Social networks as a service in modern enterprises

The power of social networks stems from their ability to capture real-world phenomena such as collaboration, competition, and partnerships. Social networks provide means for enterprises to capture and expose many informal connections between their stakeholders. In this paper, we discuss how social networks could sustain growth and unfold business opportunities in modern enterprises. Furthermore, we study various types of social networks and investigate metrics that measure their value-added to enterprises. In response to business-oriented social network requirements, we propose a multi-tenant architecture to develop Social-Networks-as-a-Service (SNaaS) and allow efficient use of server resources while reducing maintenance costs and providing a high degree of customization to support each enterprise\u27s requirements. ©2009 IEEE

Can Enterprises Capitalize on their Social Networks?

International audienc

Autonomic service-oriented grid to enhance E-learning experiences

Grid environments were initially intended to deal with issues surrounding computing-intensive applications. Today, however, the use of Grids has evolved to tackle new horizons such as managing large amounts of data and running business applications that support consumers and casual users. In particular, this evolution towards a general-purpose, Grid service-based infrastructure allows educational institutions to enhance e-learning technologies and innovate in e-learning experiences through the provision and mutualisation of various services. Grid technologies will likely become the Information and Communication Technologies backbone of tomorrow\u27s elearning programmes due to their ability to handle and process data from a multitude of resources (i.e., sensors, data warehouses, etc.) and offer new learning experiences which do not exist without the Grid capabilities. To face these new challenges, we propose a service-oriented Grid architecture capable to deliver services that can be used in collaborative learning processes and virtual learning environments. The architecture not only supports the provision of basic e-learning services but also provides infrastructure services (e.g., storage, computational resources, and security services), which can be combined to build on-demand and customized e-learning scenarios. The architecture is self-managed and exhibits autonomic behaviour to adapt itself to environment changes and exempt non-IT people from managing technical issues. ©2009 IEEE

Enabling intrusion detection systems with dueling double deep Q-learning

Purpose – In this research, the authors demonstrate the advantage of reinforcement learning (RL) based intrusion detection systems (IDS) to solve very complex problems (e.g. selecting input features, considering scarce resources and constrains) that cannot be solved by classical machine learning. The authors include a comparative study to build intrusion detection based on statistical machine learning and representational learning, using knowledge discovery in databases (KDD) Cup99 and Installation Support Center of Expertise (ISCX) 2012. Design/methodology/approach – The methodology applies a data analytics approach, consisting of data exploration and machine learning model training and evaluation. To build a network-based intrusion detection system, the authors apply dueling double deep Q-networks architecture enabled with costly features, k-nearest neighbors (K-NN), support-vector machines (SVM) and convolution neural networks (CNN). Findings – Machine learning-based intrusion detection are trained on historical datasets which lead to model drift and lack of generalization whereas RL is trained with data collected through interactions. RL is bound to learn from its interactions with a stochastic environment in the absence of a training dataset whereas supervised learning simply learns from collected data and require less computational resources. Research limitations/implications – All machine learning models have achieved high accuracy values and performance. One potential reason is that both datasets are simulated, and not realistic. It was not clear whether a validation was ever performed to show that data were collected from real network traffics. Practical implications – The study provides guidelines to implement IDS with classical supervised learning, deep learning and RL. Originality/value – The research applied the dueling double deep Q-networks architecture enabled with costly features to build network-based intrusion detection from network traffics. This research presents a comparative study of reinforcement-based instruction detection with counterparts built with statistical and representational machine learning

Special track on web technologies

The Internet and other related technologies have created an interconnected world in which information can be easily exchanged, tasks can be collaboratively processed, communities of users with similar interests can be instantly formed to achieve efficiency and improve performance, while security threats are present more than ever before. This second edition of Web Technologies track is intended to bring together researchers who are actively engaged both in theoretical and practical aspects of database interoperability

Business Artifacts for E-Business Interoperability

Traditional solutions to address interoperability issues are mainly process-centric so that consistent interactions among collaborating enterprises are ensured. These solutions examine interoperability from a technological perspective with focus on exchanging information messages between distributed and heterogeneous applications. However, interoperability from a business perspective has been overlooked in the past due to the complexity of reconciling diverse business strategies, organizational constraints, and IT infrastructures. Business interoperability denotes the ability of diverse enterprises to collaborate together to coproduce added-value products and services. In this chapter, a new line of thinking is promoted whereby interoperability is data-centric instead of process-centric. Business interoperability is dealt with by adopting business artifacts that are able to cross organizational boundaries, and by introducing a stack of three layers - strategy, service, and resource. Artifacts are self-contained business records that include attributes, states, and life cycles that reflect the changes in these states. The artifact concept not only describes a business entity, but also encompasses knowledge about what to process without explaining how to do it. The shift from processes to artifacts makes business interoperability quite simple\u27\u27 to deploy and renders collaboration easy to manage and analyze. The chapter also introduces several interaction patterns that regulate the exchange of artifacts between enterprises. The ideas and proposals in this chapter are discussed via a realistic case-study to demonstrate how business people can seamlessly manage their day-to-day activities and intuitively construct interoperable and sustainable collaborations at the business and technological levels

Business artifacts discovery and modeling

Changes in business conditions have forced enterprises to continuously re-engineer their business processes. Traditional business process modeling approaches, being activity-centric, have proven to be inadequate for handling this re-engineering. Recent research has focused on developing data-centric business process modeling approaches based on (business) artifacts. However, formal approaches for deriving artifacts out of business requirements currently do not exist. This paper describes a method for artifact discovery and modeling. The method is illustrated with an example in the purchase order domain. © 2010 Springer-Verlag

Business Artifacts for E-Business Interoperability

Traditional solutions to address interoperability issues are mainly process-centric so that consistent interactions among collaborating enterprises are ensured. These solutions examine interoperability from a technological perspective with focus on exchanging information messages between distributed and heterogeneous applications. However, interoperability from a business perspective has been overlooked in the past due to the complexity of reconciling diverse business strategies, organizational constraints, and IT infrastructures. Business interoperability denotes the ability of diverse enterprises to collaborate together to coproduce added-value products and services. In this chapter, a new line of thinking is promoted whereby interoperability is data-centric instead of process-centric. Business interoperability is dealt with by adopting business artifacts that are able to cross organizational boundaries, and by introducing a stack of three layers - strategy, service, and resource. Artifacts are self-contained business records that include attributes, states, and life cycles that reflect the changes in these states. The artifact concept not only describes a business entity, but also encompasses knowledge about what to process without explaining how to do it. The shift from processes to artifacts makes business interoperability quite simple\u27\u27 to deploy and renders collaboration easy to manage and analyze. The chapter also introduces several interaction patterns that regulate the exchange of artifacts between enterprises. The ideas and proposals in this chapter are discussed via a realistic case-study to demonstrate how business people can seamlessly manage their day-to-day activities and intuitively construct interoperable and sustainable collaborations at the business and technological levels