March 2019 - computational.science

HPBench 2019 - CFP (ONLY 10 DAYS LEFT)
by Samar Aseeri 21 Mar '19

21 Mar '19

Dear Sir, dear Madam, Submission deadline has been extended to April 1st. Accepted papers will be published at IEEE. Best regards ========================================================================== CALL FOR PAPERS The 6th Special Session on High Performance Computing for Application Benchmarking and Optimization (HPBench 2019) As part of the International Conference on High Performance Computing & Simulation (HPCS 2019) http://hpcs2019.cisedu.info/ or http://conf.cisedu.info/rp/hpcs19 Dublin, Ireland ========================================================================== Benchmarking is an essential aspect of modern high performance computing and computational science, and as such, it provides a means for quantifying and comparing the performance of different computer systems. With a large combination of aspects to benchmark, all the way from the capability of a single core, to cluster configuration, and to various software configurations, the benchmarking process is more of an art than science. However, the results of this process drive modern science and are vital for the community to draw sensible conclusions on the performance of applications and systems. This special session focuses on research work aimed at benchmarking modern parallel and distributed systems for addressing a number of real world problems. As such, contributions concerning the definition of new open platforms, new benchmarks to match modern architectural evolutions, studies on the aspects of benchmarking different aspects of systems (from raw runtime performance to energy consumption to energy consumed per data movement) and mathematical foundations of benchmarking are sought. IMPORTANT DATES : Papers Due: 1 April 2019 - Extended Author Notification: 22 April 2019 Camera-Ready Submission: 8 May 2019 Conference Dates: 15-19 July 2019 TOPICS : The HPBench topics of interest include, but are not limited to -Open Platforms for Parallel and Distributed Application Benchmarking and Optimization -Benchmarking on the Cloud -Benchmarking of Clusters, Supercomputers, and large-scale systems -Benchmarking the Performance of I/O -Benchmarking of Energy and Energy Efficiency -Benchmarking Web Services -Virtualization for Distributed Benchmarking -Data Distribution for Benchmarking -Performance results of benchmarks on modern platforms -Scalability Aspects of Benchmarking Parallel Applications on Parallel and Distributed Systems -Benchmarking of Parallel Scientific and Business Applications -Performance of Benchmarking Applications (Eg: NAS parallel benchmarks) -Techniques, frameworks and results concerning the benchmarking of library packages -Tools and frameworks for performance modeling systems and applications -Tools and frameworks for simulation, measurement and monitoring -Performance Measurements, Monitoring, Modeling and Simulation -Domain-specific benchmarks and applications (such as image processing, pattern recognition, cryptography, biometrics, differential equation solvers, signal processing and alike) -Mathematical Foundations of Benchmarking, Metrics and Heuristics GENERAL CHAIRS : - Samar Aseeri, King Abdullah University of Science and Technology, Saudi Arabia - Luigi Iapichino, Leibniz Supercomputing Centre (LRZ), Germany - Laurent Lefevre, INRIA, ENS Lyon, France TECHNICAL PROGRAM COMMITTEE: - Cosimo Anglano, Universitá del Piemonte Orientale, Italy - Daniel Balouek-Thomert, Rutgers University, USA - Fabio Baruffa, Intel, Germany - Suren Byna, Lawrence Berkeley National Laboratory, California, USA - Jesus Carretero, Universidad Carlos III de Madrid, Spain - Douglas Doerfler, Lawrence Berkeley National Laboratory, California, USA - Zhiyi Huang, University of Otago, New Zealand - Clay Hughes, Sandia National Laboratories, New Mexico, USA - Aleksandar Ilic, Universidade de Lisboa, Portugal - Bok Jik Lee, Gwangju Institute of Science and Technology, Korea - Ravi Reddy Manumachu, University College Dublin, Ireland - Dana Petcu, West University of Timisoara, Romania - Ivan Rodero, Rutgers University, USA - Gudula Rünger, Technische Universität Chemnitz, Germany - Domenico Talia, Università della Calabria, Rende, Italy ********************************************************************* For more information see http://hpcs2019.cisedu.info/2-conference/special-sessions/session02-hpbench Kind Regards -- Samar Aseeri, PhD Computational Scientist Extreme Computing Research Center (ECRC) Building 1 -Office: 0128 *King Abdullah University of Science & Technology* Thuwal, Saudi Arabia Email: samar.aseeri(a)kaust.edu.sa -- This message and its contents, including attachments are intended solely for the original recipient. If you are not the intended recipient or have received this message in error, please notify me immediately and delete this message from your computer system. Any unauthorized use or distribution is prohibited. Please consider the environment before printing this email.

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[Final Deadline Extension] The Third International Workshop on Parallel and Distributed Data Mining (WPDM 2019)
by Massimo CAFARO 16 Mar '19

