On Determining Specifications and Selections of Alternative Technologies for Airport Checked-Baggage Security Screening

Federal law mandates that every checked bag at all commercial airports be screened by explosive detection systems (EDS), explosive trace detection systems (ETD), or alternative technologies. These technologies serve as critical components of airport security systems that strive to reduce security risks at both national and global levels. To improve the operational efficiency and airport security, emerging image-based technologies have been developed, such as dual-energy X-ray (DX), backscatter X-ray (BX), and multiview tomography (MVT). These technologies differ widely in purchasing cost, maintenance cost, operating cost, processing rate, and accuracy. Based on a mathematical framework that takes into account all these factors, this article investigates two critical issues for operating screening devices: setting specifications for continuous security responses by different technologies; and selecting technology or combination of technologies for efficient 100% baggage screening. For continuous security responses, specifications or thresholds are used for classifying threat items from nonthreat items. By investigating the setting of specifications on system security responses, this article assesses the risk and cost effectiveness of various technologies for both single-device and two-device systems. The findings provide the best selection of image-based technologies for both single-device and two-device systems. Our study suggests that two-device systems outperform single-device systems in terms of both cost effectiveness and accuracy. The model can be readily extended to evaluate risk and cost effectiveness of multiple-device systems for airport checked-baggage security screening.     

Analyzing the Cost of Screening Selectee and Non-Selectee Baggage

Determining how to effectively operate security devices is as important to overall system performance as developing more sensitive security devices. In light of recent federal mandates for 100% screening of all checked baggage, this research studies the trade-offs between screening only selectee checked baggage and screening both selectee and non-selectee checked baggage for a single baggage screening security device deployed at an airport. This trade-off is represented using a cost model that incorporates the cost of the baggage screening security device, the volume of checked baggage processed through the device, and the outcomes that occur when the device is used. The cost model captures the cost of deploying, maintaining, and operating a single baggage screening security device over a one-year period. The study concludes that as excess baggage screening capacity is used to screen non-selectee checked bags, the expected annual cost increases, the expected annual cost per checked bag screened decreases, and the expected annual cost per expected number of threats detected in the checked bags screened increases. These results indicate that the marginal increase in security per dollar spent is significantly lower when non-selectee checked bags are screened than when only selectee checked bags are screened.     

Identifying Changing Aviation Threat Environments Within an Adaptive Homeland Security Advisory System

A critical component of aviation security consists of screening passengers and baggage to protect airports and aircraft from terrorist threats. Advancements in screening device technology have increased the ability to detect these threats; however, specifying the operational configurations of these devices in response to changes in the threat environment can become difficult. This article proposes to use Fisher information as a statistical measure for detecting changes in the threat environment. The perceived risk of passengers, according to prescreening information and behavior analysis, is analyzed as the passengers sequentially enter the security checkpoint. The alarm responses from the devices used to detect threats are also analyzed to monitor significant changes in the frequency of threat items uncovered. The key results are that this information‐based measure can be used within the Homeland Security Advisory System to indicate changes in threat conditions in real time, and provide the flexibility of security screening detection devices to responsively and automatically adapt operational configurations to these changing threat conditions.     

Addressing the Dependency Problem in Access Security System Architecture Design

The objective of this research is to present a method for evaluating the performance of access control security systems, such as airport security operations. This requires the examination of security system architectures, which involve security technology devices and the algorithms that coordinate their operations. Dependence between device responses in multiple-device systems is a critical practical issue in assessing the performance of such architectures, though no results on this problem have appeared in the literature. This paper presents a method for evaluating when multipledevice security systems with overlapping capabilities are cost-effective. This is achieved using a dependency structure for security system devices to quantify how various technologies interact and to measure the impact of device dependence on system error probabilities. A measure of device response dependence for a two-device system is defined and its properties are explored, including bounds on the dependency measure. The effect of dependence on the system Type I and Type II error probabilities is examined for the two-device system. System performance is compared for independent vs. dependent device responses and desirable dependence relationships are identified. Results are also presented for a cascading sequence of devices. An example is presented to illustrate the results for the two-device system. Implications of these results are discussed, such as how they can be used to identify the optimal use of security devices and to determine whether new technologies warrant investment.     

