Global Terrorism Database Research Articles

A Forensic Investigation of Terrorism in Nigeria: An Apriori Algorithm Approach

Investigations towards studying terrorist activities have recently attracted a great amount of research interest. In this paper, we investigate the use of the Apriori algorithm on the Global Terrorism Database (GTD) for forensic investigation purposes. Recently, the Apriori algorithm, which could be considered a forensic tool, has been used to study terrorist activities and patterns across the world. As such, our motivation is to utilise the Apriori algorithm approach on the GTD to study terrorist activities and the areas/states in Nigeria with high frequencies of terrorist activities. We observe that the most preferred method of terrorist attacks in Nigeria is through armed assault. Again, our experiment shows that attacks in Nigeria are mostly successful. Also, we observe from our investigations that most terrorists in Nigeria are not suicidal. The main application of this work can be used by forensic experts to assist law enforcement agencies in decision making when handling terrorist attacks in Nigeria.

Knowledge Extraction on the Nexus Between Terrorism Criteria and Attacks on Private Citizens and Property

This study extracted knowledge on the association between terrorism inclusion criteria and one of the terrorism target/victim types known as “private citizens and property.” Three criteria determine what constitutes a terror attack: Criterion 1: the action is done with intention to attain a political, economic, religious, or social goal; Criterion 2: the action is done with the intention to coerce, intimidate or publicize to larger audience(s); Criterion 3: the action is outside international humanitarian law. Literally, all terror incidents satify Criterion 3. As for Criteria 1 and 2, the odds ratio was deployed on the global terrorism database, consisting of 170,350 records of terrorist attack incidents, to evaluate the nexus between each of these criteria and terror attacks on private citizens and property. The results showed that any terror attack on private citizens and property is 2.2 times more likely to have been perpetrated by a terror group in order to achieve Criterion 2 than to achieve Criterion 1. The implications of the outcome in counterterrorism are discussed.

Profiles of Violent Radicalization: Challenging Key Premises on Root Causes Leading to Terrorism

This study challenges the key premises of the current debate on radicalization's root causes, leading to predatory mass-violence. The current debate's three key premises are that there are only two radicalization templates: top-down (fishermen) or bottom-up (swarm). Additionally, these templates of radicalization are more useful to understand terrorism than regional or violent ideology. Finally, there is only one primary dynamic, a trade-off of prevalence, between the two templates. These premises arose from case analysis of a sample set of terrorist incidents. We used the University of Maryland START Global Terrorism Database (GTD) to create a total population sample of 4,646 terrorist incidents in Western Europe (WEUR) and the United States (US) from 1995-2018. We classified them into seven different violent ideologies: Anti-Government, Crime & Hate Crimes, Left-Wing, Right-Wing, Separatism, Takfiri, and Unknown and then categorized them for indications of swarm or fishermen suspected radicalization. From this data, we assembled a catalog of profiles, which we then subjected to statistical testing using a total population sample rather. We found that regional and violent ideologies had significant differences. Even though radicalization templates in aggregate had some differences when tested to control for the region and violent ideology, those statistical differences disappeared—suggesting that region and violent ideology, as system-level contingencies, have more influence than the radicalization template. We also found evidence suggesting a third kind of radicalization template, that of copycats or wannabe. Furthermore, we found evidence that the interaction between the three templates varied from the presumption of a trade-off of prevalence. We suggest that radicalization templates are manifestations of contingencies within a general system of radicalization. The system structure and contingencies are the root causes of radicalization, not the manifestations that emerge from it. This evidence establishes a starting point for a new path of systems sciences research to bear on the important questions of predatory mass-violence and radicalization, which leads to it.

Chemical Warfare Agents in Terrorist Attacks: An Interregional Comparison, Tactical Response Implications, and the Emergence of Counterterrorism Medicine.

Terrorist attacks are growing in frequency, increasing concerns about chemical warfare agents (CWAs). Asphyxiants (e.g., cyanide), opioids (e.g., carfentanyl), and nerve agents (e.g., ricin) represent some of the most lethal CWAs. Our aim was to define the epidemiology of CWA use in terrorism and detail specific agents used to allow for the development of training programs for responders. The open-source Global Terrorism Database (GTD) was searched for all chemical attacks from January 1, 1970, to December 31, 2018. Attacks were included when they fulfilled the terrorism-related criteria as set forth in the internal Codebook of the GTD. Events meeting only partial criteria were excluded. A total of 347 terrorism-related chemical events occurred, with 921 fatalities and 13,361 nonfatal injuries (NFIs) recorded during the study period. South Asia accounted for nearly 30% (101 of 347) of CWA attacks, with 73 of 101 occurring in Afghanistan. The Taliban was implicated in 40 of 101 events utilizing a mixture of agents, including unknown chemical gases (likely representing trials of a number of different chemicals), contamination of water sources with pesticides, and the use of corrosive acid. The largest death toll from a single event (200 fatalities) was attributed to a cult-related mass murder in the Kasese District of Uganda in March 2000. East Asia sustained the highest NFI toll of 7,007 as a result of chemical attacks; 5,500 were attributed to the Tokyo subway sarin gas attack of 1995 by Aum Shinrikyo. The use of CWAs remains a concern given the rising rate of terrorist events. First responders and healthcare workers should be aware of potential chemical hazards that have been used regionally and globally and should train and prepare to respond appropriately.

