and Complexity, 26 (1), pp. 43–61, 2013. BibTeX | Tags: Behaviour, Clustering, Fifa, Soccer, Sports @article{menendez2013extracting,
title = {Extracting behavioural models from 2010 fifa world cup},
author = {Men'endez, H'ector and Bello-Orgaz, Gema and Camacho, David},
year = {2013},
date = {2013-01-01},
journal = {Journal of Systems Science and Complexity},
volume = {26},
number = {1},
pages = {43--61},
publisher = {Academy of Mathematics and Systems Science, Chinese Academy of Sciences},
keywords = {Behaviour, Clustering, Fifa, Soccer, Sports},
pubstate = {published},
tppubtype = {article}
}
|
10. | Men'endez, H'ector D; Plaza, Laura ; Camacho, David A genetic graph-based clustering approach to biomedical summarization Inproceedings Proceedings of the 3rd International Conference on Web Intelligence, Mining and Semantics, pp. 10, ACM 2013. BibTeX | Tags: Automatic Summarization, Biomedical, Clustering, Genetic Algorithms, Graph-based @inproceedings{menendez2013genetic,
title = {A genetic graph-based clustering approach to biomedical summarization},
author = {Men'endez, H'ector D and Plaza, Laura and Camacho, David},
year = {2013},
date = {2013-01-01},
booktitle = {Proceedings of the 3rd International Conference on Web Intelligence, Mining and Semantics},
pages = {10},
organization = {ACM},
keywords = {Automatic Summarization, Biomedical, Clustering, Genetic Algorithms, Graph-based},
pubstate = {published},
tppubtype = {inproceedings}
}
|
9. | Men'endez, H'ector D; Barrero, David F; Camacho, David A multi-objective genetic graph-based clustering algorithm with memory optimization Inproceedings Evolutionary Computation (CEC), 2013 IEEE Congress on, pp. 3174–3181, IEEE 2013. BibTeX | Tags: Clustering, Genetic Algorithms, Manifold, Multi-Objective Algorithms @inproceedings{menendez2013multi,
title = {A multi-objective genetic graph-based clustering algorithm with memory optimization},
author = {Men'endez, H'ector D and Barrero, David F and Camacho, David},
year = {2013},
date = {2013-01-01},
booktitle = {Evolutionary Computation (CEC), 2013 IEEE Congress on},
pages = {3174--3181},
organization = {IEEE},
keywords = {Clustering, Genetic Algorithms, Manifold, Multi-Objective Algorithms},
pubstate = {published},
tppubtype = {inproceedings}
}
|
8. | Bello, Gema ; Men'endez, H'ector ; Okazaki, Shintaro ; Camacho, David Extracting collective trends from twitter using social-based data mining Incollection Computational Collective Intelligence. Technologies and Applications, pp. 622–630, Springer Berlin Heidelberg, 2013. BibTeX | Tags: Classification, Clustering, Social Mining, Twitter @incollection{bello2013extracting,
title = {Extracting collective trends from twitter using social-based data mining},
author = {Bello, Gema and Men'endez, H'ector and Okazaki, Shintaro and Camacho, David},
year = {2013},
date = {2013-01-01},
booktitle = {Computational Collective Intelligence. Technologies and Applications},
pages = {622--630},
publisher = {Springer Berlin Heidelberg},
keywords = {Classification, Clustering, Social Mining, Twitter},
pubstate = {published},
tppubtype = {incollection}
}
|
7. | Men'endez, H'ector David ; Llorente, Jos'e Luis The Combination of Graph Theory and Unsupervised Learning Applied to Social Data Mining Incollection Graph Theory: New Research, pp. 155–184, NOVA Publishers, 2013. Links | BibTeX | Tags: Clustering, Graph-based, Network, Social Mining @incollection{menendez2013combination,
title = {The Combination of Graph Theory and Unsupervised Learning Applied to Social Data Mining},
author = {Men'endez, H'ector David and Llorente, Jos'e Luis},
url = {http://freedevelop.org/wp-content/uploads/menendezLlorente.pdf},
year = {2013},
date = {2013-01-01},
booktitle = {Graph Theory: New Research},
pages = {155--184},
publisher = {NOVA Publishers},
keywords = {Clustering, Graph-based, Network, Social Mining},
pubstate = {published},
tppubtype = {incollection}
}
|
2012
|