16 Mar '19

WPDM 2019 The Third International Workshop on Parallel and Distributed Data Mining (WPDM 2019) http://sara.unisalento.it/~cafaro/WPDM2019/ CALL FOR PAPERS The Third Workshop on Parallel and Distributed Data Mining (WPDM 2019) will be held in conjunction with The 19th International Conference on Computational Science and Its Applications (ICCSA 2019), http://www.iccsa.org Saint Petersburg University, Saint Petersburg, Russia July 1-4 2019 Final deadline for submissions extended to: April 7, 2019 SCOPE AND OBJECTIVES The Workshop on Parallel and Distributed Data Mining is an international forum which brings together researchers and practitioners working on different high-performance aspects of data mining algorithms, enabling novel applications. Data mining techniques and algorithms to process huge amount of data in order to extract useful and interesting information have become popular in many different contexts. Algorithms are required to make sense of data automatically and in efficient ways. Nonetheless, even though sequential computer systems performance is improving, they are not suitable to keep up with the increase in the demand for data mining applications and the data size. Moreover, the main memory of sequential systems may not be enough to hold all the data related to current applications. Therefore, there is an increasing interest in the design and implementation of parallel data mining algorithms. On parallel computers, by exploiting the vast aggregate main memory and processing power of processors and accelerators, parallel algorithms can easily address both the running time and memory requirement issues. Anyway, parallelizing existing algorithms in order to achieve good performance and scalability with regard to massive datasets is not trivial. Indeed, it is of paramount importance a good data organization and decomposition strategy in order to balance the workload while minimizing data dependences. Another concern is related to minimizing synchronization and communication overhead. Finally, I/O costs should be minimized as well. The Workshop will allow exchanging ideas and results related to on-going research, focusing on high-performance aspects of data mining algorithms and applications. Creating breakthrough parallel algorithms for high-performance data mining applications requires addressing several key computing problems which may lead to novel solutions and new insights in interdisciplinary applications. The focus of the workshop is on all forms of advances in high-performance data mining algorithms and applications, and related topics. The WPDM Workshop topics include (but are not limited to) the following: - Parallel data mining algorithms using MPI and/or OpenMP - Parallel data mining algorithms targeting GPUs and many-cores accelerators - Parallel data mining applications exploiting FPGA - Distributed data mining algorithms - Benchmarking and performance studies of high-performance data mining applications - Novel programming paradigms to support high-performance computing for data mining - Performance models for high-performance data mining applications and middleware - Programming models, tools, and environments for high-performance computing in data mining - Caching, streaming, pipelining, and other optimization techniques for data management in high-performance computing for data mining INSTRUCTIONS FOR PAPER SUBMISSIONS You are invited to submit original and unpublished research works on above topics. Submitted papers must not have been published or simultaneously submitted elsewhere. The submitted paper must be between 10 to 16 pages long and formatted according to the Springer LNCS (Lecture Notes in Computer Science) rules, Guidelines and templates can be found at the url http://www.springer.com/it/computer-science/lncs/conference-proceedings-gui… To submit a paper, please connect to the Submission site from the link available at the ICCSA 2019 web site: http://ess.iccsa.org. Only papers submitted through the electronic system and strictly adhering to the relevant format will be considered for reviewing and publication. Please pay attention, when submitting your contribution to the workshop, to select the right entry in the listbox shown in the submission form. CONFERENCE POLICY By submitting the paper to ICCSA conference, all authors agree to abide by all ICCSA conference paper submission, publication and presentation policies. Namely, authors confirm that the work is original, has not appeared in literature in any form in the past and will not be submitted to any other venue concurrently with ICCSA submission or until it appears in ICCSA proceedings (in the case of acceptance). Furthermore, upon paper acceptance, authors agree to transfer copyright on the accepted paper to ICCSA, and one of the authors will register the paper and present the paper at the event. No paper withdrawals can be accepted after Conference pre-registration date or within three months of the actual event, whichever date comes first. Paper withdrawal request can be only accepted in writing through email, letter or fax to conference organizers. The conference has no responsibility for any intentional or accidental misuse, misinterpretation, or failure to follow above rules and conditions and holds no legal, civil or other responsibility for opinions, content or utilization of any methods/algorithms expressed in the Conference Proceedings. If you have any questions about paper submission or the workshop, please contact the workshop organisers. IMPORTANT DATES April 7, 2019: Deadline for paper submission April 24, 2019: Notification of Acceptance. May 8, 2019: Early-bird Registration ends. May 8, 2019: Submission deadline for the final version of the Papers July 1-4, 2019: ICCSA 2019 Conference WORKSHOP ORGANIZERS Massimo Cafaro University of Salento, Italy Phone: +39 0832 297371 Fax: +39 0832 297235 Email: massimo.cafaro(a)unisalento.it Italo Epicoco University of Salento, Italy Phone: +39 0832 297235 Fax: +39 0832 297235 Email: italo.epicoco(a)unisalento.it Marco Pulimeno University of Salento, Italy Phone: +39 0832 297371 Fax: +39 0832 297235 Email: marco.pulimeno(a)unisalento.it Giovanni Aloisio University of Salento & Euro Mediterranean Center on Climate Change Foundation, Italy Phone: +39 334 6501704 Fax: +39 0832 297235 Email: giovanni.aloisio(a)unisalento.it All submitted papers will be reviewed by the workshop technical program committee members. International Program Committee: Alfredo Cuzzocrea, University of Trieste and ICAR-CNR, Italy Bronis R. de Supinski, Lawrence Livermore National Laboratory, USA Giuseppe Di Fatta, University of Reading, UK Ann Gordon-Ross, University of Florida, USA Kenli Li, Hunan University, China Donato Malerba, University of Bari, Italy Barbara Masucci, University of Salerno, Italy Mitsunori Ogihara, University of Miami, USA Takahiko Shintani, The University of Electro-Communications , Japan Domenico Talia, University of Calabria, Italy Paolo Trunfio, University of Calabria, Italy Jeffrey D. Ullman, Stanford University, USA Laurence T. Yang, St Francis Xavier University, Canada - ************************************************************************************ Massimo Cafaro, Ph.D. Associate Professor Dept. of Engineering for Innovation University of Salento, Lecce, Italy Via per Monteroni 73100 Lecce, Italy Voice/Fax +39 0832 297371 Web http://sara.unisalento.it/~cafaro E-mail massimo.cafaro(a)unisalento.it cafaro(a)ieee.org cafaro(a)acm.org CMCC Foundation Euro-Mediterranean Center on Climate Change Via Augusto Imperatore, 16 - 73100 Lecce massimo.cafaro(a)cmcc.it ************************************************************************************

