Review Essay: By Dr. Joshua Sinai
With the world of terrorism and counterterrorism impacted by latest advances in sophisticated technologies, such as in cyberspace, weaponry, logistics, software analytics, including artificial intelligence, new intelligence analytic methodologies and technologies are required to effectively analyze such trends not only in government and law enforcement counterterrorism agencies, but at the academic level, as well. Numerous books have been published on these subjects, with a representative sample of 17 books listed and briefly reviewed in this essay.
The books below are listed in alphabetical order, per the authors’ last names. This listing is followed by the books’ capsule reviewed coverage arranged by topic.
Jonathan M. Acuff, et al., Introduction to Intelligence: Institutions, Operations, and Analysis (Thousand Oaks, CA: SAGE/CQ Press, 2022), 440 pp., US $80.54 [Paperback], ISBN: 978-1-54437467-3.
Richard M. Adler, Bending the Law of Unintended Consequences: A Test-Drive Method for Critical Decision-Making in Organizations (Cham, Switzerland: Springer, 2020), 328 pp., US $79.99 [Hardcover]. US $54.99 [Paperback], ISBN: 978-3-0303-2716-3.
Patrick T. Biltgen, AI for Defense and Intelligence (Chantilly, VA: Tallaios, 2025), 379 pp., US $69.99 [Hardcover], ISBN: 979-8-2183-5148-9.
Robert M. Clark, Geospatial Intelligence: Origins and Evolution (Washington, DC: Georgetown University Press, 2020), 320 pp., US $149.95 [Hardcover], US $49.95 [Paperback], ISBN: 978-1-6471-2011-5.
Thomas E. Copeland, Fool Me Twice: Intelligence Failure and Mass Casualty Terrorism (Boston, MA/Leiden, The Netherlands: Martinus Nijhoff Publishers, 2007), 292 pp., US $156.62 [Hardcover], ISBN: 978-9-0041-5845-0.
Erik J. Dahl, Intelligence and Surprise Attack: Failure and Success from Pearl Harbor to 9/11 and Beyond (Washington, DC: Georgetown University Press, 2013), 256 pp., US $29.95 [Paperback], ISBN: 978-1-5890-1998-0.
Jack Dangermond, The Power of Where (Redlands, CA: Esri Press, 2024), 300 pp., $36.50 [Paperback], ISBN: 978-1-5894-8606-5.
Bruce Garvey and Adam D.M. Svendsen, Navigating Uncertainty Using Foresight Intelligence: A Guidebook for Scoping Scenario Options in Cyber and Beyond (Cham, Switzerland: Springer, 2024), 372 pp., US $109.99 [Hardcover], ISBN: 978-3-0316-6114-3.
John A. Gentry and Joseph S. Gordon, Strategic Warning Intelligence: History, Challenges, and Prospects (Washington, DC: Georgetown University Press, 2019), 296 pp., US $103.29 [Hardcover], US $33.89 [Paperback], ISBN: 978-1-6261-6655-4.
Robert Mandel, AI & Early Warning Systems: Technology Innovation for National Security (Bouilder, CO: Lynne Rienner Publishers, 2025), 279 pp., US $115.00 [Hardcover], ISBN: 978-1-9625-5168-7.
Colleen McCue, Data Mining and Predictive Analysis [Second Edition] (Boston, MA: Elsevier/Butterworth-Heinemann, 2015), 422 pp., US $78.89 [Paperback], ISBN: 978-0-1280-0229-2.
Thomas L. Norman, Risk Analysis and Security Countermeasures Selection [Second Edition] (Boca Raton, FL: CRC Press, 2015), 483 pp., US $126.00 [Hardcover], ISBN: 978-1-4822-4419-9.
Katherine Hibbs Pherson and Randolph H. Pherson, Critical Thinking for Strategic Intelligence [3rd Edition] (Thousand Oaks, CA: SAGE/CQ Press, 2021), 408 pp., US $40.00 [Paperback], ISBN: 978-1-5442-7426-0.
Randolph H. Pherson and Richards J. Heuer Jr., Structured Analytic Techniques for Intelligence Analysis [3rd Edition] (Thousand Oaks, CA: SAGE/CQ Press, 2021), 385 pp., US $123.95 [Paperback], ISBN: 978-1-5063-6893-1.
