SAC 2018 is offering 5 half-day tutorials on Monday April 9, 2018. Tutorials are open for those who registered for them. Handouts will be available online right before the conference. No printed handouts are provided during the tutorials. Please bring your copies of the handouts (printed or electronic). Lunch tickets will be issues for registered attendees. For questions or inquiries about the tutorials, please contact the Tutorials Chairs.
University of Pau & Pays Adour
University of Pau & Pays Adour
|Salle Ernest Gabard||Auditorium Alphonse de Lamartine||Salle Adolphe Alphand|
T#1 Developing Fashion Personalized Applications using Recommendation Systems and Data Mining Techniques
Evandro Costa, Hemilis Rocha, Emanuele Tuane, and Artur Maia
AM Coffee Break
T#2 BigData Platform - Real-time recommendation models design and development
Vincent Moreno, and Romain Roquefere
AM Coffee Break
T#3 Standard-based IoT platform for cross-domain interoperability
Mahdi Ben Alaya, Khalil Drira, and Ghada Gharbi
AM Coffee Break
|12:30pm||Social Luncheon for attendees who registered for the Tutorials.
The luncheon event will be held at the conference venue, and lunch tickets will be issued.
|Salle Aristide de Monpezat|
T#4 Web Security Vulnerabilities: Challenges and Solutions
PM Coffee Break
T#5 IBM Cloud Platform: IOT and Watson
PM Coffee Break
The aim of this tutorial is to bring together researchers and practitioners working on various aspects of recommender systems for fashion domain, including data-driven and knowledge based approaches. Hence, this tutorial aims to cover both the theory and practice of Recommender Systems, providing a systematic study and techniques for making personalized recommendations, including their main concepts and approaches with a detailed taxonomy, as well as illustrating them with practical examples. Thus, the first part of the tutorial introduces concepts, methods and techniques associated with artificial intelligence techniques focused on recommender systems and data mining/machine learning. The second part covers aspects of constructing fashion personalized applications of recommendation systems, giving participants the opportunity to know the potential of such systems in fashion domain, including demonstration of a clothing personalized recommender system.
Evandro de Barros Costa is Associate Professor in the Computing Institute at Federal University of Alagoas, Brazil. He obtained his BSc degree in computer science from Federal University of Paraiba (UFPB), Brazil. Later, he received his Master degree in Electrical Engineering – Information Processing, from UFPB, Brazil, and his PhD in Electrical Engineering – Information Processing, from the same university. He coordinates a research group named TIPS (Technologies equipped with Intelligence, Personalization and Socialization). His research interests include Knowledge Representation and Reasoning, Machine Learning and Data Mining, Personalized Recommender Systems, Intelligent Tutoring Systems, Multiagent Systems, Social and Semantic Web. He teaches disciplines, such as Artificial Intelligence, Machine Learning and Data Mining, Knowledge Discovery in Databases, among others. He has published various papers in international conferences and journals. He has been on the Technical Program Committee of many conferences, such as UMAP (Conference on User Modelling, Adaptation and Personalization), Web Intelligence, ITS (Intelligent Tutoring Systems), AIED (Artificial Intelligence in Education), BRACIS (Brazilian Conference on Intelligent System), and has been reviewer on some international journals, such as Information Science, IEEE Transactions on Education, IEEE Transactions on Learning Technologies, International Journal of Web Based Communities, Expert Systems with Applications. He advised 6 PhD thesis and 53 Master Thesis. He has co- authored or presented tutorials in conferences, such as the International Conference on Artificial Intelligence in Education (AIED-2007 http://iaied.org/media/conferences/past/AIED2007/wt.html ), the Brazilian Symposium on Informatics and Education (see http://cbie2012.nce.ufrj.br/jaie/minicursos.html, http://perseus.nied.unicamp.br/joomla/index.php/jaie.html, and http://www.br-ie.org/pub/index.php/pie/issue/view/146), the Brazilian Symposium on Multimedia Systems and Web, among others. Evandro Costa has also been organizer, co-organizer of conferences and workshops in his research field, such as the Intelligent Tutoring System international conference (ITS 2002), the Brazilian Symposium on Artificial Intelligence, the Brazilian Symposium on Informatics in Education, the Workshop on Architectures and Methodologies for Building Agent-based Learning Environments and the First Brazilian Workshop on Semantic Web and Education. He has participated in various international and national research projects. He has given invited talks in various countries, e.g. Brazil, Canada, Portugal, Spain, France, etc.