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Job Openings: Professor / Associate Professor / Assistant Professor (Computer Science) at Hong Kong Baptist University
by COMP HKBU 15 Mar '19

15 Mar '19

The Department of Computer Science of Hong Kong Baptist University, presently offers BSc, MSc, MPhil, and PhD programmes, now seeks outstanding applicants for the following faculty positions on tenure-track. The appointees are expected to perform high-impact research; to teach and manage programmes at undergraduate and postgraduate levels, as well as to contribute to professional and institutional services. Collaboration with other faculty members in research and teaching is also expected. They will be encouraged to collaborate with colleagues within the Department to contribute to two special thematic applications including (a) health informatics and (b) secure and privacy-aware computing, and/or outside the Department to contribute to interdisciplinary research projects under our University’s Research Cluster on Data Analytics and A.I. in X. Applicants should possess a PhD degree in Computer Science, Computer Engineering, Information Systems, or a related field, and sufficiently demonstrate abilities to conduct high-quality research in one of the Department’s key research areas: (i) computational intelligence, (ii) databases and information management, (iii) networking and systems, and (iv) pattern recognition and machine learning. Applicants should also demonstrate strong commitment to undergraduate and postgraduate teaching in computer science and/or information systems, possess track record of innovative research and high-impact publications, and demonstrate the ability to bid for and pursue externally-funded research programmes. Initial appointment will be made on a fixed-term contract of three years. Re-appointment thereafter is subject to mutual agreement and availability of funding. For enquiry, please contact Dr. William Cheung, Head of Department (email: william(a)comp.hkbu.edu.hk) More information about the Department can be found at http://www.comp.hkbu.edu.hk . Rank and salary will be commensurate with qualifications and experience. Application Procedure: Applicants are invited to submit their applications at the HKBU e-Recruitment System (jobs.hkbu.edu.hk). Applicants are requested to send in samples of publications, preferably three best ones out of their most recent publications. Applicants should also request two referees to send in confidential letters of reference, with PRnumber (stated above) quoted on the letters, to the Personnel Office (email: recruit(a)hkbu.edu.hk) direct. All application materials including publication samples, scholarly/creative works will be destroyed after completion of the recruitment exercise. Details of the University's Personal Information Collection Statement can be found at http://pers.hkbu.edu.hk/pics. The University reserves the right not to make an appointment for the posts advertised, and the appointment will be made according to the terms and conditions applicable at the time of offer. Review of applications will begin in mid April 2019 and will continue until the positions are filled. URL: https://www.comp.hkbu.edu.hk/v1/?page=job_vacancies&id=503

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IDC 2019 - CALL FOR PAPERS - The 13th International Symposium on Intelligent Distributed Computing
by Igor Kotenko 14 Mar '19

