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Behavioural Detection and Other Technologies in Aviation Security

Table of Contents
  1. Introduction
  2. Behavioral Detection and Other Technologies
  3. Efficacy of Current International Conventions and Legislations
  4. Conclusion
  5. Reference List


Many industries today face the challenge of detecting and preventing terrorism. The challenge is not significantly different for the commercial air travel sector. However, it can be acknowledged that the aviation industry remains a high-profile target for terrorist organizations. Airport security and screening have, in response to increased threats, advanced to include technological innovations and behavioral detection mechanisms. These two approaches work together to improve the detection of suspicious activity and persons and help avert terrorism. This paper presents a critical analysis of aviation security paying attention to behavioral detection and other technological advancements. An examination of these developments leading to greater airport security will be presented considering the evolving nature of terrorism activities. Lastly, the critical analysis will explore the efficacy of current international conventions and other legislations in providing deterrence against modern aviation security threats.

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Behavioral Detection and Other Technologies

The events of September 11th, 2001 have resulted in significant developments in airport security and screening. Many studies of aviation safety examine the trade-offs for safety improvements. According to Sakano, Obeng, and Fuller (2016), the results have included longer waiting lines at the screening points. Additionally, passengers have expressed unpleasant experiences and other inconveniences which could potentially reduce demand for air travel. These inconveniences are a compromise the industry is willing to make to avoid serious breaches of security.

Behavioral detection has been used alongside other safety technologies to alleviate potential threats. Trained personnel can assess human actions and determine when malice is intended. The primary benefit of this approach is that, even though not conclusively, it can help determine further screening actions to make sure the risk is present or absent. The screening technologies are the more prominent ones in an examination of the advances in aviation security. An example given by Sakano, Obeng, and Fuller (2016) involves an online risk-based process where the customers are pre-qualified for different levels of screening. Behavioral detection, it can be argued, can also work with the security officers directing the passengers to different screening points based on their assessment of the level of risk involved.

Behavioral and cognitive sciences are the foundation of behavioral detection. Scientists in these fields are, therefore, poised for the security community in the identification of reliable behavioral indicators. These can then be used in the empirical examination of the threat performance (Sweet, Meisner, and Atkinson, 2017). Today, several studies illustrate how behavioral, cognitive sciences, and threat detection programs, can help law enforcers distinguish concealed objects which resemble threat devices both at a single target level and in the crowds. The most important idea behind behavioral detection and related programs is that threat markers are isolated through passive identification. However, further research may need to be undertaken to determine the success level of the officers using their behavioral judgment. Sweet, Meisner, and Atkinson (2017) emphasize that it is unfortunate that only a few studies have systematically assessed the nonverbal indicators of threat and concealment which is the primary screening method used by security personnel. Therefore, behavioral detection remains a vague area of scholarly exploration.

It is important to highlight that the behavioral approaches can be critiqued for various weaknesses, especially when subjected to scientific examination. Behavioral detection can be described as a collection of approaches based on social psychology (Maguire and Fussey, 2016). The ecological validity of these tactics is often questioned due to the use of small sample sizes. Additionally, the ontological and epistemological concerns further dispute many of the scientifically approved techniques for distinguishing suspicious behavior. For instance, people often assume a binary moral world consisting of good and evil, where all wrongdoers are supposed to be aware of their supposed turpitude. Additionally, there is also the self-awareness of the deceptive nature of certain behaviors. Therefore, the lines between illegal and legal are hard to determine among the transgressors.

Even with the weaknesses mentioned above, behavioral detection can still be appreciated for its contribution to improving aviation security. The main goal of behavioral detection is to identify high-risk individuals and to subject them to further scrutiny. The main advantages, therefore, include that the approaches are unobtrusive and are applied in real-time (Dynon, 2018). Additionally, they help the security officers to focus on the person rather than the weapon which allows behavioral detection to be deployed in various settings configurations. They are also free of large equipment footprints since only the intelligence of the personnel is needed. It is easier for security officers to identify suspicious behaviors because offenders are known to have fear of being discovered or anxiety and stress often preceding a terrorist attack. A checklist developed in the United States by the Transport Security Authority (TSA) highlights behaviors such as excessive yawning, throat clearing, and complaints regarding the screening process. Other behaviors include late arrival for a flight, gazing down, pale faces, visible disguise, and the pretense not to understand questions.