Measuring the Benefit of Offering Auxiliary Services: Do Bag‐Checkers Differ in Their Sensitivities to Airline Itinerary Attributes?

When firms evaluate their service system design choices, there is typically more uncertainty surrounding the value that a particular auxiliary service provides than there is on the cost of providing that service. To help inform this decision, we propose an approach where we compare the relative value of the segment of passengers who use an auxiliary service to the relative value of the segment that does not use it. We demonstrate this approach for a typical auxiliary service common to the airline industry. In 2008, most US airlines implemented checked baggage fee policies to decrease their costs by reducing the number of customer service agents needed in the check‐in and baggage handling processes. The success of this change has led to a current debate at many of these airlines on whether to make further staffing cuts in these areas, essentially making it even less attractive for passengers to check their baggage. Our proposed methodology helps answer whether passengers who continue to check bags in today's baggage‐fee era are more or less valuable than passengers who do not check bags. We explore this question empirically by examining, through a stated preference survey, if a history of checking or not checking bags can be used to segment passengers based on how their itinerary choices are influenced by common airline service attributes (on‐time performance, itinerary time, number of connections, airfare, and schedule delay). Contrary to the opinions of some top airline executives, we find that the passengers who continue to check bags at airlines that charge baggage fees are generally less sensitive to differences in three of these important service attributes and are less likely to switch airlines when a competing airline improves its offerings along these dimensions. Thus, airlines that charge for checked bags should consider improving the customer experience for their bag‐checking passengers, as they represent a potentially more valuable segment class to the airline.     

Modeling Precheck Parallel Screening Process in the Face of Strategic Applicants with Incomplete Information and Screening Errors

In security check systems, tighter screening processes increase the security level, but also cause more congestion, which could cause longer wait times. Having to deal with more congestion in lines could also cause issues for the screeners. The Transportation Security Administration (TSA) Precheck Program was introduced to create fast lanes in airports with the goal of expediting passengers who the TSA does not deem to be threats. In this lane, the TSA allows passengers to enjoy fewer restrictions in order to speed up the screening time. Motivated by the TSA Precheck Program, we study parallel queueing imperfect screening systems, where the potential normal and adversary participants/applicants decide whether to apply to the Precheck Program or not. The approved participants would be assigned to a faster screening channel based on a screening policy determined by an approver, who balances the concerns of safety of the passengers and congestion of the lines. There exist three types of optimal normal applicant's application strategy, which depend on whether the marginal payoff is negative or positive, or whether the marginal benefit equals the marginal cost. An adversary applicant would not apply when the screening policy is sufficiently large or the number of utilized benefits is sufficiently small. The basic model is extended by considering (1) applicants' parameters to follow different distributions and (2) applicants to have risk levels, where the approver determines the threshold value needed to qualify for Precheck. This article integrates game theory and queueing theory to study the optimal screening policy and provides some insights to imperfect parallel queueing screening systems.     

A Risk Analysis Framework for Cyber Security and Critical Infrastructure Protection of the U.S. Electric Power Grid

The purpose of this article is to introduce a risk analysis framework to enhance the cyber security of and to protect the critical infrastructure of the electric power grid of the United States. Building on the fundamental questions of risk assessment and management, this framework aims to advance the current risk analysis discussions pertaining to the electric power grid. Most of the previous risk-related studies on the electric power grid focus mainly on the recovery of the network from hurricanes and other natural disasters. In contrast, a disproportionately small number of studies explicitly investigate the vulnerability of the electric power grid to cyber-attack scenarios, and how they could be prevented or mitigated. Such a limited approach leaves the United States vulnerable to foreign and domestic threats (both state-sponsored and “lone wolf”) to infiltrate a network that lacks a comprehensive security environment or coordinated government response. By conducting a review of the literature and presenting a risk-based framework, this article underscores the need for a coordinated U.S. cyber security effort toward formulating strategies and responses conducive to protecting the nation against attacks on the electric power grid.     

Incremental and Average Cost‐Effectiveness Ratios: Will Physicians Make a Distinction?