14 Mar '19

To: computational.science(a)lists.iccsa.org Subject: [computational.science] IDC 2019 - CALL FOR PAPERS - The 13th International Symposium on Intelligent Distributed Computing [Apologies if you receive multiple copies of this message] ---------------- The Announcement and Call for Papers The 13th International Symposium on Intelligent Distributed Computing (IDC 2019) Saint-Petersburg, Russia, October 7-9, 2019 https://idc2019.ru CALL FOR PAPERS Symposium description The 13th International Symposium on Intelligent Distributed Computing (IDC 2019) will be held October 7-9, 2019 in Saint-Petersburg, Russia. The main goal of the symposium is to gather researchers and practitioners to foster and ease rich discussions around the latest findings, research achievements and ideas in the area of Intelligent Distributed Computing. The IDC provides an open forum for enhancing the collaboration between researchers, lecturers, and students from Intelligent Computing and Distributing Computing communities. Intelligent Computing covers a hybrid palette of methods, techniques and their applications ranging from classical artificial intelligence, information and data sciences, multi-agent technologies or computational intelligence to more recent trends such as swarm intelligence, bio-inspired computation, cloud computing, machine learning or social-cyber-physical security. Recent trends on this field present ephemeral computing, federated learning, swarm Intelligence, fog computing, semantic data science and others. Thus, the field of Intelligent Distributed Computing seeks for the design and implementation of new generation of intelligent distributed systems, adapting or hybridizing researches in both Intelligent Computing and Distributed Computing. IDC 2019 welcomes research works centered on all aspects of intelligent distributed computing, with an intention to balance between theoretical research ideas and their application to great variety of industrial cases. To this end, scholars and practitioners from academia and industrial fields are invited to submit high-quality original contributions to IDC 2019. The structure of the symposium consists of regular sessions with technical contributions reviewed and selected by an international program committee, as well as of special sessions and workshops targeted on multi-disciplinary and cutting-edge topics. IDC 2019 has a special interest in novel and creative approaches, architectures, systems and methods that facilitate distributed / parallel / multi-agent / bio-inspired computing for solving complex computational and communicational problems as well as real-life challenges. The scope of this edition spans further to embrace recent paradigms in Distributed Computation. Location The IDC 2019 Symposium organized by Laboratory of Computer Security Problems of St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS) and ITMO University will be held in St. Petersburg, Russia. Saint-Petersburg founded by Peter the Great in 1703, can rightly be called one of the most beautiful cities in Europe, united in its appearance European and Russian, architectural tradition. It was the imperial capital for two centuries and remains Russia's cultural center, with venues like the Hermitage, one of the largest art museums in the world, the State Russian Museum showcasing Russian art, from Orthodox icon paintings to Kandinsky works, and the Mariinsky Theatre hosting opera and ballet. The historic centre of St. Petersburg and related groups of monuments constitute a UNESCO World Heritage Site. The city is often called the "Venice of the North" because it is built on 44 islands, separated by 86 rivers and canals. Saint Petersburg is famous for its "white nights" when the end of May to mid-July instead of darkness envelops the city soft twilight, creating a unique romantic atmosphere, which is complemented by the classic St. Petersburg overlooking divorced bridges. St. Petersburg is not less beautiful, and in the winter, with encased in ice Neva and brilliant snow on the domes of St.Petersburg cathedral. Important dates Notification of acceptance for Tutorials/ Workshops/ Special sessions: March 4th, 2019 Paper submission: April 9th, 2019 Notification of acceptance: May 31st, 2019 Final paper submission: June 4th, 2019 Symposium dates: October 7th-9th, 2019 Submission of Papers All accepted papers will be included in the Symposium Proceedings, which will be published by Springer as part of their series Studies in Computational Intelligence. Papers must be at most 10 pages long and must be formatted according to Springer format. Submissions and reviews are automatically handled by EasyChair. Please submit your paper at: https://easychair.org/conferences/?conf=idc2019. Symposium Contacts General Chairs: Prof. Igor Kotenko, St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS) and ITMO University Prof. Costin Badica, University of Craiova, Romania E-mail: idc2019(a)comsec.spb.ru The conference Website: https://idc2019.ru Symposium Main Topics Intelligent Distributed and High-Performance Architectures * Hybrid distributed systems involving software agents and human actors * Intelligent grid and cloud infrastructures * Agent-based wireless sensor networks * Distributed frameworks and middleware for the IoT * Intelligent high-performance architectures * Context-aware intelligent computing * Virtualization for intelligent computing * Bio-inspired and nature-inspired distributed computing Computation Organization and Management * Autonomic and adaptive distributed computing * Multi-agent systems * Intelligent service composition and orchestration * Self-organizing and adaptive distributed systems * Emerging behaviors in complex systems * Intelligent integration of heterogeneous data and processes * Methodologies for development of intelligent distributed systems and applications Parallel metaheuristics for optimization * Evolutionary simulated annealing, Distributed Tabu Search * Parallel Variable Neighborhood Search * Swarm intelligence methods based on distributed knowledge sharing * Hybridization of Swarm Intelligence techniques, Memetic Computing, Adaptive Swarm Intelligence * Distributed Evolutionary Techniques, Cellular Evolutionary Algorithm, Hyper Heuristics Ephemeral and Unreliable computing * Theory and applications of complex ephemeral or unreliable environments * Design of ephemeral computing systems * Application of Soft Computing methods on computational environments featuring ephemeral behavior * Meta-heuristics for modeling and analyzing systems with ephemeral properties, such as social network dynamics, ephemeral clustering and pattern mining, ephemeral computational creativity or content generation Intelligent Distributed Knowledge Representation and Processing * Information extraction and retrieval in distributed environments * Knowledge integration and fusion from distributed sources * Data mining and knowledge discovery in distributed environments * Semantic and knowledge grids * Fuzzy methods * Ontologies and meta-data for describing heterogeneous resources and services * Distributed fusion of sensor data streams Networked Intelligence * E-service and web intelligence * Intelligence in mobile, ubiquitous and wearable computing * Intelligence in peer-to-peer systems * Intelligence in distributed and networked multimedia systems * Security, privacy, trust and reputation Parallel Computing * Parallel and Distributed Computational Models * Embedded Parallel Distributed Systems * Multi- and Many-core Systems * GPU and FPGA based Parallel Systems * Parallel Input/Output * Memory Organization * Parallel Cloud Computing * Parallel and Distributed Optimizations * Hardware Acceleration for Deep Learning Data Science * Big Data technologies * Machine Learning * Large Scale data processing * Distributed databases and archives * Data Management * Semantic Data Science and Applications * Soft Social Computing and Network Science * Interdisciplinary Approaches in Data Science * Data Intensive Applications * Intelligent Analysis of Large Spatial Data * Ontological based Approaches to Data Storage and Processing * Data Sciences use-cases, including Social Network analysis Networked Intelligence * E-service and web intelligence * Intelligence in mobile, ubiquitous and wearable computing * Intelligence in peer-to-peer systems * Intelligence in distributed and networked multimedia systems * Security, privacy, trust and reputation Nature inspired methods for data science and machine learning * Recent advances on nature inspired methods for data science * Novel applications of bio-inspired methods to data mining, with priority on real-world scenarios * Nature-inspired methods for supervised and unsupervised data mining * Hybridizing bio-inspired methods with machine learning and data mining techniques * Nature-inspired methods for feature selection and/or instance generation/selection * Implementation of bio-inspired methods using Big Data technologies * Federated learning: theory and applications Intelligent Distributed Applications * Security of Intelligent Distributed Systems * Attack Modeling, intrusion detection and protection in Intelligent Distributed Systems * Intelligent methods in Cyber-Physical Systems * Distributed problem solving and decision making * Semantic Applications * Intelligent applications in e-business/e-commerce, e-learning, e-health, e-science, e-government, crisis management, smart grid * Modeling, simulation and development of intelligent distributed systems * Crisis management * Simulation of groups and crowds * Intelligent data processing * Intelligent robots Special Sessions: * Advanced Methods for Intelligent Distributed Computing in Telecommunication Systems * Advanced Methods for Social Network Analysis and Inappropriate Content Counteraction * Big Data for Intelligent Distributed Information Processing * Intelligent Autonomous Vehicles and Safety (AVS) * Intelligent Distributed Computing for Cyber-Physical Security and Safety (IDCCPSS) * Intelligent Distributed Decision Support Systems (IDDSS) * Intelligent Human-Machine Interfaces (IHMI) * Internet of Things and Internet of Agents * Parallel and Distributed Algorithms for Artificial Intelligence Applications (PDAAIA) * Security for Intelligent Distributed Computing (IDC) - Machine Learning (ML) vs. Chains of Trust (CoT) * Visual Analytics in Distributed Environment =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=