Hemilis Rocha is a teacher of Informatics at Federal Institute of Alagoas, Brazil. She is the leader of the of the Research Group named TEIA (Emergent Technologies in Artificial Intelligence). She received a B.S. degree in Information System from the Faculty of Alagoas (FAL), Brazil, in 2009, an M.Sc. degree Knowledge Computational Modeling in from the Federal University of Alagoas, Brazil, in 2012. Her research interests include Knowledge Representation and Reasoning, Personalized Recommender Systems, Intelligent Tutoring Systems. She has published papers in international conferences, including Frontiers in Education (FIE), International Conference on Enterprise Information Systems (ICEIS), World Conference on Information Systems and Technologies (WorldCist), Edulearn, Internet/WWW. She participated of the Technical Program Committee of WorldCist2016 Conference. She has co-authored or presented tutorial in conferences, such as the Brazilian Symposium on Informatics and Education (see http://www.br-ie.org/pub/index.php/pie/issue/view/146). She has taught disciplines, such as Artificial Intelligence, Programming, Statistics and Probability.
Emanuele Silva is a graduate student of Knowledge Computational Modeling at Federal University of Alagoas (UFAL), Brazil. She received a B.S. degree in Computer Science from UFAL in 2016. In 2014 she participated of Science without Borders that is a large scale nationwide scholarship program funded by the Brazilian federal government, studying one year in the Arizona State University. This program seeks to expand the initiatives of science and technology through international mobility of undergraduate and graduate students and researchers. She worked as undergraduate teaching assistant (UGTA) in Calculus I and Design and Analysis of Algorithms. Currently, she is a member of the Research Group named TIPS (Technologies equipped with Intelligence, Personalization and Socialization) and her research interests include Intelligent Tutoring Systems, Knowledge Representation and Reasoning, Personalized Recommender Systems, Machine Learning and Data Mining. She has published papers in international conferences, including Frontiers in Education (FIE), International Conference on Enterprise Information Systems (ICEIS), World Conference on Information Systems and Technologies (WorldCist), and International Conference on Intelligent Tutoring Systems (ITS).
Artur Maia is a Master student in Computing in the Federal University of Alagoas (UFAL), Brazil. He received a B.S. degree in Computer Science, in 2016, from UFAL, Brazil. He participated in scientific initiation projects in the area of software engineering. In 2017, he completed a Swift programming language course for iOS devices offered by IBM in association with the Eldorado Research institute. He is working on a teaching internship in the field of Artificial Intelligence. His research interests include Personalized Recommender Systems, Machine Learning, Data Mining, Knowledge Representation and Reasoning, Software Engineering, Natural Language Processing and Database.
This tutorial is intended to provide a global overview of specialized machine learning models in order to design and develop real-time recommendations engines.
During the tutorial, an advance big data platform (Hupi platform) will be introduced. This platform include a rich set of components (i.e. spark 2.1 framework and the scala 2.11 language, etc.) intended to ensure a complete data processing cycle while respecting real time constraints.
During the tutorial, the following phases will be illustrated:
- The collection of any data set, of any size, from any sources, including data flows
- The storage of high volume of data on a cluster environment guaranteeing high performance
- The distributed computation for real time analysis by machine learning algorithms to generate well-adapted recommendations
- The visualization functionalities allowing to check the results of the recommendations and to track their performance
- The automation module to push the results to external systems in real time.
Based on these components several recommendation models will be designed and implemented, including several styles such as ALS, item-item, user-item, etc. An event-oriented approach will be followed based on specific features in order to implement real-time reactive services.
Moreover, secured access to Restful APIs will be studied in order to provide real- time recommendation systems for interactive environments, such as e-commerce systems.
Vincent Moreno holds a Diploma and Master degree in Informatics and a MBA in Enterprise Management. He has worked over 15 years in different companies from the public, energy, financial, and industry sectors, playing different roles as a data architect, project manager, IT consultant, finance IT architect, or IT executive. He has coordinated several research and innovation activities in various research projects.
Romain Roquefere holds a Diploma in Electric Engineering and a Master degree in Business administration. He has worked in different IT and BD companies and consulting firms. He has experience as an IT engineer, data analyser, business development and strategic planning, project manager, responsible for strategic planning activities, ad IT consultant, among others.
The tutorial will present the IoT vision, challenges, and efforts achieved by the standardization bodies to design a globally agreed IoT service platform. The oneM2M standard will be introduced as a promising solution for IoT cross-domain interoperability. The participants will be asked to follow practical sessions to learn how to integrate heterogeneous devices based on the oneM2M API, and quickly develop oneM2M applications in smart building use cases.