Without the statistical and empirical evidence, however, the deficiencies of behavioral detection will dominate the current discussion. Firstly, the approach has been labeled unscientific and described as having less or the same effectiveness as chance (Dynon, 2018). According to Maguire and Fussey (2016), behavioral detection hardly achieves a 50% accuracy in identifying deception. Deception, therefore, becomes the greatest point of weakness in these approaches. Sweet, Meisner, and Atkinson (2017) find that there is inadequate research in lie detection to show the success of identifying reliable nonverbal or passive indicators of deceptive responses. Additionally, there is no evidence of officers’ training on deception detection via nonverbal channels. The researchers also support that nonverbal indicators have the same impact as chance.

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Behavioral detection, however, is often not implemented on its own, especially in the current era of the digital revolution. There currently exist some algorithms used for behavioral detection that could work better than human judgment. Even so, there would need to be empirical evidence to suggest that these new technologies have significantly improved aviation security. The technological developments have been fuelled by advances in computational power and data. The application of artificial intelligence and robotics has led to enormous enhancements in capabilities which have provided security-sensitive environments comprising lie detection and non-invasive threat identification. Additionally, they help in the prediction of criminal activity and tracing diseases and illicit intentions (Blum, 2020). With these technologies, it can be argued that behavioral detection becomes easier and more effective in providing aviators with the ultimate security.

The use of innovative technologies in aviation security systems has several advantages. Apart from improved success, the airlines can also benefit from speedier screening processes and avoid the inconveniences and unpleasant passenger experiences such as long wait times. These benefits have been highlighted by Sakano, Obeng, and Fuller (2016) who state that the TSA is already deploying these technologies to increase passenger satisfaction and reduce wait times. New screening equipment is faster and more effective and involves the use of a computer-assisted passenger prescreening system (CAPPS). This approach works by categorizing air travelers into two risk classes. Further development in this technology, labeled CAPPS II, comprises three classes, including one containing those individuals who are not permitted to fly. In the United States, the TSA also requires airlines flying into the country to submit to the immigration department the list of passengers 30 minutes before departing. Such an arrangement allows the authorities more time to pre-screen all people going into the US before their arrival. The low or no-risk individuals can be allowed into the nation while those classified as high-risk can be subjected to further screening upon arrival.

With behavior detection technologies, the most important question asked regards the type of information processed. To emphasize the concept, the basic idea in behavioral detection is that the internal emotional processes tend to produce detectable physical changes which can be captured using sensors. These indicators can then be processed and understood, as well as used to create alerts depending on the algorithm used (Blum, 2020). The technologies offer a multi-modal approach in which every factor can be taken into account. Blum (2020) expresses that in aviation, behavioral detection depends on both nonverbal and verbal elements and is based on the premise that criminals tend to show signals which differ from normal behavior. In addition to the TSA checklist mentioned earlier on, Blum (2020) adds other aspects such as biometrics, facial expressions, perspiration, temperature, and lack of eye contact and classifies them under micro factors. At the macro level, hiding faces and entire bodies or even attempting to conduct surveillance are key indicators of criminal intent.

The combination of behavioral detection and technological tools can have led to the emergence of the concept of tech-science as applied in counter-terrorism. Researchers such as Maguire and Fussey (2016) describe counter-terrorism techno-science as the contemporary response to the events of September 11th, 2001, and the shoe-bomber attack. Techno-science provided counter-terrorism apparatus which deviate from the traditional threat detection and prevention. The United States remains the best example of how techno-science is deployed with projects such as the Automated Virtual Agent for Truth Assessments in Real-time (AVATAR). AVATAR is a behavioral-psychological examination combined with facial recognition systems housed in an ATM-sized machine. Other developments by the US Department of Homeland Security (DHS) include Future Attribute Screening Technology (FAST), which is a mobile security infrastructure that individuals pass through in high-risk areas such as mega-events and airports (Maguire and Fussey, 2016). Regardless of the functioning of these techno-science apparatus, the basic idea is that persons with criminal intent can be identified using the signals they display.

It can be argued, therefore, that behavioral detection deployed on its own cannot assure any significant improvements in aviation security. It is indeed the new technologies that make behavioral detection a feasible approach. The new equipment, as evidenced by the deployments by the TSA, makes it possible to conclusively determine those behaviors which point toward a potential terrorist. Without the help of the digital apparatus, human judgment becomes less effective than chance as insisted by researchers such as Maguire and Fussey (2016). It has been expressed earlier that detecting deception is the one area in which behavioral detection fails almost entirely. According to Dillon, Burns, and John (2018), computing detection probabilities have eliminated the need to rely on expert assessments in securing critical infrastructure such as nuclear power plants. In this discussion, airports are considered key infrastructure with global importance and, therefore, the computing systems should replace human judgment in behavioral detection.