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Call For Papers: The 1st International Workshop on Human-oriented Intelligent Defence Against Malware Threats (HIDAMT)
by Andrii Shalaginov 13 Mar '19

13 Mar '19

Dear Colleague, (Apologies for multiple postings) You are welcome to submit your contributions to the workshop on Human-oriented Intelligent Defence Against Malware Threats, which will be held as a part of the 28th International Joint Conference on Artificial Intelligence (IJCAI) 2019. The conference will take place on the 10-16th of August 2019 in Macao, China. Workshop webpage: https://folk.ntnu.no/andriis/hidamt2019/ *** IMPORTANT DATES *** Apr 12, 2019: Due date for full workshop paper submissions May 10, 2019: Paper acceptance notification Jun 3, 2019: Complete papers submission Aug 10-12, 2019: Workshops and conference *** INTRODUCTION *** Recent cybersecurity incidents involving malware demonstrated how serious the consequences can be for both individual users and large organizations. McAfee report on malware threats shows that over four quarters of 2017 there were identified 690 millions of malware samples, which is an extreme number considering amount of manual work required to process even a tiny fraction of those. Many malware analysis across different security organizations spent hours trying to analyze and understand functionality of malware. At the same time overwhelming amount of malicious threats and malware forms cause considerable delays from the time malware has been discovered to the time a corresponding efficient signature was created. Moreover, the malware infection is no longer limited to personal computers, but now also hits such components as Internet of Things and Industrial Control Systems, which were previously unaffected and the cybersecirty impact was underestimated. >From before Machine Learning and Computational Intelligence have demonstrated advantages of application in cybersecurity-related tasks. In particular, many researchers have been employing such techniques to mitigate obfuscation, polymorphous and encryption while building intelligent malware detection mechanisms. Intelligent malware analysis and detection is an emerging topic of cybersecurity that has to go in line with advancement of malware developers and consistent presence of zero-day attacks. Our focus is not only to build and effective Machine Learning-based malware protection, but also comprise models that are to be understood by human experts. Therefore, we believe that Machine Learning-aided human-oriented approaches will ensure timely response to malware threats. Moreover, those can serve as a stepping stone in faster and more efficient analysis of novel malware as well as similarity-based identification of adversarial attacks on Machine Learning. *** PROPOSED TOPICS *** Note that the topics are not limited to this proposed list. 1. Automated pre-processing phase - Efficient features identification and construction - Novel approaches for malware categorization - Human-understandable characterization of malware - Indicators of Compromise as successful identification tool - Information Fusion and Open Threats Intelligence 2. Advanced computational methods - Deep Learning models - Similarity-based analysis to avoid evasion - Big Data-oriented optimization of detection - Hybrid Intelligence and Soft Computing - Secure and robust models to avoid adversarial attacks 3. Combating malware in a wild - End-point implementations - Novel malware collection and sharing platforms - Applications in Decision Support Systems - Human reasoning in Machine Learning-aided malware detection - Real-time defence and online learning - Explainable rules derived from train Machine Learning models *** PROGRAM CO-CHAIRS *** Andrii Shalaginov, Norwegian University of Science and Technology Geir Olav Dyrkolbotn, Center for Cyber and Information Security Sergii Banin, Norwegian University of Science and Technology Ali Dehghantanha, University of Guelph Katrin Franke, Norwegian University of Science and Technology *** PROGRAM COMMITTEE *** Olaf M. Maennel (Tallinn University of Technology) Asif Iqbal (KTH Royal Institute of Technology) Oleksandr Semeniuta (Norwegian University of Science and Technology) Mamoun Alazab (Charles Darwin University) Vasileios Mavroeidis (University of Oslo) Sreyasee Das Bhattacharjee (University of North Carolina at Charlotte) Igor Kotsiuba (Pukhov Institute for modeling in Energy Engineering) Mark Scanlon (University College Dublin) Piotr Andrzej Kowalski (AGH University of Science and Technology) Reza Parizi (Kennesaw State University) Mohammad Hamoudeh (Manchester Metropolitan University) Gregory Epiphaniou (University of Wolverhampton) Bojan Kolosnjaji (Technical University of Munich) Shih-Chieh Su (‎Microsoft) -- Best regards / Med vennlig hilsen, ―- Andrii SHALAGINOV, PhD Postoctoral Researcher in Digital Forensics Malware Analyst IEEE Member Norwegian University of Science and Technology NTNU | http://www.ntnu.edu/employees/andrii.shalaginov

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[CFP] IEEE EUC 2019 - The 17th IEEE International Conference on Embedded and Ubiquitous Computing
by Han Qiu 13 Mar '19