Dr. Mahdi BEN ALAYA is Founder and CEO of Sensinov. He obtained a Ph.D in systems architectures from the Federal University of Toulouse in France. He is Vice Chairman of the oneM2M Testing Group. He is co-founder and technical manager of the open source project OM2M at the Eclipse foundation. He is selected as expert by ETSI to develop interoperability tests for various IoT standards and to develop extensions and conformance tests for SAREF ontology. He organized various schools on IoT in France,Taiwan and Korea. He initiated and managed several R&D projects at LAAS-CNRS and Sensinov including H2020-LSP5- AUTOPILOT, ITEA2-USENET and ITEA2-A2NETS. He has authored more than 20 publications in international journals and conferences and more than 40 contributions in M2M standards. firstname.lastname@example.org
Dr. Khalil DRIRA, Ph.D. Univ. of Toulouse, is Research Director, a full-time research position at the French National Center for Scientific Research (CNRS). His research interests include formal design, implementation, and provisioning of distributed communicating systems and cooperative networked services. His research activity addresses different topics in this field focusing on model-based analysis and design of correctness properties including robustness, adaptability and reconfiguration. He is or has been involved in different European and French R&D projects (FP6, FP7, ITEA, H2020, PIA, ANR, …) in the field of distributed system engineering, collaborative activities, distributed systems, IoT/M2M and software architectures. He has organized and chaired several international conferences including IEEE-WETICE, ECSA, SESOS. He has been guest editors of different journal special issued including JSS, FGCS, Wiley Concurrency and Computation. More information is available on: http://homepages.laas.fr/khalil
Dr. Ghada GHARBI obtained a Ph.D in Networks and Telecom from the Federal University of Toulouse in France. She is selected as expert by the ETSI to develop an interoperable devkit system offering testing and debugging tools for IoT ecosystem. She is committer in the open source project OM2M at the Eclipse foundation. She was contractual professor at INSA of Toulouse and participated in the constitution and the establishment of a training unit around the IoT. She also participated in the organization of several schools on IoT worldwide. email@example.com
We rely on web applications to perform many useful activities. Despite the awareness over the past decade on secure programming practices and tools on vulnerability discovery in the implementation, we still observe the presence of known vulnerabilities. Both the client sides and server sides are responsible to let attackers exploiting vulnerabilities with malicious inputs. Web services are used as integral part of web applications and they remain vulnerable when not implemented securely. Given that an understanding of the common vulnerabilities for applications and services are essential for practitioners to tame the unsecured web.
In this tutorial, we will provide an overview of common vulnerabilities for web applications and web services, followed by common techniques useful to combat against security threats. In particular, we will discuss implementation level vulnerabilities for applications (e.g., code injection, object injection, clickjacking) along with a popular mitigation approach known as security testing. We also focus on web service security vulnerabilities and exploitation techniques followed by best practices.
Dr. Hossain Shahriar is an Assistant Professor of Information Technology at Kennesaw State University, Georgia, USA since Fall 2012. He received his PhD in Computing from Queen’s University, Canada in 2012. His research interests include cyber security, particularly application (web, mobile) security vulnerabilities and mitigation approaches, risk assessment techniques, and metric-based attack detection. He also teaches cyber security courses such as Ethical Hacking. Dr. Shahriar has published more than 70 peer reviewed research articles on various topics within cyber security in International Journals, Conferences, and Book Chapters including ACM SAC, ACM SIN, IEEE HASE, IEEE COMPSAC, Computer & Security, and ACM Computing Survey. He has been a reviewer for many international journals and PC member of international conferences on software, computer, and application security. He served as Fast Abstract Chair in IEEE COMPSAC 2015-2017, Program Chair in ACM SIN 2016, Publicity Chair in IEEE COMPSAC 2017, Publication Chair in ACM SAC 2017 and 2018, and Student Research Competition Chair in ACM SAC 2016. Currently, he is also a Co-PI of a funded research project from National Science Foundation on Secure Mobile Application Development aiming to develop open source labware resources. Dr. Shahriar is a professional member of ACM, SIGAPP, and IEEE.
This tutorial demonstrates a Raspberry PI device connected to the Watson IoT IBM Cloud platform. This system could, for example, be used as a domotic system: the Raspberry PI is a MQTT client receiving message to take pictures and these are then stored on the IBM Cloud platform and sent to the Watson visual recognition service hosted by the IBM Cloud platform. The half day is decomposed in 2 steps. In a first step, a presentation and demonstration of the IBM Cloud of an existing system connecting a Raspberry PI and, in a second step, a hands-on session where the participants creates on their own IBM Cloud platform account an extension of the existing system using a NodeRed editor calling the Watson visual recognition service.
Yves Holvoet is a Software Engineering Specialist with Engineering diploma and a major in languages theory. He Did some applied research on formal specifications and formal proof of programs before joining Rational in 1989 where he worked on methods, processes and tools, participated in task forces defining the UML (Unified Modeling Language) and did some consulting in large companies (telecom, aviation, finance) all over the world in 16 countries on 4 continents.