Terrorism in armed conflict: new data attributing terrorism to rebel organizations

The Terrorism in Armed Conflict project integrates the Uppsala Conflict Data Project sample of rebel organizations with START’s Global Terrorism Database, covering 409 organizations for 1970–2013. For many Global Terrorism Database incidents, perpetrator information is missing, or ambiguous. Because the accuracy of perpetrator information likely varies systematically, simply dropping these incidents from analyses may bias results. Terrorism in Armed Conflict provides possible attribution to specific rebel groups with coding for uncertainty, enabling researchers to (1) address “description bias” in media-based terrorism data, (2) model uncertainty regarding perpetrator attribution and (3) vary the way terrorism is counted. The Terrorism in Armed Conflict dataset further provides a measure of deliberately indiscriminate terrorism that allows for more nuanced testing of arguments about the strategic logic of terrorism.

Ethnic Economic Inequality and Fatalities From Terrorism.

Few studies have explored the influence of horizontal (i.e., among group) inequalities on terrorism, yet it seems plausible that these inequalities may be relevant. Employing data from the Global Terrorism Database and Ethnologue, this article examines the effect of ethnic economic inequality on domestic terrorism for 130 countries over the period 2001 to 2018. We present evidence that higher degrees of ethnic inequality lead to higher numbers of terrorist attacks as well as a higher number of people killed or injured. This positive association between ethnic inequality and terrorism is robust to alternative measures of ethnic inequality, omission of influential countries and regions, the inclusion and exclusion of controls, and alternative estimation strategies. In contrast, countries with high degree of political freedom and high governance quality tend to suffer less from terrorism. Promoting economic equality among ethnic groups, therefore, has the potential to reduce the risk of domestic terrorism. We propose that a critical step towards promoting this equality is to enhance social inclusion. The benefits of increasing social inclusion extend beyond simply reducing the incidence of terrorism and inter-racial violence; creating a socially inclusive society is a social justice imperative and the responsibility of policymakers, social institutions, civil society, and the private sector. It is also consistent with the notion of inclusive economic growth, as championed by organizations such as the OECD and the United Nations Development Program.

Domestic Terrorism, Investment and Economic Growth: Evidence from Developing Countries

The main objective of the study is to empirically examine the relationship between domestic terrorism, investment and economic growth. The study finds the implication of domestic terrorism on investment and growth among 26 Muslim and 14 Christian developing countries. Data regarding the incidence of terrorism are obtained from Global Terrorism Database (2015). While, economic data are obtained from World Development Indicators (WDI, 2015). The data on external and internal conflict have been extracted from Global Conflict Risk Index (GCRI, 2015) for the time period 1990-2015. Ordinary least square (OLS), feasible generalized least squares (FGLS) and system generalized method of moment (SGMM) approaches were applied to ensure robust results with different specification of models by using dummy variable. The value of Dummy variable is 1, if country is Muslim otherwise 0. For all specifications, it is confirmed that increase in domestic terrorism will decrease the level of investment directly, but the percentage decrease in investment due to terrorism is high among Muslim as compared to Christian developing economies. The results indicate the public policy efforts to mitigate the loss of private investment which can be done initially by public investments to ensure public safety. Keywords: OLS, FGLS, SGMM, Domestic Terrorism, Muslim and Christian Developing Countries.

Factors of Mass Casualty Terrorism

Several changes in terrorist tactics have occurred recently. First, terrorist attack targets have changed from hard to soft targets. Second, terrorists are actively using low-tech terrorism methods that they can choose easily. Finally, terrorist attacks are evolving into complex and simultaneous terrorist events. This study endeavored to determine whether these changes affected the number of casualties from terrorist events that occurred in developed countries. Based on the rational choice theory and situational crime prevention, the variables were constructed based on two dimensions: “target factors in terrorism” and “terrorist attack factors in terrorism.” To achieve the purpose of this study, a negative binomial regression analysis was performed based on data from the Global Terrorism Database. Consequently, variables such as “exposure,” “protection capability,” “attack patterns (vehicle),” and “suicide terrorism” were verified for their statistically significant influence on “mass casualty terrorism (MCT).” This study suggests that it is necessary to design a preventive environment and arrange for personnel at each site that is vulnerable to terrorism to prevent MCT events from occurring inside facilities.