Physicians are increasingly asked to use cost-effectiveness information when evaluating alternative health care interventions. Little is known about how the way such information is presented can influence medical decision making. We presented physicians with hypothetical screening scenarios with multiple options, varying the type of cost-effectiveness ratios provided as well as whether the scenarios described cancer screening settings that were familiar or unfamiliar. Half the scenarios used average cost-effectiveness ratios, as commonly reported, calculating benefits and costs relative to a no-screening option. The other half used the preferred incremental cost-effectiveness ratios, with each option's benefits and costs calculated relative to the next best alternative. Relative to average cost-effectiveness ratios, incremental cost-effectiveness information significantly reduced preference for the most expensive screening strategies in two of three unfamiliar scenarios. No such difference was found for familiar scenarios, for which physicians likely have established practice patterns. These results suggest that, in unfamiliar settings, average cost-effectiveness ratios as reported in many analyses reported in the literature can hide the often high price for achieving incremental health care goals, potentially causing physicians to choose interventions with poor cost effectiveness.     

A framework for supporting health capability-based planning: Identifying and structuring health capabilities

The COVID-19 pandemic has highlighted that health security systems must be redesigned, in a way that they are better prepared and ready to cope with multiple and diverse health threats, from predictable and well-known epidemics to unexpected and challenging pandemics. A powerful way of accomplishing this goal is to focus the planning on health capabilities. This focus may enhance the ability to respond to and recover from health threats and emergencies, while helping to identify the level of resources required to maintain and build up those capabilities that are critical in ensuring the preparedness of health security systems. However, current attempts for defining and organizing health capabilities have some important limitations. First, such attempts were not designed to consider diverse scenarios and multiple health threats. Second, they provide a limited representation of capabilities and lack a systemic perspective. Third, they struggle to identify capability and resource gaps. In this article, we thus propose a new framework for identifying and structuring health capabilities and support health capability planning. The suggested framework has three main potential benefits. First, the framework may help policymakers in planning under high levels of uncertainty, by considering multiple realistic and stressful scenarios. Second, it can provide risk analysts with a more comprehensive representation of health capabilities and their complex relationships. Third, it can support planners in identifying resource and capability gaps. We illustrate the use of the framework in practice considering an outbreak scenario caused by three different health threats (COVID-19, Ebola, and Influenza viruses).     

IT security planning under uncertainty for high-impact events

While many IT security incidents result in relatively minor operational disruptions or minimal recovery costs, occasionally high-impact security breaches can have catastrophic effects on the firm. Unfortunately, measuring security risk and planning for countermeasures or mitigation is a difficult task. Past research has suggested risk metrics which may be beneficial in understanding and planning for security incidents, but most of these metrics are aimed at identifying expected overall loss and do not directly address the identification of, or planning for, sparse events which might result in high-impact loss. The use of an upper percentile value or some other worst-case measure has been widely discussed in the literature as a means of stochastic optimization, but has not been applied to this decision domain. A key requirement in security planning for any threat scenario, expected or otherwise, is the ability to choose countermeasures optimally with regard to tradeoffs between countermeasure cost and remaining risk. Most of the planning models in the literature are qualitative, and none that we are aware of allow for the optimal determination of these tradeoffs. Therefore, we develop a model for optimally choosing countermeasures to block or mitigate security attacks in the presence of a given threat level profile. We utilize this model to examine scenarios under both expected threat levels and worst-case levels, and develop budget-dependent risk curves. These curves demonstrate the tradeoffs which occur if decision makers divert budgets away from planning for ordinary risk in an effort to mitigate the effects of potential high-impact outcomes.     

Who Should Pay for Interdependent Risk? Policy Implications for Security Interdependence Among Airports

We study interdependent risks in security, and shed light on the economic and policy implications of increasing security interdependence in presence of reactive attackers. We investigate the impact of potential public policy arrangements on the security of a group of interdependent organizations, namely, airports. Focusing on security expenditures and costs to society, as assessed by a social planner, to individual airports and to attackers, we first develop a game-theoretic framework, and derive explicit Nash equilibrium and socially optimal solutions in the airports network. We then conduct numerical experiments mirroring real-world cyber scenarios, to assess how a change in interdependence impact the airports' security expenditures, the overall expected costs to society, and the fairness of security financing. Our study provides insights on the economic and policy implications for the United States, Europe, and Asia.     

