A Model For Risk Factors' Detection And Evaluation Of Migrating Workflow System

The migrating workflow, as a new research field of workflow management, leads the technology of mobile computing to traditional migrating workflow system and separates it into three parts:workflow engine, workplace and migrating instance.Migrating instance is the central part for task execution and can be explained as affect of the integrated static workflow on workplace in operation, local rules and strategies and the response of the users. The execution of workflow can be explained as a process of the cooperating of many migrating instances carrying the task specification, automatically finding resources and migrating, and completing tasks at the target workplace and returning. The migrating workflow solves the insufficiency of flexibility and dilatancy of traditional workflow, reduces the transmission of data and the remote function call and makes the workflow more flexibly adapt to the dynamic environment. Therefore, migrating workflow is especially suitable for the distributed and concurrent interaction which involves transmitting large amount of data and remote function calls.Migrating workflow provides a new research field for workflow technology, but at the same time brings new security problems. The security problems in migrating workflow system can be considered from two aspects in the main, which are problems of workplace security and problems of migrating instance security. The migrating instance security includes the migrating security and operating security. During the operating process, protecting the migrating instance from being attacked by malicious hosts is especially important. Now, concerning the security problems, two methods can be applied: precaution and detection. The former is rather passive and the latter is comparatively active, though very few researches have been made in this field, which proves the significance of this research.Artificial Immune System (AIS) is a new intelligent method simulating natural immune system. AIS aims at using ideas gleaned from immunology in order to develop systems capable of performing a wide range of tasks in various research areas such as noise tolerance, self-learning, self-organization and memory, thus having enormous potential supplying novel methods to solve complex problems. AIS has been widely used in many areas including pattern recognition, failure detection, auto-control and computer security, and become a hotspot in recent years.Based on the research background, this thesis puts forward the detective model and assessing model for the danger factors of migrating workflow system. When migrating instance is operating at current location, a detection of the next work position should be made in advance to assess the security level. In the detective module, an agent constituted by artificial immunity serves as the outpost. Negative Selection Algorithm is applied to construct the antibody library of the workplace and the danger factors are defined as antigen. Through the affinity calculation of the antibody and antigen, the danger factors are detected. The assessing module, based on the density of the antigen and the analysis of the influence coefficient of the antigen over the migrating instance, determines the danger level of the workplace. This thesis provides formal description for the immune body and introduces in details the construction algorithm of the immune body's functional modules, the detection process and the updating mechanism of the detector. This thesis also elaborates the definition of danger signal and the calculating methods of the affinity and density of the antibody and the danger coefficient. Through simulation experiment, the thesis proves that this system has very high immune efficiency and detecting efficiency and very low error positive rate.