Counterterrorism resource allocation during a pandemic: The effects of dynamic target valuations when facing a strategic terrorist

The outbreak of pandemics such as COVID-19 can result in cascading effects for global systemic risk. To combat an ongoing pandemic, governmental resources are largely allocated toward supporting the health of the public and economy. This shift in attention can lead to security vulnerabilities which are exploited by terrorists. In view of this, counterterrorism during a pandemic is of critical interest to the safety and well-being of the global society. Most notably, the population flows among potential targets are likely to change in conjunction with the trend of the health crisis, which leads to fluctuations in target valuations. In this situation, a new challenge for the defender is to optimally allocate his/her resources among targets that have changing valuations, where his/her intention is to minimize the expected losses from potential terrorist attacks. In order to deal with this challenge, in this paper, we first develop a defender-attacker game in sequential form, where the target valuations can change as a result of the pandemic. Then we analyze the effects of a pandemic on counterterrorism resource allocation from the perspective of dynamic target valuations. Finally, we provide some examples to display the theoretical results, and present a case study to illustrate the usability of our proposed model during a pandemic.

Defensive Resource Allocation: The Roles of Forecast Information and Risk Control

In defensive resource allocation problems, the defender usually collects some forecast information about the attacker. However, the forecast information may be incorrect, which means that there could be a risk associated with the defender using it in their decision making. In this article, we propose a forecast and risk control (FRC) framework to manage the risk in defensive resource allocation with forecast information. In the FRC framework, we introduce a new measure of risk and three types of defense plans: riskless defense plan, risky defense plan, and risk-control defense plan. Several desirable properties based on the concepts of reward and penalty show that the risk-control defense plan is a general form to support defensive resource allocation. Subsequently, we study a specific defensive allocation problem with forecast information and develop an optimization model that considers the forecast information and the defender's risk tolerance level in order to obtain the risk-control defense plan with maximum reward. Furthermore, we provide some numerical analysis to illustrate the effects of forecast information and risk tolerance level on the risk-control defense plan. Finally, a numerical case study is presented to demonstrate the usability of a risk-control defense plan.

Self-powered multilayer radioisotope identification device

PURPOSE

This is a computational study to develop a rugged self-powered Radioisotope Identification Device (RIID). The principle of operation relies on the High Energy Current (HEC) concept (Zygmanski and Sajo, Med Phys. 43 4-15, 2016) with measurement of fast electron currents between low-Z and high-Z thin-film electrodes separated by nanoporous aerogel films in a multilayer detector structure whose prototypes were previously investigated (Brivio, Albert, Freund, Gagne, Sajo and Zygmanski, Med Phys, 46 4233-4240, 2019), (Brivio, Albert, Gagne, Freund, Sajo and Zygmanski, J Phys D Appl Phys, 53 265303, 2020). Here, we present an optimal detector design that accounts for a wide energy range (keV-MeV) of x-ray-emitting radioisotopes that are of interest to national security and radiation therapy.

MATERIALS

We studied numerous multilayer detector geometries with N = 1..24 basic detector elements composed of 3 electrodes: N x (Al-aerogel-Ta-aerogel-Al). The thicknesses of electrodes and their total number were varied depending on the incident x-ray spectra and its ability to penetrate and interact with the different layers, producing fast electrons. We used radiation transport simulations to find a balanced geometry that accounts for all energies from 10 keV to 6 MeV in a single design with relatively few detector elements (N = 24). In the balanced design, the electrodes have increasing thickness as a function of depth in the detector, ranging from 0.5 μm-Ta and 10 μm-Al at the entrance to 10 mm-Ta and 2.5 mm-Al at the exit. Aerogel thickness was fixed at 50 μm. Electron currents forming RIID signals were acquired from all Ta electrodes. A model function M(x, E_i ) representing the detector yield as a function of the cumulative Ta thickness (x) for 70 monoenergetic incident beams (E) was derived. We also investigated the detector response to selected radioactive isotopes (Pd-103, I-125, Pu-239, U-235, Ir-192, Cs-137, Co-60). Additional studies were performed with Bremsstrahlung spectra produced by electron beams in kVp tubes and in MV Linacs used in radiology and radiation therapy departments. We investigated different algorithms for radioisotope identification that would work for unknown unshielded as well as shielded sources.

