Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page

Actor-network procedures: Modeling multi-factor authentication, device pairing, social interactions

As computation spreads from computers to networks of computers, and migrates into cyberspace, it ceases to be globally programmable, but it remains programmable indirectly: network computations cannot be controlled, but they can be steered by local constraints on network nodes. The tasks of "programming" global behaviors through local constraints belong to the area of security. The "program particles" that assure that a system of local interactions leads towards some desired global goals are called security protocols. As computation spreads beyond cyberspace, into physical and social spaces, new security tasks and problems arise. As networks are extended by physical sensors and controllers, including the humans, and interlaced with social networks, the engineering concepts and techniques of computer security blend with the social processes of security. These new connectors for computational and social software require a new "discipline of programming" of global behaviors through local constraints. Since the new discipline seems to be emerging from a combination of established models of security protocols with older methods of procedural programming, we use the name procedures for these new connectors, that generalize protocols. In the present paper we propose actor-networks as a formal model of computation in heterogenous networks of computers, humans and their devices; and we introduce Procedure Derivation Logic (PDL) as a framework for reasoning about security in actor-networks. On the way, we survey the guiding ideas of Protocol Derivation Logic (also PDL) that evolved through our work in security in last 10 years. Both formalisms are geared towards graphic reasoning and tool support. We illustrate their workings by analysing a popular form of two-factor authentication, and a multi-channel device pairing procedure, devised for this occasion.Comment: 32 pages, 12 figures, 3 tables; journal submission; extended references, added discussio

Modelling and Verification of Large-Scale Sensor Network Infrastructures

Large-scale wireless sensor networks (WSN) are increasingly deployed and an open question is how they can support multiple applications. Networks and sensing devices are typically heterogeneous and evolving: topologies change, nodes drop in and out of the network, and devices are reconfigured. The key question we address is how to verify that application requirements are met, individually and collectively, and can continue to be met, in the context of large-scale, evolving network and device configurations. We define a modelling and verification framework based on Bigraphical Reactive Systems (BRS) for modelling, with bigraph patterns and temporal logic properties for specifying application requirements. The bigraph diagrammatic notation provides an intuitive representation of concepts such as hierarchies, communication, events and spatial relationships, which are fundamental to WSNs. We demonstrate modelling and verification through a real-life urban environmental monitoring case-study. A novel contribution is automated online verification using BigraphER and replay of real-life sensed data streams and network events by the Cooja network simulator. Performance results for verification of two application properties running on a WSN with up to 200 nodes indicate our framework is capable of handling WSNs of that scale

A Complete Axiomatization of Quantified Differential Dynamic Logic for Distributed Hybrid Systems

We address a fundamental mismatch between the combinations of dynamics that occur in cyber-physical systems and the limited kinds of dynamics supported in analysis. Modern applications combine communication, computation, and control. They may even form dynamic distributed networks, where neither structure nor dimension stay the same while the system follows hybrid dynamics, i.e., mixed discrete and continuous dynamics. We provide the logical foundations for closing this analytic gap. We develop a formal model for distributed hybrid systems. It combines quantified differential equations with quantified assignments and dynamic dimensionality-changes. We introduce a dynamic logic for verifying distributed hybrid systems and present a proof calculus for this logic. This is the first formal verification approach for distributed hybrid systems. We prove that our calculus is a sound and complete axiomatization of the behavior of distributed hybrid systems relative to quantified differential equations. In our calculus we have proven collision freedom in distributed car control even when an unbounded number of new cars may appear dynamically on the road