The current research shows that behavioral detection and counter-terrorism techno-science has the potential to prevent security breaches and terror attacks. However, the inadequate scholarly work on behavioral detection and the fact that the new technologies are still novel means that the extent to which these apparatuses are effective is yet to be fully understood. The TSA has developed several projects but their success is either not yet documented or availed to the general public. Other innovations such as fuzzy knowledge base and equipment-specific methods discussed by Gladkikh et al. (2019) are merely propositions and theoretical frameworks without hard evidence. The concepts, however, are feasible from a theoretical point of view and the fact that TSA invests heavily in them means there is either the potential or the organization is recording great success in the new methodologies.

Efficacy of Current International Conventions and Legislations

International conventions and legislations are often pursued by global entities such as the United Nations (UN), European Union (EU), and major industry-specific organizations such as International Air Transport Association (IATA) representing the aviation industry. These bodies have developed multiple policies on anti-terrorism, often in cooperation with major world governments. Aviation is a global industry meaning terrorism in one airline or airport could affect more than one country. Therefore, the examination of the efficacy of the current international conventions and legislations in averting terrorist threats will focus majorly on these global aviation institutions.

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It is important to emphasize that international aviation organizations often work jointly with others with similar interests. For example, a press release by International Air Transport Association (2020) indicated that IATA seeks to cooperate with the United Nations Office of Counter-Terrorism (UNOCT) to inhibit terrorist travel. The memorandum of understanding between these two bodies was signed to initiate a flagship program that uses advanced passenger information (API) and passenger name records (PNR) among other traveler data as per the Security Council resolutions such as 2178 of 2014, 2396 of 2017, and 2482 of 2019 (International Air Transport Association, 2020). These resolutions provide conventions agreed to by international governments as globally-accepted counter-terrorism frameworks and conventions.

The efficacy of the international conventions can be examined by looking into how each convention is framed and implemented, as well as any empirical data showing success levels. The conventions have been developed since 1963 and over 16 of them have been initiated and approved under the auspices of the UN (Einsiedel, 2016). One of the most current conventions is the 2005 Convention for the Suppression of Acts of Nuclear Terrorism. Their framing indicates that the UN and its members agree that all acts of terrorism should be suppressed. However, they fail to offer a clear implementation plan or guideline meaning they remain relatively ineffective. Therefore, each country is left to deal with the internal terrorism problems using its own counter-terrorism infrastructure, policies, and methodologies. According to Einsiedel (2016), efforts to develop a comprehensive and all-encompassing counter-terrorism convention have dodged the UN. The explanation for this observation is that the world nations cannot agree on how to define terrorism and on whether the definition should include the term “state terrorism” denoting the terror acts conducted by armed forces on non-combatants.

The UN Charter is the basis for all international laws, including laws about state terrorism. However, some authors feel that terrorism can also be a tool for the dispossessed meaning that countries mostly have to deal with non-state actors (NSAs) (Trapp, 2016). The international resolutions, therefore, provide the governments with a cooperative framework for suppressing terrorism which involves the formulation of criminal law enforcement agreements which seek to secure individual responsibility (Trapp, 2016). In civil aviation, conventions such as the 1971 Convention for the Suppression of Unlawful Acts against the Safety of Civil Aviation, which came into effect in 1973, allow the aviation authorities to undertake measures to prevent crime and related acts. This Act was passed in Montreal and was agreed upon by 188 member states. The main purpose was to help address acts of unlawful interference against civil aviation which were not addressed in the Hague Convention. It is important to acknowledge that the Montreal convention was in many ways similar to the Hague convention and the only need for a separate one was due to fears regarding the possibility of the conclusion of the Hague Convention.

Other agreements include the subsequent Protocol on the Suppression of Unlawful Act at Airports Serving International Aviation. It outlines how the 1971 treaty is to be implemented (Nesi, 2016). These treaties generalize all unlawful actions and it can be argued that acts of terror are included in the framing of the convention. One of the legislations which best addressed terrorism was the European Convention on the Suppression of Terrorism which was passed in 1977. It made significant alterations to the extradition exercises between the member states and provided for the exercise of jurisdiction where extradition does not occur. In other words, it eliminated or eased the barriers to extradition by allowing those specific offenses cannot be classified as political and could, therefore, be subject to extradition. The provisions of this international legislation, it should be noted, include those offenses within the scope of both the Montreal and Hague conventions in addition to several others, such as liberty of internationally protected persons, the attack against life, and physical integrity.