Hank Prunckun, Methods for Inquiry for Intelligence Analysis [Third Edition] (Lanham, MD: Rowman & Littlefield, 2019), 248 pp., US $121.00 [Hardcover], US $60.00 [Paperback], ISBN: 978-1-5381-2587-8.
Julian Richards, The Art and Science of Intelligence Analysis (New York, NY: Oxford University Press, 2010), 197 pp., US $69.28 [Paperback], ISBN: 978-0-1995-7845-0.
Itai Shapira, Israeli National Intelligence Culture: Problem-Solving, Exceptionalism, and Pragmatism (New York, NY: Routledge, 2025), 270 pp., US $140.00 [Hardcover], ISBN: 978-1-0327-7811-2.
Lessons From Government Intelligence Agencies’ Failed Anticipation of Surprise Attacks
As a category of asymmetric warfare, with a small insurgent group or lone actor targeting its larger country adversary, terrorists operate covertly with their violent operations taking the form of surprise attacks. The surprise nature of their unexpected attacks increases the likelihood that their targets will be accessible. The role of government intelligence agencies in anticipating surprise attacks by their terrorist adversaries is crucial, as they provide critical strategic, operational, and tactical warnings and insights that can preempt or prevent such incidents.
Understanding the historical context for examples where terrorists carried out successful surprise attacks, or were preempted from carrying them out, therefore, is important for counterterrorism analysts. The authors who discuss this subject include Erik J. Dahl’s Intelligence and Surprise Attacks: Failure and Success from Pearl Harbor to 9/11 and Beyond, whose theory of preventive action posits that the key to success in preempting surprise attacks is the acquisition of precise, tactical level intelligence combined with the decision makers who listen to and follow-up on the warnings they receive from their intelligence staff (p. 176). In Fool Me Twice: Intelligence Failure and Mass Casualty Terrorism, Thomas E. Copeland examines the surprise terrorist attacks against the World Trade Center (2003), the 1995 bombing of the Murrah Federal Building (Oklahoma City), the Khobar Towers bombing, the bombings of the U.S. Embassies in Kenya and Tanzania, and the 9/11 attacks to examine the questions concerning the nature of the surprise, were details of the event foreseeable?, what was the threat environment at the time, were the successful attacks the product of intelligence failures or policy failures, and were the surprises preventable (pp. xii-xiv).
In Israeli National Intelligence Culture, Itai Shapira examines the failure of the Israeli intelligence agencies to anticipate Hamas’s planning to launch its devastatingly successful surprise cross-border attack against Israeli on October 7, 2023. One factor was its “fixated analytical paradigm according to which Hamas was deterred from initiating a war with Israel” despite contradictory intelligence-derived information that was considered as “weak signals” (p. 239). This resulted in “groupthink and fixation” overtaking contrary assessments (p. 239).
To avoid failures by intelligence services to anticipate major surprise attacks by their terrorist adversaries, the intelligence analytic discipline utilizes strategic warning methodologies. As explained by Julian Richards in The Art and Science of Intelligence Analysis, the potential points of failure in the intelligence cycle begin with the inadequate setting by policy-makers of collection requirements, which require appropriate information/data gathering, which is followed by effective analysis (including the formulation of alternative future scenarios), and then the efficient dissemination and implementation of response measures by decision-makers (p. 33).
As part of the strategic warning analytic process, as explained by John A. Gentry and Joseph S. Gordon in Strategic Warning Intelligence, this serves to alert national leaders to the emergence of significant future threats and the measures required to address them (p. 11). These are framed as alternative future threat scenarios that are assessed as possible or plausible, and as inflicting high- or low-impact (p. 132).
Textbooks on Intelligence Analytic Methodologies
The academic discipline of intelligence analysis in the form of textbooks encompasses a spectrum of approaches and methodologies. In Jonathan M. Acuff, et. al. (Eds.), Introduction to Intelligence: Institutions, Operations, and Analysis, the volume’s chapters on intelligence analysis and analytic methods are especially pertinent as they cover the topic of prediction (short-term) and forecasting (long-term) of likely future incidents by applying an estimative probability methodology consisting of almost no chance, very unlikely, unlikely, roughly even chance, likely, very likely, and almost certainly (p. 263). It also discusses software-based analytic techniques such as network analysis, which graphically represents relationships in an adversary’s network (pp. 282-284), and indicators, which serve as drivers of future events (pp. 286-288).
