New Advances in Intelligence and Security Informatics

By Wenji Mao and FeiYue Wang

The Intelligent Systems Series comprises titles that present state of the art knowledge and the latest advances in intelligent systems. Its scope includes theoretical studies, design methods, and real-world implementations and applications.

Traditionally, Intelligence and Security Informatics (ISI) research and applications have focused on information sharing and data mining, social network analysis, infrastructure protection and emergency responses for security informatics. With the continuous advance of IT technologies and the increasing sophistication of national and international security, in recent years, new directions in ISI research and applications have emerged to address complicated problems with advanced technologies. This book provides a comprehensive and interdisciplinary account of the new advances in ISI area along three fundamental dimensions: methodological issues in security informatics; new technological developments to support security-related modeling, detection, analysis and prediction; and applications and integration in interdisciplinary socio-cultural fields.

• Identifies emerging directions in ISI research and applications that address the research challenges with advanced technologies
• Provides an integrated account of the new advances in ISI field in three core aspects: methodology, technological developments and applications
• Benefits researchers as well as security professionals who are involved in cutting-edge research and applications in security informatics and related fields

• Language: English
• Publisher: Academic Press
• Release date: Apr 16, 2012
• ISBN: 9780123973245

Book preview

Index

Chapter 1

Intelligence and Security Informatics Research Frameworks

Intelligence and security informatics (ISI) is defined as the development of advanced information technologies, systems, algorithms, and databases for international, national, and homeland security-related applications, through an integrated technological, organizational, and policy-based approach [1]. Traditionally, ISI research and applications have focused on information sharing and data mining, social network analysis, infrastructure protection, and emergency responses for security informatics.

With the continuous advance of information technologies and the increasing sophistication of national and international security, in recent years new directions in ISI research and applications have emerged that address the research challenges with advanced technologies. To meet the challenges and achieve a methodology shift in ISI research and applications, we propose a social computing-based research paradigm consisting of a three-stage modeling, analysis, and control approach that researchers have used successfully to solve many natural and engineering science problems.

1.1 Research Methodology and Frameworks for ISI

In the past few years, ISI has experienced tremendous growth and made significant progress in academic research and practice involving both government agencies and industry. There have been a number of research methods and frameworks proposed to support intelligence and security informatics-related studies.

The Dark Web project developed one of the best-known ISI research frameworks. The project has for several years collected a wide variety of data relating to, and emanating from, extremist and terrorist groups. These data have included websites, multimedia material linked to the websites, forums, blogs, virtual world implementations, etc. The early system design contained three modules: data acquisition, data preparation, and system functionality. To further support its potential use as an open-source intelligence tool, several improvements in system functionality were later made [2].

New advances in ISI have emerged in recent years, especially the advancements in social-cultural computing. Subrahmanian [3] argues that cultural, economic, political, and religious factors can help policymakers predict the behavior of radical groups and proposes a cultural reasoning framework, CARA (Cognitive Architecture for Reasoning about Adversaries) [4]. CARA is comprised of four components, namely a Semantic Web extraction engine to elicit organization data, an opinion-mining engine that captures the group's opinions, an algorithm to correlate culturally relevant variables with the actions the organization takes, and a simulation environment within which analysts and users can experiment on hypothetical situations. When a new event occurs, CARA can forecast the k most probable sets of actions the group might take in a few minutes. To further develop CARA, several algorithms have been proposed to forecast the behavior of radical groups [5, 6].

Social computing refers to the computational facilitation of social studies and human social dynamics, as well as the design and use of information and communication technologies that consider the social context. As a new paradigm of computing and technology development, social computing can help us understand and analyze individual and organizational behavior and facilitate ISI research and applications in many aspects. To meet the challenges and achieve a methodology shift in ISI research and applications, we propose a social computing-based research paradigm called the ACP approach. Below, we introduce the three major components of ACP—namely, artificial societies for modeling (A), computational experiments for analysis (C), and parallel execution for control (P)—and discuss the philosophical and physical foundations of the ACP approach.

1.2 The ACP Approach

To achieve a paradigm shift in ISI research and applications, we propose adapting the three-stage modeling, analysis, and control approach that researchers have used successfully to solve many natural and engineering science problems [7, 8]. In this section, we describe what we call the ACP approach [8–12]: artificial societies for modeling, computational experiments for analysis, and parallel execution for control.

1.2.1 Modeling with Artificial Societies

There are as yet no effective, widely accepted methods for modeling complex systems, especially those involving human behavior and social organizations. Agent-based artificial societies or general artificial systems may be the most promising approach.

Modeling with artificial societies has three main parts: agents, environments, and rules for interactions. In this modeling approach, the accuracy of approximation to real systems is no longer the only objective, as it is in traditional computer simulations. Instead, the model society represented by an artificial system is considered real—an alternative possible realization of the target society. Along this line of thinking, the real society is also one possible realization. So, the behaviors of two societies, real and artificial, are different but are considered equivalent for evaluation and