Collaborative Security and Decision Making in SOA environment

In a service-oriented environment, services exposed in a network might be invoked not only by legitimate applications but also by hackers.

Traditionally, each service is protected individually. In modern environments, especially with the adaptation of Internet of Things (IoT), many services work simultaneously. This multiplicity of "things" and factors, described as situational scenarios, can serve for collaborative security and collaborative decision making.

Security is all about the levels of security. Taking into account multiple factors in a collaborative fashion will increase security.

Simultaneous activity of many services or "things", working on a common task, requires collaborative decision making. People not always have easy time, while making collaborative efforts. How can computer services optimize their behavior, when many of them simultaneosly perform different and sometimes conflicting tasks, interfere with external events and weather, trying to adapt to a quickly changing situation?

The invention, Collaborative Security and Decision Making in SOA environment, answers this question and turns this beautiful idea into a working system. The illustration above provides an example of collaborative interaction of transportation services. Ground and Aviation transports, including unmanned aerial vehicles (UAV), are controlled by multiple services:
- Operational Systems
- Traffic Controllers
- Scheduling and Planning Services
- Geospatial Services
- Situational Awareness Services (weather and external objects)
- Disruption Management Services
- Optimization Services (general trajectory optimization)
- Transportation Expert Services (specific transport knowledgebase)
- Conversational Rules Services (multi-dimensional matrix of rules and scenarios, capable to expand in conversation with SME)
- Subject Mater Experts can be engaged for unexpected situations to expand the rules and scenarios with new situations; more often in the beginning and not so often when the system can recognize more and more situational cases

One of the keys, similar to people’s collaboration, is the ability of system services to converse, understand, and adapt to the changes. The difficult part is the mixture of business and technical slangs in expressing events and situations. Generally speaking, business prefers natural language, while technical language is XML and web services standards. Necessity of the semantic bridge is obvious. The bridge is coming especially handy when Subject Matter Experts must intervene in an unexpected situational scenario.

Conversing with a machine and modeling on-the-fly requires new skills. It requires a SME to understand business and system architecture, in other words to perform a role of a business architect. Business Architects are becoming key players changing corporate culture and promoting new approaches. They need a safe playground.

Business Architecture Sandbox for Enterprise, BASE, offers this playground. BASE facilitates business and IT collaboration and encourages placing the seeds of new technologies in the current business ground.

This relatively new area of integrated software and knowledge engineering opens new horizons to application development. The industry started its heavy turn to Big Data and Business Intelligence demanding a new set of skills. Most of the related products and tools are based on Java. On the top of Core Java, application developers need to learn more about Semantic Technology and come closer to the business side of the story, ideally becoming Business Architects, who understand a bigger picture.


1. - the book online on Cognitive Computing and Semantic Cloud Architecture, Yefim (Jeff) Zhuk

2. Integration-Ready Architecture and Design, by Cambridge University Press, Yefim (Jeff) Zhuk, the book on Software and Knowledge Engineering

3. SOA, Microservices and Software Semantic Evolution, the Dataversity Magazine

4. - Internet Technology University

5. - The message from 2040



- Knowledge-Driven Architecture | US Patent | Yefim Zhuk | Driving applications with business scenarios

- Adaptive Mobile Robot System | US Patent | Yefim Zhuk | Integrating software and knowledge engineering with robotic technologies

- Collaborative security and decision making | US and 15 European countries, Patent| Yefim Zhuk/Boeing | Turning a beautiful idea of collaborative decision into a system

- Rules Collector System and Method | US Patent | Yefim Zhuk/Boeing | Formalizing expert knowledge into rules, which can be used for solving the next problem in the expert-computer brainstorming

- Distributed Active Knowledge and Process | US Patent | Jeff (Yefim) Zhuk/Yahoo | Collaborative access and negotiation for data and services

- Design Factory | Patent Pending

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Distributed Active Knowledge, Knowledge-Driven Architecture, Adaptive Robot Systems, Rules Collector, Collaborative Security and Decisions