Assessing the Benefits and Costs of Homeland Security Research: A Risk-Informed Methodology with Applications for the U.S. Coast Guard

This article describes a methodology for risk-informed benefit–cost analyses of homeland security research products. The methodology is field-tested with 10 research products developed for the U.S. Coast Guard. Risk-informed benefit–cost analysis is a tool for risk management that integrates elements of risk analysis, decision analysis, and benefit–cost analysis. The cost analysis methodology includes a full-cost accounting of research projects, starting with initial fundamental research costs and extending to the costs of implementation of the research products and, where applicable, training, maintenance, and upgrade costs. The benefits analysis methodology is driven by changes in costs and risks leading to five alternative models: cost savings at the same level of security, increased security at the same cost, signal detection improvements, risk reduction by deterrence, and value of information. The U.S. Coast Guard staff selected 10 research projects to test and generalize the methodology. Examples include tools to improve the detection of explosives, reduce the costs of harbor patrols, and provide better predictions of hurricane wind speeds and floods. Benefits models and estimates varied by research project and many input parameters of the benefit estimates were highly uncertain, so risk analysis for sensitivity testing and simulation was important. Aggregating across the 10 research products, we found an overall median net present value of about $385 million, with a range from $54 million (5th percentile) to $877 million (95th percentile). Lessons learned are provided for future applications.     

A Preliminary Investigation of the Reinforcement Function of Signal Detections in Simulated Baggage Screening: Further Support for the Vigilance Reinforcement Hypothesis

The vigilance reinforcement hypothesis (VRH) asserts that errors in signal detection tasks are partially explained by operant reinforcement and extinction processes. VRH predictions were tested with a computerized baggage screening task. Our experiment evaluated the effects of signal schedule (extinction vs. variable interval 6 min) and visual field complexity (dial vs. baggage x-ray) on search behavior rates. There was a main effect for signal schedule [F (1, 20) = 14.0, p = .001, p_rep = 0.99], but no effects for field complexity or interaction. The VRH suggests that performance errors in visual screening work may be reduced through operant conditioning of search behaviors by intensive management of artificially planted signals.     

Risk-Based Decision Making for Terrorism Applications

This article describes the anti-terrorism risk-based decision aid (ARDA), a risk-based decision-making approach for prioritizing anti-terrorism measures. The ARDA model was developed as part of a larger effort to assess investments for protecting U.S. Navy assets at risk and determine whether the most effective anti-terrorism alternatives are being used to reduce the risk to the facilities and war-fighting assets. With ARDA and some support from subject matter experts, we examine thousands of scenarios composed of 15 attack modes against 160 facility types on two installations and hundreds of portfolios of 22 mitigation alternatives. ARDA uses multiattribute utility theory to solve some of the commonly identified challenges in security risk analysis. This article describes the process and documents lessons learned from applying the ARDA model for this application.     

Security Investment in Contagious Networks

Security of the systems is normally interdependent in such a way that security risks of one part affect other parts and threats spread through the vulnerable links in the network. So, the risks of the systems can be mitigated through investments in the security of interconnecting links. This article takes an innovative look at the problem of security investment of nodes on their vulnerable links in a given contagious network as a game‐theoretic model that can be applied to a variety of applications including information systems. In the proposed game model, each node computes its corresponding risk based on the value of its assets, vulnerabilities, and threats to determine the optimum level of security investments on its external links respecting its limited budget. Furthermore, direct and indirect nonlinear influences of a node's security investment on the risks of other nodes are considered. The existence and uniqueness of the game's Nash equilibrium in the proposed game are also proved. Further analysis of the model in a practical case revealed that taking advantage of the investment effects of other players, perfectly rational players (i.e., those who use the utility function of the proposed game model) make more cost‐effective decisions than selfish nonrational or semirational players.     

The Potential of Next-Generation Microbiological Diagnostics to Improve Bioterrorism Detection Speed

Emerging, rapid, multivalent, microbial diagnostic technologies can produce results in hours, as contrasted to the standard methods that require at least the better part of a week. Used in bioterrorism surveillance in medical settings, the new biodetectors could significantly reduce the time between a covert attack and its detection. By how much is determined by the intensity of sampling. If used to screen all patients reporting flu-like symptoms to their doctors, this basic level of "front-line" sampling would reduce life-threatening medical floundering and missteps and give responders 3-5 days of warning that they otherwise would not have had. Being miniaturized and amenable to mass production, these devices could reduce the cost of screening to a fraction of current costs and so it is tempting to imagine their use in more intensive bioterrorism screening programs aimed at the apparently healthy population, programs that could detect a covert attack even before the victims felt ill. This article examines the tradeoffs between surveillance effort and probability of detection for such programs. Dual-use deployment, where the biodetector provides some medically useful information in addition to bioterrorism surveillance, is discussed.     