6. | Men'endez, H'ector ; Camacho, David A genetic graph-based clustering algorithm Incollection Intelligent Data Engineering and Automated Learning-IDEAL 2012, pp. 216–225, Springer, 2012. BibTeX | Tags: Clustering, Genetic Algorithms, Graph-based @incollection{menendez2012genetic,
title = {A genetic graph-based clustering algorithm},
author = {Men'endez, H'ector and Camacho, David},
year = {2012},
date = {2012-01-01},
booktitle = {Intelligent Data Engineering and Automated Learning-IDEAL 2012},
pages = {216--225},
publisher = {Springer},
keywords = {Clustering, Genetic Algorithms, Graph-based},
pubstate = {published},
tppubtype = {incollection}
}
|
5. | Men'endez, H'ector ; Bello-Orgaz, Gema ; Camacho, David Features selection from high-dimensional web data using clustering analysis Inproceedings Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics, pp. 20, ACM 2012. BibTeX | Tags: Clustering, Features Selection @inproceedings{menendez2012features,
title = {Features selection from high-dimensional web data using clustering analysis},
author = {Men'endez, H'ector and Bello-Orgaz, Gema and Camacho, David},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics},
pages = {20},
organization = {ACM},
keywords = {Clustering, Features Selection},
pubstate = {published},
tppubtype = {inproceedings}
}
|
4. | Bello-Orgaz, Gema ; Men'endez, H'ector D; Camacho, David Adaptive k-means algorithm for overlapped graph clustering Journal Article International journal of neural systems, 22 (05), pp. 1250018, 2012. BibTeX | Tags: Clustering, Community Detection, Genetic Algorithms, Overlapping @article{bello2012adaptive,
title = {Adaptive k-means algorithm for overlapped graph clustering},
author = {Bello-Orgaz, Gema and Men'endez, H'ector D and Camacho, David},
year = {2012},
date = {2012-01-01},
journal = {International journal of neural systems},
volume = {22},
number = {05},
pages = {1250018},
publisher = {World Scientific Publishing Company},
keywords = {Clustering, Community Detection, Genetic Algorithms, Overlapping},
pubstate = {published},
tppubtype = {article}
}
|
3. | Men'endez, H'ector D A genetic approach to the graph and spectral clustering problem Journal Article 2012. BibTeX | Tags: Clustering, Genetic Algorithms, Graph-based, Spectral Clustering @article{menendez2012geneticb,
title = {A genetic approach to the graph and spectral clustering problem},
author = {Men'endez, H'ector D},
year = {2012},
date = {2012-01-01},
keywords = {Clustering, Genetic Algorithms, Graph-based, Spectral Clustering},
pubstate = {published},
tppubtype = {article}
}
|
2011
|
2. | Bello, Gema ; Men'endez, H'ector ; Camacho, David Using the clustering coefficient to guide a genetic-based communities finding algorithm Incollection Intelligent Data Engineering and Automated Learning-IDEAL 2011, pp. 160–169, Springer, 2011. BibTeX | Tags: Clustering, Clustering Coefficient, Community Detection, Genetic Algorithms @incollection{bello2011using,
title = {Using the clustering coefficient to guide a genetic-based communities finding algorithm},
author = {Bello, Gema and Men'endez, H'ector and Camacho, David},
year = {2011},
date = {2011-01-01},
booktitle = {Intelligent Data Engineering and Automated Learning-IDEAL 2011},
pages = {160--169},
publisher = {Springer},
keywords = {Clustering, Clustering Coefficient, Community Detection, Genetic Algorithms},
pubstate = {published},
tppubtype = {incollection}
}
|
1. | Jim'enez-Diaz, Guillermo ; Men'endez, H'ector D; Camacho, David ; Gonz'alez-Calero, Pedro A Predicting performance in team games Journal Article II for Systems, C. Technologies of Information, and Communication, ICAART, pp. 401–406, 2011. BibTeX | Tags: Behaviour, Classification, Clustering, Videogames @article{jimenez2011predicting,
title = {Predicting performance in team games},
author = {Jim'enez-Diaz, Guillermo and Men'endez, H'ector D and Camacho, David and Gonz'alez-Calero, Pedro A},
year = {2011},
date = {2011-01-01},
journal = {II for Systems, C. Technologies of Information, and Communication, ICAART},
pages = {401--406},
keywords = {Behaviour, Classification, Clustering, Videogames},
pubstate = {published},
tppubtype = {article}
}
|