13 Mar '19

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ IEEE EUC 2019 - The 17th IEEE International Conference on Embedded and Ubiquitous Computing - August 1–3, 2019 New York, USA http://www.cloud-conf.net/EUC/2019/index.html +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ INTRODUCTION With the rapid development and increasing complexity of computer systems and communication networks, user requirements for embedded and ubiquitous computing are becoming more and more demanding. Therefore, there is a grand challenge that traditional computing techniques may not meet user requirements in open, dynamic, heterogeneous, mobile, wireless, and distributed computing environments. As a result, we need to build embedded systems and networks based on ubiquitous computing. As important and innovative technologies, embedded and ubiquitous computing techniques are attracting researchers with more and more attention. Embedded ubiquitous computing is promising to improve people’s quality of life by creating new applications based on data processing in IoT network. Many research efforts have been performed on novel processing and communication architectures, technologies and management strategies. Embedded ubiquitous computing systems can leverage wireless sensor networks to collect and process data and use cloud technologies, peer-to-peer systems, and big data paradigms to provide computing and analytics capabilities. Nowadays, because of the growth of smart devices, embedded ubiquitous computing technologies and combined with cyber world to provide many smart services, the Internet of Things (IoT) became more promising to realize that various embedded applications allow users to enjoy more comprehensive services. As an emerging research topic, embedded ubiquitous computing relate to and support a computing vision for a greater range including smart devices (mobile, wireless, service), smart environments (of embedded system devices) and smart interaction (between devices). The EUC conference aims, as such, to provide a platform for the dissemination of recent research efforts that explicitly aim at addressing these challenges, and supports the presentation of advanced solutions in these areas. TOPIC Topics of particular interest include, but are not limited to: - Data analysis and data management for embedded and ubiquitous computing - Applications for embedded and ubiquitous computing - Parallel and distributed systems - Mobile systems and applications for embedded and ubiquitous computing - Enhanced living environments and smart habitats for older adults - Security, safety and reliability/dependability - Hardware architectures and design tools - Software and programming tools for embedded and ubiquitous computing PAPER SUBMISSION Prospective authors are invited to submit papers via Easychair (https://easychair.org/conferences/?conf=ieeeeuc2019) The submissions should be formatted with the IEEE 8.5 x 11 inches two-column format with 10-12 point font. Detailed formatting and submission instructions are available at the conference website (http://www.cloud-conf.net/EUC/2019/submission.html) IMPORTANT DATES Paper submission: April 5, 2019 Notification of acceptance: May 15, 2019 Final manuscript submission: June 15, 2019 For further information, please contact: han.qiu(a)telecom-paristech.fr.

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CFP: The 5th IEEE International Conference on Big Data Intelligence and Computing (IEEE DataCom 2019)
by Bahman Javadi 13 Mar '19

13 Mar '19

The 5th IEEE International Conference on Big Data Intelligence and Computing Kaohsiung, Taiwan, Nov. 18-21, 2019http://www.cs.ccu.edu.tw/~conference/datacom2019/ Dear Colleagues: We cordially invite you to share your latest research results related to big data analytics and intelligence at the IEEE DataCom 2019 conference. --------------------------- CALL FOR PAPERS --------------------------- Big data is a rapidly expanding research area spanning the fields of computer science and information management, and has become a ubiquitous term in understanding and solving complex problems in different disciplinary fields such as engineering, applied mathematics, medicine, computational biology, healthcare, social networks, finance, business, government, education, transportation and telecommunications. The goal of the IEEE International Conference on Big Data Intelligence and Computing (IEEE DataCom 2019) is to establish an international forum for engineers and scientists to present their ideas and experiences in the fields of Big Data intelligence and computing. IEEE DataCom 2019 welcomes paper submissions on innovative work from researchers in academia, industry and government describing original research work in Big Data. Authors of selected papers will be invited to submit an extended version (with at least 30% new material) for review and publication in special issues of international journals. IEEE DataCom 2019 will be held on Nov. 18-21, 2019, co-located with IEEE SC2 2019, IEEE SOCA 2019 and IOV 2019, in Kaohsiung, Taiwan. Topics of interest include, but are not limited to: - The 5Vs of the data landscape: volume, variety, velocity, veracity, value - Big data science and foundations - Analytics, visualization and semantics - Software and tools for big data management. - Security, privacy and legal issues specific to big data - Big data economy, QoS and business models - Scientific discovery and business intelligence - Software, hardware and algorithm co-design - High-performance computing - Large-scale recommendation systems - Graph analysis - Infrastructures and systems for big data analytics and managements - Middleware and tools for big data analytics and managements - Algorithmic, experimental, prototyping and implementation - Data quality issues: such as validation, metrics, optimizations and consistency - Data-driven innovation, computational modelling and data integration - Data intensive computing theorems and technologies - Big data for advanced manufacturing and productivity - Modeling, simulation and performance evaluation - Green data centers / environmental-friendly perspectives - Computing, scheduling and resource management for sustainability - Complex applications in areas where massive data is generated ---------------------------------------- PUBLICATION HIGHLIGHTS ---------------------------------------- IEEE CS proceedings, indexed by - IEEE Xplore - Scopus - EI Engineering Index - ACM Digital Library - dblp - Google Scholar Extended version of the selected papers will be invited for publication in prestigious international journals. ---------------------------- IMPORTANT DATES ---------------------------- Tutorial/Workshop/Special Session Proposal Due: April 30, 2019 Research Article (early track): Paper Submission May 30, 2019 Author Notification June 15, 2019 Research Article (regular track): Paper Submission July 20, 2019 Author Notification August 31, 2019 Poster/Special Session: Paper Submission September 10, 2019 Author Notification September 26, 2019 Registration Due: October 10, 2019 Camera ready submission: October 20, 2019 Official Invitation Letter will be issued upon completion of registration ----------------- SUBMISSION ----------------- Authors are invited to submit their original research work that has not previously been submitted or published in any other venue. Papers should be prepared in IEEE CS format and submitted via The EasyChair system. IEEE formatting information:http://www.ieee.org/conferences_events/conferences/publishing/t… - Proposals for organizing tutorials, workshops and special sessions need to be submitted to the Workshops Chair of the conference. A proposal should include title, theme, scope and main presenters/organizers. - Research paper (8 pages) should explore a specific technology problem and propose a complete solution to it, with experimental results. - Works-in-Progess (WIP) (6 pages) papers are expected to present either work currently in progress or less developed but highly innovative ideas. - Demo/Poster papers (4 pages) must describe working systems and be related to DataCom. These systems may be innovative prototype implementations or mature systems that use related technology. Papers/proposals need to be submitted to the Demo/Poster Chair. - Workshop and Special Session papers need to be submitted to the corresponding workshops and special sessions Chairs. All accepted papers in the main tracks, workshops, special sessions and demos/posters will be published in an IEEE Computer Society proceedings. Extended versions of selected excellent papers will be considered for publication in special issues of prestige journals (SCI/EI indexed). ------------------------------- BEST PAPER AWARDS ------------------------------- The award committee will select Best Paper/Poster Award(s) and present the winners with an actual frame Award Certificate at the conference banquet. ------------------------------- Organizing Committees ------------------------------- General Chairs Ren-Hung Hwang, National Chung Cheng University, Taiwan Albert Zomaya, The University of Sydney, Australia Jiming Chen, Zhejiang University, China Program Chairs Che-Rung Lee, National Tsing Hua University, Taiwan Jemal Abawajy, Deakin University, Australia Workshop Chairs Che-Lung Hung, Chang Gung University, Taiwan Demo & Poster Chair Hung-Chang Hsiao, National Cheng Kung University, Taiwan Publication Chair Alex Mu-Hsing Kuo, University of Victoria, Canada Award Chair Frank Hsu, Fordham University, USA Publicity Chair Song Wu, Huazhong University of Science and Technology, China Bahman Javadi, University of Western Sydney, Australia I-Hsin Chung, IBM Thomas J. Watson Research Center, USA Chao-Chin Wu, National Changhua University of Education, Taiwan Advisory Committee Anna Kobusinska, Poznan University of Technology, Poland Beniamino Di Martino, Second University of Naples, Italy Christophe Cérin, Université Paris 13, France Cho-Li Wang, The University of HongKong, Hong Kong Jinsong Wu, University de Chile, Chile Rajiv Ranjan, Newcastle University, UK Song Guo, The Hong Kong Polytechnic University, Hong Kong Vincent S. Tseng, National Chiao-Tung University, Taiwan Wenguang Chen, Tsinghua University, China Xiaolin Li, University of Florida, USA Yeh-Ching Chung, The Chinese University of HongKong, Hong Kong Feng Xia, Dalian University of Technology, China Steering Committee Sanjay Ranka, University of Florida, USA Robert Hsu, National Chung Cheng University, Taiwan Manish Parashar, Rutgers University, USA Hai Jin, HUST, China Jie Li, University of Tsukuba, Japan Yuanyuan Yang, Stony Brook University, USA