In Methods of Inquiry for Intelligence Analysis, Hank Prunckun discusses significant intelligence methodologies to examine adversarial threats, some of which are discussed by the other volumes, as well. These consist of qualitative analytics, such as SWOT analysis (strengths, weaknesses, opportunities, and threats), Pest analysis (political, economic, social, and technological), analysis of competing hypotheses, which are outlined in a matrix, and network analysis, in which a matrix is applied to outline associations among adversarial subjects. Quantitative analytics consist of organizing intelligence-type data according to numbers that analysts attribute to them for statistical testing, which are applied to four levels of measurement: nominal data, ordinal data, interval data, and ratio data (p. 113). The volume also discusses the key parts of a target profile in terms of personal details, criminal record, and target planning (pp. 139-152), as well as conducting risk assessments and producing national security policy assessment reports.
Critical Thinking for Strategic Intelligence, by Katherine Hibbs Pherson and Randolph H. Pherson, is a comprehensive textbook for developing intelligence analytic methodologies and techniques. These include structured analytic techniques, such as the cross-impact matrix, network analysis, multiple scenario generation, quadrant crunching, and the complexity manager. The chapter on portraying probability levels of confidence compares how they are defined and scaled by the United States, Canada, and the UK, as well as how quantitative data should be used in intelligence reports. The textbook is complemented by the handbook Structured Analytic Techniques for Intelligence Analysis, Randolph H. Pherson and Richards J. Heuer Jr., which features sixty-six analytic methodologies and techniques employed in intelligence agencies. These include matrices, process maps, gantt charts, mind maps, Venn analysis, network analysis, chronologies and timelines, alternative competing analyses, deception detection, key drivers generation, indicators generation, critical path analysis, decision trees, and complexity manager.
Patrick McGlynn’s Taking Intelligence Analysis to the Next Level includes a chapter on futures analysis. Forecasting, the author explains, is “an objective estimation technique used to predict future data as a function of past known data” (p. 164). He adds that quantitative forecasting can predict future data (or event cycles) when past numerical data is available, while qualitative forecasting is a subjective technique, which is applied to potential intermediate or long-range events, through the Delphi, alternative future scenario, futures wheel, horizon scanning, and other forecasting methods (pp. 164-195).
Security Risk Management
The integrated application of security risk management (SRM) frameworks is considered an important component of effective government counterterrorism campaigns. With security risk management a function of the correlation of threat (the potential to be attacked by a threat actor), vulnerability (to be attacked), and consequence (of being attacked), operationalizing it can reveal a country’s level of risk tolerance, which can enable it to prioritize mitigation measures to lower the overall risk to terrorist attacks.
Thomas L. Norman’s Risk Analysis and Security Countermeasure Selection is considered one of the leading handbooks on security risk management. It covers topics such as an overview of risk, assessing threat, vulnerability and consequence analysis, estimating probability to be attacked and prioritizing the threat actors, and implementing countermeasures. Among the SRM frameworks, it also discusses the widely used adversarial target selection known as CARVER, the acronym for criticality, access, recuperability, vulnerability, effect on the population, and recognizability. The handbook’s discussion is operationalized by numerous tables, matrices and checklists.
In Bending the Law of Unintended Consequences: A Test-Drive Method for Critical Decision-Making in Organizations, Richard M. Adler arranges risks into the three categories of strategic, preventable, and external. With risk assessment encompassing quantitative and qualitative dimensions, he calculates risk according to the formula of Risk = likelihood of occurrence plus economic value of loss [to which we might add the value of the human loss of life – JS], with the management of risk falling into the four categories of avoidance, sharing, reduction, and acceptance (pp. 192-195). To manage a risk reduction portfolio (which also applies to a government’s counterterrorism campaign), he posits as performance effectiveness metrics four outcomes: reduction of risk, residual risk (the remaining level of risk following a risk reduction campaign), cost, such as in the form of a return-on-investment (ROI), and time efficiency, such a effectiveness in reducing risk “sooner rather than later” (p. 198).
Risk assessment is also discussed in Prunckun’s Methods of Inquiry for Intelligence Analysis, with the equation of risk = likelihood + consequence operationalizing the process of managing risk (p. 202). It also features tables outlining the rankings of risk likelihood, consequence, and overall risk to a variety of hazards.