Optimal investment in setup reduction for finite horizon periodic review inventory system under deterministic time varying demand

This paper examines the impact of setup reduction on a finite horizon, periodic review inventory system, under deterministic time varying demand. A total relevant cost function is developed for such systems. Using this, the impact of setup reduction is examined under various forms of setup reduction cost functions that have been suggested in the literature. The operating characteristics and optimization of the various scenarios are discussed. Our analysis shows that the effects of setup reduction in a periodic review system are similar to those in a reorder point system. Our results are likely to help practitioners who use similar periodic review systems towards decreasing total inventory related costs by investing in setup reduction.     

How does homeland security affect U.S. firms' international competitiveness?

This paper frames the issue of homeland security and its relationship to the international competitiveness of U.S. firms in general. This is largely a conceptual statement, identifying the areas of national security (homeland security) that are key to business, and exploring the management concerns of business to the new threats and opportunities that have arisen.We establish the point that homeland security is a purposeful, conscious, and rational response to terrorist events that is an emergent and evolving systems phenomenon. This systems approach is an especially useful way to look at the implications of homeland security in its relation to business. We then look specifically at the kinds of costs and risks that are generated for U.S. international business (exports, imports, incoming and outgoing investments) as a result of this phenomenon. Management strategies for dealing with these costs and risks are explored for U.S. firms.Our conclusion is to demonstrate the scope of analysis that is needed to understand and to managerially cope with the homeland security problem. We show the value of using theory from various disciplines for analyzing a multi-dimensional problem like this. And finally we are able to recommend some policy dimensions for both companies and the U.S. Government toward mitigating the negative impacts of the homeland security problem.     

Spatial Risk Assessment Across Large Landscapes with Varied Land Use: Lessons from a Conservation Assessment of Military Lands

Spatial decision-support tools are necessary for assessment and management of threats to biodiversity, which in turn is necessary for biodiversity conservation. In conjunction with the U.S. Geological Survey-Biological Resources Division's Species at Risk program, we developed a GIS-based spatial decision-support tool for relative risk assessments of threats to biodiversity on the U.S. Army's White Sands Missile Range and Fort Bliss (New Mexico and Texas) due to land uses associated with military missions of the two bases. The project tested use of spatial habitat models, land-use scenarios, and species-specific impacts to produce an assessment of relative risks for use in conservation planning on the 1.2 million-hectare study region. Our procedure allows spatially explicit analyses of risks to multiple species from multiple sources by identifying a set of hazards faced by all species of interest, identifying a set of feasible management alternatives, assigning scores to each species for each hazard, and mapping the distribution of these hazard scores across the region of interest for each combination of species/management alternatives. We illustrate the procedure with examples. We demonstrate that our risk-based approach to conservation planning can provide resource managers with a useful tool for spatial assessment of threats to species of concern.     

On‐Call Overtime for Service Workforce Scheduling when Demand Is Uncertain

This article builds on prior research to develop shift scheduling models that include on‐call overtime for service environments where demand is uncertain. The research is motivated by recent developments in nurse scheduling, such as laws prohibiting mandatory overtime and the popularity of self‐scheduling systems. For single‐period scenarios, models are developed, solution methods are described, and results are explored for a variety of environments. Results show that the use of on‐call overtime can reduce costs slightly, with the amount of savings dependent on characteristics of the scheduling environment. The factor that most significantly affects cost savings is the cost of outside agency workers relative to overtime workers. In addition to lowering costs, on‐call overtime greatly reduces reliance on outside agency workers, which can have important practical implications in terms of quality of service and workforce morale. Results based on single‐period models motivate multiperiod formulations for single‐ and multidepartment scenarios, and solution methods are outlined for those cases. The possibility of using multiperiod models within a rolling horizon framework with forecast updating is discussed. This goes along with an extension of the traditional workforce management hierarchy that separates overtime and regular‐time scheduling, as seen in practice with self‐scheduling and shift‐bidding systems.