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[CFP] 4th IEEE International Conference on Rebooting Computing
by Tumeo, Antonino 12 Mar '19

12 Mar '19

[Apologies if you receive multiple copies of this CFP] Call for Papers 4th IEEE International Conference on Rebooting Computing Part of IEEE Rebooting Computing Week 6-8 November 2019 San Francisco Bay Area, California http://icrc.ieee.org/ The 4th IEEE International Conference on Rebooting Computing (ICRC 2019) will be held November 6-8 in the San Francisco Bay Area, California. ICRC is a premier venue for novel computing approaches. ICRC grew out of the IEEE Rebooting Computing Initiative (RCI), which was founded in 2012 to catalyze rethinking of the computer at all levels of the technology stack. The Rebooting Computing Committee represents thirteen IEEE Societies and Councils, and the membership in the Rebooting Computing Technical Community is approaching three thousand. For more information on the RCI please visit the Rebooting Computing Portal (http://rebootingcomputing.ieee.org) Now in its 4th year, the IEEE International Conference on Rebooting Computing is the premier venue for forward looking computing, including algorithms and languages, system software, system and network architectures, new devices and circuits, and applications of new materials and physics. This is an interdisciplinary conference that has participation from a broad technical community, with emphasis on all aspects of the computing stack. The broad scope of ICRC extends to many areas of interest, including novel device physics and materials for post-Moore, beyond CMOS, and non-von Neumann computing paradigms. ——————————————— Topics of interest ——————————————— *Future computing approaches, including neuromorphic, brain-inspired computing, approximate and probabilistic, analog computing; computing based on novel device physics and materials (e.g., spin-based electronics, nonlinear dynamics and chaos); energy-efficient computing including reversible, adiabatic, and ballistic computing, superconductor and cryogenic computing; quantum computing; optical computing; biological and biochemical computing; Non-von Neumann computer architectures (e.g., in-memory processing, memory-based computing, cellular automata, or cellular neural networks). *Future computing design aspects, including extending Moore’s law and augmenting CMOS; error-tolerant logic and circuits; future of design automation. post-CMOS, 3D, heterogeneous integration and packaging; future impact on performance, power, scalability, reliability, supportability *Future Software and Applications, including beyond von Neumann system software issues (operating systems, compilers, security, and resource management); future computing programming paradigms and languages; applications suitable for and driving next generation computing (e.g., machine learning, deep learning.) *Future computing use cases and prototypes, including ethics in design, implementation, and use; new technologies impacting the International Roadmap for Devices and Systems (IRDS); cybersecurity in future computing systems. ——————————————— Organizing Committee ——————————————— General co-Chairs: Cullen Bash (Hewlett Packard Enterprise) and Vivek Sarkar (Georgia Institute of Technology) Program co-Chairs: Jim Ang (PNNL) and Paolo Faraboschi (Hewlett Packard Enterprise) Full committee list: http://icrc.ieee.org/committee Authors’ guidelines: http://icrc.ieee.org/authors-guidelines ——————————————— Important dates ——————————————— *Paper abstract submissions due: April 29, 2019 (11:00 pm EDT) *Paper submissions due: May 6, 2019 (11:00 pm EDT) *Author notification of acceptance: August 7, 2019 *Final copies of papers due: September 6, 2019