RESULTS

Characteristic features of response functions for monoenergetic beams and radioisotopes were determined and used to develop two inverse algorithms of radioisotope identification. Using these algorithms, we were able to identify the unshielded and shielded sources, quantify the minimum, mean and maximum effective energies of the shielded spectra, and estimate the amount of Compton background in the spectrum.

CONCLUSIONS

A multilayer sensor based on fast electron current was optimized and studied in its abilities as RIID. A balanced design permits the identification of radioisotopes with of a wide range of keV-MeV energies. The device is low cost, rugged, self-powered and can withstand very high dose rates, allowing deployment in difficult conditions, including radiation incidents. The algorithm we developed for radioisotope identification and spectral unfolding is robust and it is an important component in practical applications.

An Attacker-defender Resource Allocation Game with Substitution and Complementary Effects

The United States is funding homeland security programs with a large budget (e.g., 74.4 billion for FY 2019). A number of game-theoretic defender-attacker models have been developed to study the optimal defense resource allocation strategies for the government (defender) against the strategic adversary (attacker). However, to the best of our knowledge, the substitution or complementary effects between different types of defensive resources (e.g., human resource, land resource, and capital resource) have not been taken into consideration even though they exist in practice. The article fills this gap by studying a sequential game-theoretical resource allocation model and then exploring how the joint effectiveness of multiple security investments influences the defensive budget allocation among multiple potential targets. Three false belief models have been developed in which only the defender, only the attacker, and both the defender and attacker hold false beliefs about the joint effectiveness of resources. Regression analysis shows that there are significant substitution effects between human and capital resources. The results show that the defender will suffer a higher loss if he fails to consider the substitution or complementary effects. Interestingly, if the attacker holds a false belief while the defender does not, the defender will suffer an even higher loss, especially when the resources are substitutes. However, if both the attacker and defender hold false beliefs, there will be lower loss when resources are complementary. The results also show that the defender should allocate the highly effective resource when the resources substitute each other. This article provides some new insights to the homeland security resource allocation.

Defender-Attacker Games with Asymmetric Player Utilities

The presence of strategic attackers has become an important factor in the security and protection of systems, especially since the 9/11/2001 attacks, and considerable efforts have been dedicated to its study. When defending against the strategic attacker, many existing studies assume that the attacker would seek to minimize the defender's utility, which implies that the defender and attacker have symmetric utilities. However, the attacker's objective is determined by its own valuation of the system and target of the attack, which is not necessarily consistent with the defender's utility. If the attacker unexpectedly targets a different utility, then the defense strategy might no longer be optimal. In particular, the defense strategy could be inferior if the attacker's utility is not known to the defender. This study considers a situation where the defender's utility is the system survivability and the attacker's utility is the expected number of destroyed elements in the system. We investigate possible attack strategies under these two different utilities and compare (a) the conservative defense strategy when the attack utility is unknown to the defender with (b) the optimal defense strategy when the attack utility is known to the defender. We show that the conservative protection strategy is still optimal under asymmetric utilities when the contest intensity is smaller than one.

Deterrence and Risk Preferences in Sequential Attacker-Defender Games with Continuous Efforts

Most attacker-defender games consider players as risk neutral, whereas in reality attackers and defenders may be risk seeking or risk averse. This article studies the impact of players' risk preferences on their equilibrium behavior and its effect on the notion of deterrence. In particular, we study the effects of risk preferences in a single-period, sequential game where a defender has a continuous range of investment levels that could be strategically chosen to potentially deter an attack. This article presents analytic results related to the effect of attacker and defender risk preferences on the optimal defense effort level and their impact on the deterrence level. Numerical illustrations and some discussion of the effect of risk preferences on deterrence and the utility of using such a model are provided, as well as sensitivity analysis of continuous attack investment levels and uncertainty in the defender's beliefs about the attacker's risk preference. A key contribution of this article is the identification of specific scenarios in which the defender using a model that takes into account risk preferences would be better off than a defender using a traditional risk-neutral model. This study provides insights that could be used by policy analysts and decisionmakers involved in investment decisions in security and safety.