Geo-Spatial Analytics
With terrorists operating clandestinely and difficult to locate, the application of geospatial analytics is beneficial to terrorism and counterterrorism analysts, as it enables them to map, predict, and potentially prevent terrorist operations and incidents against their targets in a spatiotemporal context.
In The Power of Where, Jack Dangermond, the co-founder and President of Esri, a major geo-spatial corporation, explains that digital mapping technology and online geospatial data have created a “global geospatial nervous system” through “an array of instruments, satellites, sensors, and cameras [that – JS] measure on a continuous basis almost everything that can be detected” on the earth’s various surfaces (p. 2). GIS, the author explains, integrates and synthesize such disparate data, which enable ‘previously hidden views of the world’ (p. 2). Geographic data, not only captures major geospatial data categories such as the environment, critical infrastructure, and boundaries, but people, as well, such as the incidences of crime and terrorism (p. 52). Geospatial modeling tools such terrain analysis, site suitability analysis, and 3D analysis (pp. 168-173).
Robert M. Clark’s Geospatial Intelligence: Origins and Evolution examines the field of GEOINT as the synthesis of geography, cartography, remote sensing, photogrammetry, geopolitics, and geographic information systems (GIS). The chapter on the tools of geospatial intelligence terms them as geomatics, GIS, geo-visualization, big data, data analytics and visual analytics, and geospatial simulation modeling. Future trends in geo-spatial analytics, the author writes, include applying graphic techniques to create and update layered digital maps in real time, applying techniques of virtual reality to create a computer image of the real world, and equipping drones and autonomous vehicles with remote-sensing artificial intelligence technologies to search for items of interest from distant regions (pp. 304-310).
Artificial Intelligence in Intelligence Analysis
The application of artificial intelligence (AI) systems have become prevalent in supporting intelligence analysis, with this new technology enabling faster processing of vast datasets. While it has not transformed traditional methods of intelligence analysis, it is being applied in predictive analytics (utilizing historical data to forecast future trends), prescriptive analytics (recommending actions to achieve specific objectives), and anomaly detection (identifying potentially anomalous activities in datasets).
Colleen McCue’s Data Mining and Predictive Analysis was one of the earliest books to examine the algorithmic technology that became artificial intelligence and how it was being used in intelligence and security analysis. It discusses how advanced analytics in the form of algorithmic-based data mining is applied to risk and threat assessment, social network analysis, and geospatial tools, including surveillance detection and the behavioral analysis of violent crime.
In AI & Early Warning Systems: Technology Innovation for National Security, Robert Mandel observes that “AI can perform anomaly detection, classification, clustering, continuous estimation, data generation, optimization, ranking, and recommendation and is especially adept at identifying relevant alternative explanations, disruptive discontinuities, underexplored trends, unrealized risks, and missed data interconnections” (p. 48).
The advanced analytical capabilities of AI are further examined in AI for Defense and Intelligence, by Patrick T. Biltgen. He notes that what is termed Artificial General Intelligence (AGI), a self-++learning machine capable of performing human tasks, in national security “could be utilized for tasks like information extraction, automated report generation, or threat detection” (p. 333). In intelligence missions, the author observes, AGI could upgrade what is currently a time-consuming process to identify connections by analyzing vast quantities of disparate data into a rapid process “to provide more accurate and timely intelligence, helping to anticipate threats and providing strategic advances” (p. 337).
The application of AI in upgrading intelligence analysis is also discussed in Chapter 12, “Trends in Intelligence Analysis” (pp. 267-311) in Patrick McGlynn’s Taking Intelligence to the Next Level, and in the section on “Models and Artificial Intelligence” (pp. 102-113) in Critical Thinking for Strategic Intelligence, by Katherine Hibbs Person and Randolph H. Pherson.
Conclusion
This capsule-based overview of selected textbooks, handbooks, and general books about the application of intelligence analytic methodologies and technologies to examine terrorism and counter-terrorism is intended to provide a representative snapshot of the vast published literature on these subjects. As terrorists, whether as organized groups, loosely affiliated networks, and lone actors incorporate technological innovations in their warfare, government counter-terrorism agencies are also innovating analytically and technologically in their response measures. This is reflected in the new publications which are continuously being published on these issues.
Dr. Joshua Sinai is Professor of Practice, Intelligence & Global Security Studies at Capitol Technology University, in Laurel, MD. He is the author of the best-selling “Active Shooter – A Handbook on Prevention” (ASIS International, 2016. 2nd edition). |