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CFP: Int. Conference on Deep Learning and Machine Learning in Emerging Applications (Deep-ML 2019)
by Deep ML 11 Mar '19

11 Mar '19

------------------------ Call for Papers ----------------------------- The International Conference on Deep Learning and Machine Learning in Emerging Applications (Deep-ML 2019) 26-28 August 2019, Istanbul, Turkey http://www.ficloud.org/deep-ml-2019/ ----------------------------------------------------------------------------- Deep learning and machine learning are the state-of-the-art at providing models, methods, tools and techniques for developing autonomous and intelligent systems which can revolutionize industrial and commercial applications in various fields such as online commerce, intelligent transportation, healthcare and medicine, security, manufacturing, education, games, and various other industrial applications. Google, for example, exploits the techniques of deep learning in voice and image recognition applications, while Amazon uses such techniques in helping customers in their online purchase decisions. The International Conference on Deep Learning and Machine Learning in Emerging Applications (Deep-ML) provides a leading forum for researchers, developers, practitioners, and professional from public sectors and industries in order to meet and share latest solutions and ideas in solving cutting edge problems in modern information society and economy. The conference comprises a set of tracks that focus on specific challenges in deep learning and machine learning and their applications in emerging areas. Topics of interest include, but are not limited to, the following: 1) Deep and Machine Learning Models and Techniques: Novel machine and deep learning Active learning; Incremental learning and online learning Agent-based learning; Manifold learning Multi-task learning Bayesian networks and applications Case-based reasoning methods Statistical models and learning Computational learning; Evolutionary algorithms and learning Evolutionary neural networks Fuzzy logic-based learning Genetic optimization Clustering, classification and regression Neural network models and learning Parallel and distributed learning Reinforcement learning Supervised, semi-supervised and unsupervised learning Tensor Learning 2) Deep and Machine Learning for Big Data Analytics: Deep/Machine learning based theoretical and computational models Novel techniques for big data storage and processing Data analysis, insights and hidden pattern Data analysis and decision making Data wrangling, munching and cleaning Data integration and fusion Data visualization Data and information quality, efficiency and scalability Security threat detection using big data analytics Visualizing security threats Enhancing privacy and trust Data analytics in complex applications – finance, business, healthcare, engineering, medicine, law, transportation, and telecommunication 3) Deep and Machine Learning for Data Mining and Knowledge: Data mining in the web and online systems Multimedia; images and video data mining Feature extraction and classification Information retrieval and extraction Distributed and P2P data search Sentiment analysis Mining high velocity data streams Anomaly detection in streaming data Mining social media and social networks Mining sensor and computer networks data Mining spatial and temporal datasets Data classification, clustering, and association Knowledge acquisition and learning Knowledge representation and reasoning Knowledge discovery in large datasets 4) Deep and Machine Learning Application Areas: Bioinformatics and biomedical informatics Finance, business and retail Intelligent transportation Healthcare, medicine and clinical decision support Computer vision Human activity recognition Information retrieval and web search Cybersecurity Natural language processing Recommender systems Social media and networks 5) Deep and Machine Learning for Computing and Network Platforms: Network and communication systems Software defined networks Wireless and sensor networks Internet of Things (IoT) Cloud Computing Edge and Fog Computing Paper Submission: Full papers must be in English and should be between 12 to 14 pages. Short papers should be limited to 8 pages. Papers must be formatted in Springer's LNCS format. Submitted research papers may not overlap with papers that have already been published or that are simultaneously submitted to a journal or a conference with proceedings. ORGANISING COMMITTEE General Co-Chairs: Joao Gama, University of Porto, Portugal Edwin Lughofer, Johannes Kepler University Linz, Austria Program Co-Chairs: Irfan Awan, University of Bradford, UK Hadi Larijani, Glasgow Caledonian University, UK Local Organising Co-Chairs: Perin Ünal, Teknopar, Turkey Sezer Gören, Ugurdag Yeditepe University, Turkey Tacha Serif, Yeditepe University, Turkey Publication Chair: Muhammad Younas, Oxford Brookes University, UK Journal Special Issue Coordinator: Lin Guan, Loughborough University, UK Workshop Coordinator: Filipe Portela, University of Minho, Portugal Publicity Chair: Esra N. Yolaçan, Osman Gazi University, Turkey

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[IEEE ICCI*CC'19:] Invitation to IEEE TC-BCS Special Sessions
by Yingxu Wang 08 Mar '19

08 Mar '19

Dear Colleague, The IEEE SMC TC on Brain-Inspired Cognitive Systems (TC-BCS) will organize the following Special Sessions at IEEE SMC'19 (http://smc2019.org/index.html) 1) Brain-Inspired Cognitive Systems (BMI35, Code: 75sm9) 2) Cognitive Cybernetics and Autonomous Systems (C37, Code: 8xm35) 3) Autonomous Systems by Cognitive Computing (S18, code: t4567) You are cordially invited for contributing a 4-page paper to the special sessions, which will be treated as the same as other categories of papers in the IEEE proceedings with EI index. The submission website is at: https://conf.papercept.net/conferences/scripts/start.pl . The session code as provided above will be needed for submission. Sincerely, Session Co-Chairs: Prof. Yingxu Wang, Prof. Sam Kong, Prof. Henry Leung, and Prof. Kostas Plataniotis _______________________________________________ This message was sent to all subscribers of IEEEicci13-L To unsubscribe, see instructions at: http://www.ucalgary.ca/it/email/mailman E-mail: IEEEicci13-L(a)mailman.ucalgary.ca Homepage: http://mailman.ucalgary.ca/mailman/listinfo/ieeeicci13-l

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