Quantifying Adversary Capabilities to Inform Defensive Resource Allocation

We propose a Bayesian Stackelberg game capable of analyzing the joint effects of both attacker intent and capabilities on optimal defensive strategies. The novel feature of our model is the use of contest success functions from economics to capture the extent to which the success of an attack is attributable to the adversary's capability (as well as the level of defensive investment), rather than pure luck. Results of a two-target example suggest that precise assessment of attacker intent may not be necessary if we have poor estimates of attacker capability.

Portfolio analysis of layered security measures

Layered defenses are necessary for protecting the public from terrorist attacks. Designing a system of such defensive measures requires consideration of the interaction of these countermeasures. In this article, we present an analysis of a layered security system within the lower Manhattan area. It shows how portfolios of security measures can be evaluated through portfolio decision analysis. Consideration is given to the total benefits and costs of the system. Portfolio diagrams are created that help communicate alternatives among stakeholders who have differing views on the tradeoffs between security and economic activity.

Managing risk at the Tucson Sector of the U.S. Border Patrol

This article describes a risk analysis used to inform resource allocation at the Tucson Sector of the U.S. Border Patrol, the busiest sector for alien and drug trafficking along the Southwest land border with Mexico. The model and methodology that underlie this analysis are generally applicable to many resource allocation decisions regarding the management of frequently occurring hazards, decisions regularly made by officials at all levels of the homeland security enterprise. The analysis was executed by agents without previous risk expertise working under a short time frame, and the findings from the analysis were used to inform several resource allocation decisions.

Digital detectives and virtual volunteers: Integrating emergent online communities into disaster response operations

The demonstration of altruistic behaviours by disaster survivors, and even those observing emergencies from afar, is well documented. Over the past few decades, government-sponsored crisis planning has evolved to include affiliated volunteer agencies, with a general acknowledgment of the need to plan for unaffiliated or spontaneous volunteers. Just as the understanding of the need for volunteers has grown, so too have the ways in which volunteers are able to donate their time and skills. The popularity of social media networks and online communities provide new ways for the public to get involved in disaster response. Public service agencies should be proactive in investigating these emerging platforms and understanding their impacts during crises. Established methods of integrating on-scene volunteers into post-disaster response operations can be used as templates for creating virtual volunteer programmes.

Catastrophic Anachronisms: The Past, Present and Future of Disaster Medicine

There is a worldwide spiraling risk for more frequent catastrophic events involving multiple casualties, not only in terms of acute injury and illness, but also subsequent psychological and public health concerns. Today, such events will likely be multinational in nature, even when localized to a particular venue and this require international cooperation in terms of prevention, mitigation and relief. The best approach to preparing for disasters is to expand, modify and enhance current local ∖Jobname: S34055 Batch number: 00060 infrastructures and capabilities for managing the multiple types of disaster scenarios and create a number of inter-facility cooperative agreements in advance. Aside from safer internal locations for ICUs and surgical theaters, certain structural changes will need to be installed such as modified ventilation systems, protected water supplies, decontamination mechanisms and security renovations. A key strategy will be to proliferate interoperable, multi-disciplinary, all-hazards training initiatives such as the AMA National Disaster Life Support courses. Purchases of cadres of antidotes, antibiotics and hemoglobin-based oxygen carriers should be coordinated regionally, stored in secure locations and made readily-available for the applicable disaster scenario.

Evaluation of Handheld Radionuclide Identifiers

Characterization of commercially available instruments for measurement and identification of unknown radionuclides was carried out in support of the development and testing of the American National Standards Institute (ANSI) standard, N42.34, "Performance Criteria for Hand-held Instruments for the Detection and Identification of Radionuclides." Measurements were based on the performance of the devices, i.e., the capability of the detectors to ensure a correct radionuclide identification in a given time interval for various radioactive sources.