Process Mining

Research and White Papers

We’re publishing research and adding new white papers frequently. Check back often.

The Coin of the Realm: Understanding and Predicting Relative System BehaviorThis article discusses a way of understanding and predicting relative system behavior–or, what we call: “The Coin of the Realm.” From a systems confrontation perspective, understanding and predicting relative blue (friendly) and red (adversary) systems behavior is of great value for private organizations, government agencies, and the national security community in general. Coordinated activities, emergent (uncoordinated) relationships, and stimulus-response patterns between systems are all discoverable. After discussing the importance of predicting relative system behavior, we define our usage of entropy. Then, we review a recent study of interacting geostationary (GEO) satellite ecosystems. We then present several case studies which relate the findings to other domains of national security interest.

GEO Satellite Ecosystem Relative Behavior: A Cross-correlation Study: In this unpublished study, we analyzed geostationary (GEO) resident space object (RSO) orbital maneuver ecosystems from the United States (US), the Commonwealth of Independent States (CIS), and the People’s Republic of China (PRC). Satellites from each country were selected based upon observed high maneuver variety. Time series information entropy measures were cross-correlated by lagging observations (+/-) 7 days to find objectively how they match up with each other and where the best matches occur. When the time series is filtered down to a 1-month period, larger statistically significant correlations are present among the three countries compared to a longer analysis time period. For both the US and CIS, maneuver variety tends to precede PRC maneuver activity by 5-7 days. Correlations may reflect a general tendency for satellite operators, by country, to react according to near-term predictable schedules. Continual sliding window time series cross-correlation may be an efficient, explainable method for understanding changing operational tempo and tactics. A future work agenda is described.

Process Mining, Situational Awareness, and Competitive Advantage: In this article, we explain how process mining is being adapted for decision-making beyond understanding typical business processes. After reviewing traditional process mining utility in a corporate context, we describe our methodology for examining self-organizing process ecosystems. The United States Space Force (USSF), for example, is prototyping process technologies which allow space operators to plan and execute counter-maneuvers on orbit. We then make the case that these technologies may improve situational awareness and competitive advantage for businesses.

Detecting Botnet Signals Using Process Mining: Detecting bots and elucidating botnets is an active area of research. This draft journal article presents weaponized bot detection analysis results from an analysis of an ISIS terrorist Twitter dataset using process technologies. A future effort is presented to understand cross-platform choreographed information warfare campaigns and recursive adversarial modeling.

Process Mining Organization Email Data and National Security Implications: Tremendous intelligence is contained within unstructured organizational data sources. Properly analyzed, these data provide government and private organizations with actionable management and risk mitigation insights. Using explainable process technologies combined with natural language processing, a private critical infrastructure participant’s organizational process model is discovered from semi-structured email data. Data derived from the process model are presented which elucidate internal operations. National security implications and future research needs are described.

A Process Mining Approach for Protecting Self-Organizing Critical Infrastructure Ecosystems: Self-organized ecosystems are found throughout the natural world, including critical infrastructure. Self-organized criticality is the tendency of some systems to naturally self-organize into critical states far from equilibrium and which are barely stable. Small changes or stimuli can result in cascading chain reactions which may have unwanted or devastating effects on economies or societies. Process technologies offer an expedient method for simulating self-organized critical infrastructure ecosystems, understanding criticality within these ecosystems, and adopting mitigation strategies analogous to controlled avalanches. Several case studies from broad domains present naturally occurring criticality as well as deliberate ecosystem attacks designed to induce criticality or trigger catastrophic events. (In print) 

Whale Ecosystem Pattern of LifeWe performed a pattern of life analysis using whale telemetry data; the preliminary results are interesting and warrant more rigorous statistical testing. This research was part of a Department of Defense AFWERX (Air Force/Space Force) funded small business research opportunity (SBIR) designed to understand the effects of space weather phenomena on satellite ecosystems. Changes in whale behavior during different periods of solar intensity are evident to the naked eye. Behavioral differences by gender are evident, as well. Using whale ecosystems as a proxy, our objective is to determine if our data tools may improve Space Domain Awareness using an “ecosystem” approach that combines advancements in process mining and artificial intelligence to monitor and predict impacts from space weather on space assets, links, and maneuvers.

COVID Disease ProcessUsing publicly available data, we created COVID patient flow process models for different patient cohorts. The disease progression processes are different to the naked eye for people with comorbidities compared to relatively healthy patients. With enhancements, these kinds of disease process models may improve decision & policy making, help optimize deployment of rapidly-emerging technologies, optimize patient workflow, help healthcare professionals understand emerging best practices, model geographic spread, plus other agent-based simulations.

Space Object Process Analysis: Objects in space from four different countries are examined from a process perspective using explainable artificial intelligence. For all countries, objects tend to remain predominantly in the same process activity state. Activity state transitions are observed, however, suggesting intentional maneuver, object degradation, or other ecosystem behaviors. Future work is suggested.

This INFORMS ORMS article describes the right way to adopt process mining in your organization.

FOCAL Information Warfare Defense StandardTM: This Information Warfare Defense Standard helps public and private critical infrastructure participants defend against the growing information and cognitive threat, which is fueled by weaponized AI. It may also facilitate a whole-of-society effort to protect freedom and individual liberty. Five interlocking  tenets help organizations shift culture, train the workforce, identify vulnerabilities, prepare for and recover from attack, and contribute to the community as a vested stakeholder. This short article offers and introduction, and a detailed technical paper accompanies the standard, as well. The FOCAL Information Warfare Defense StandardTM is available for free. Contact us to request a copy.

Process Mining: The Missing Capability in Information WarfareFrom an information warfare perspective, The Cold War never ended. Moreover, the 21st Century presents vivid new security challenges related to information weaponry. This article describes novel, scalable, and extensible process-oriented methodologies not currently part of the United States’ informational warfare solution set.