Panel 1: Security and Privacy in Collaborative Environments
Moderator: Anna Squicciarini, Pennsylvania State University, USA
- Bogdan Carbunar, Florida International University, USA
- Mohamed Eltoweissy, Virginia Military Institute & Professor, Virginia Tech, USA
- Murat Kantarcioglu, University of Texas, Dallas, USA
- Vincent Hu, NIST, USA
- Kevin Butler, University of Florida, USA
Collaborative computing has emerged as a promising paradigm for developing large-scale distributed systems. New hot topics such as BigData, IoT, Social Networks. Crowdsoucing, Participatory Sensing, Cyber-physical environments, Cloud computing, etc., represent recent successes of collaborative computing in the context of large scale social computing and distributed service computing. These successes have pushed the computing and communication to be more ubiquitous and towards more global collaboration, and have demonstrated that collaboration is and continue to be a fundamental capability of network computing and . However, with increased interconnectivity and opportunities of collaboration at scale, and its infusion in every aspect of society, there is also growing concerns of security and privacy (S&P) issues. This panel will focus on discussing pressing challenges related to S&P issues that can pose as hurdles in advancing collaborative computing as well as how S&P solutions may help further foster collaboration computing technologies.
Panel 2: BigData - Challenges and Opportunities
Moderator: James Joshi, University of Pittsburgh, USA
- Karl Aberer, EPFL, Switzerland
- Panos Chrysanthis, University of Pittsburgh, USA
- Taghi Khoshgoftaar, Florida Atlantic University, USA
- Latifur Khan, University of Texas at Dallas, USA
With the huge amounts of data being produced continuously by plethora of computing devices and infrastructures (enterprise data repositories, Internet of Things, monitoring devices such as in healthcare domain and surveillance activities, federated sensor/mobile networks, cyber-physical infrastructures, social networks, etc.), the key data handling tasks such as storing, processing, and analyzing, are increasingly becoming very difficult. BigData has thus emerged as an area representing these growing problems of handling data sets characterized by high volume, high velocity and variety. While large and dynamic data sets that can be easily generated today provide an opportunity for streamlining decision making capabilities, improving business intelligence, mining new knowledge and enabling new and enriched services, current data handling solutions have significant limitations. Solutions that employ collaborative systems, technologies and network infrastructures are crucial for addressing such BigData related challenges. This panel will focus on identifying key BigData related challenges and the opportunities it offers, limitations of current solutions (architectural, storage, algorithmic, etc.), and future research directions in this domain. Some big questions related to BigData, for instance, include:
- How a collaborative cloud computing infrastructure may need to be leveraged to address BigData analytics problems?
- What kind of new network and storage infrastructures may need to be developed?
- How BigData may exacerbate security and privacy (S&P) problems?
- How BigData may be leveraged to solve some critical S&P problems?
- What data and meta-data modeling approaches are needed (such as for context, structure, multi-modality, quality, dependability, provenance, etc.) to support BigData handling tasks?
- What are the BigData analytics challenges and how to model Human in the loop ?