These conventions have not necessarily be specific to the aviation industry and those focusing on the sector deal with general unlawful behavior. There has not been any empirical examination of their efficacy and any judgment will majorly lie within the extent of the application by the individual countries. Scholars and experts explain that the differences in ideologies cause different applications and implementation, as well as interpretations of certain aspects. One major issue observed by Sinnar (2019) is that countries find it hard to tell between acts of terrorism and those of violence, and many of them cannot decide whether to treat these two behaviors differently or as the same thing. Most importantly, policymakers in certain countries such as the United States have been shown to display bias and stereotypes either in the application of the conventions or in developing counter-terrorism policies. For example, counter-terrorism in the US has often led to the monitoring of Muslim communities with law enforcers intercepting phone conversations and obtaining secret internet records among other things. Without better guidelines and protocols, therefore, the international conventions remain largely ineffective in preventing breaches and attacks.

In essence, it is hard to tell how much of the international conventions and other legislations are implemented by individual countries. As mentioned earlier on, the activities and initiatives by international aviation agencies such as IATA and UNOCT remain the most visible applications of international counter-terrorism resolutions. However, it is important to acknowledge that the composition of treaties such as the Hague and Montreal conventions, or even the European convention on the suppression of terrorism, is plausible and commendable. This is because it provides a general agreement among states that all offenses are to be suppressed effectively to allow for a smooth operation of the aviation industry. Therefore, unless more research is done on the subject, it will remain difficult to appreciate the efficacy of the international conventions and other legislations in averting terrorism in aviation.


This paper discussed why the aviation industry is a high-profile target for terrorist organizations. For this reason, the aviation authorities and the national governments have pursued multiple mechanisms and strategies to secure critical infrastructures such as airports and airlines. Behavioral detection has become a widely used approach where security personnel identify suspicious activity and prevent potential terrorist acts. Without empirical evidence, this critical analysis paper finds it hard to explain its efficacy. However, the emergence of new technologies has given behavioral detection a new outlook and greater success potential. Also discussed is the extent to which conventions and legislations are effective in preventing terrorism. The conclusion reached is that these offer a framework through which local efforts in crime and terrorism prevention can be implemented.

Reference List

Blum, S. (2020) ‘Behavior detection technology: screening on the go’, Aviation Security International, 26(2), pp. 34-37.

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Dillon, R., Burns, W. and John, R. (2018) ‘Insights for critical alarm-based warning systems from a risk analysis of commercial aviation passenger screening’, Decision Analysis, 15(3), pp. 154-173.

Dynon, N. (2018) ‘Behavior detection at the border: dark art or science?’, Defsec, Web.

Einsiedel, S. (2016) Assessing the UN’s efforts to counter terrorism. New York: United Nations University Centre for Policy Research.

Gladkikh, A. et al. (2019) ‘Fuzzy knowledge base synthesis of the experience level classification of aviation security screeners using subtractive clustering and anfis-training’ International Journal of Civil Engineering and Technology, 10(3), p. 2316–2328.

International Air Transport Association (2020) IATA and UNOCT to cooperate on countering terrorist travel. Web.

Maguire, M. and Fussey, P. (2016) ‘Sensing evil counterterrorism, techno-science, and the cultural reproduction of security’, Focaal—Journal of Global and Historical Anthropology, 75, pp. 31-44.

Nesi, G. (2016) International cooperation in counter-terrorism: the United Nations and regional organizations in the fight against terrorism. London: Routledge.

Sakano, R., Obeng, K. and Fuller, K. (2016) ‘Airport security and screening satisfaction: a case study of U.S’, Journal of Air Transport Management, 55, pp. 129-138.

Sinnar, S. (2019) ‘Separate and unequal: the law of “domestic” and “international” terrorism’, Michigan Law Review, 117(7), pp. 1333-1404.

Sweet, D., Meisner, C. and Atkinson, D. (2017) ‘Assessing law enforcement performance in behavior-based threat detection tasks involving a concealed weapon or device’, Law and Human Behavior, 41(5), pp. 411-421.

Trapp, K. (2016) ‘The potentialities and limitations of reactive law making: a case study in international terrorism suppression’, UNSW Law Journal, 39(3), pp. 1191-1218.

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