Terrorists Use of Ambulances for Terror Attacks: A Review.

Using an ambulance as an attack modality offers many advantages to a terrorist organization. Ambulances can carry more explosives than most vehicles and can often bypass security. Yet, studies examining how terrorist organizations have incorporated ambulances into their attacks are lacking. This article seeks to identify and analyze known instances in which an ambulance has been used in a terrorist attack. The Global Terrorism Database (GTD) was searched for terrorist events that involved the use of an ambulance from the years 1970-2018. Variables of event time, location, and loss of life were analyzed. Twenty instances where an ambulance had been used in a terrorist attack were identified from the GTD. Fifteen of the attacks occurred in the Middle East, while the remaining five occurred in Southeast Asia. All attacks except one had occurred after 2001, and 13 had occurred within the past decade. Most attacks (12/20) resulted in up to three people killed, while six attacks had 10-20 casualties. The deadliest attack occurred in Kabul, Afghanistan in 2018 and caused over 100 casualties. One event did not have casualty information in the GTD. In all cases, ambulances were used as vehicle-borne improvised explosive devices (VBIED) by terrorist organizations. This study shows that terrorists are increasingly acquiring and utilizing ambulances in their attacks, often with deadly consequences. Security and public health experts must be aware of this hazard and work to deny terrorists access to these vehicles.

Who Said We Were Terrorists? Issues with Terrorism Data and Inclusion Criteria

This article examines the reliability of “terrorism” classifications within the Global Terrorism Database (GTD) by looking at its inclusion criteria as well as filtering mechanisms for ensuring quality case inclusion. Using several descriptive analyses, this article examines how various measures within the GTD affect researcher’s ability to adequately analyze various patterns or trends of offending. The underlying limitations of the data, namely data inclusion, the defining of terrorism, and inconsistency in labeling events are examined. It is concluded from the analyses that what is being defined as terrorism matters downstream when examining the data, given that it is used to make inferences about groups, movements, or the efficacy of governmental policy. Since scholars often lack a proper “error” framework for assessing the quality of big data derived from open sources on terrorism, it makes it difficult for scholars to assess the quality of the data itself. As a result, researchers are encouraged to include an error framework within the GTD for academics to assess the quality of the data they are plugging into their models. Results, limitations, and recommendations are further expanded upon within.

TerrorClassify: An Algorithm for Terror Groups Placement Into Hierarchical Categories of Casualties and Consequences

This study developed an algorithm, TerrorClassify, which places terror organizations into hierarchical categories of casualties and consequences. A previous study proposed a method of categorizing terrorists into four classes based on the extent of havoc caused by individual terror groups. The classes include low-casualty, medium-consequence terror groups; medium-casualty, high-consequence terror groups; high-casualty, low-consequence terror groups; and higher-casualty, low-consequence terror groups. In this research, an algorithm was designed to show the procedures to be followed in placing terror groups into the four classes using the records in the global terrorism database. The algorithm can be implemented with any programming language.

Modeling multi-target defender-attacker games with quantal response attack strategies

Due to the growing interest in incorporating behavioral models within the defender-attacker game literature, the perfect rationality assumption of adversaries has been relaxed in many recent works. This paper studies four multi-target defensive resource allocation in defender-attacker games by using a quantal response model, in which the attacker might be bounded rational. We compare the results from the proposed models with the traditional game theoretic model where the attacker behaves rationally. Moreover, we studied the impacts of the attacker’s rationality level on the defender’s optimal defense strategies. Real data from the Urban Areas Security Initiative (UASI) and the Global Terrorism Database (GTD) are employed to estimate the rationality parameter as well as numerically illustrate the model. The results show that: (a) in the quantal response model, the defender’s expected loss at equilibrium increases with the attacker’s rationality parameter and the expected loss approach the results from the game theoretic model; (b) when the attacker’s rationality parameter in the quantal response model approaches infinity, both the equilibrium defensive allocation and expected loss approach to the results from the game theoretic model; (c) when the attacker uses quantal response while the defender falsely believes that the attacker uses game theoretic response, the expected loss will be similar to the model where both players utilize game theoretic response, but higher than the expected loss from the model where both players use quantal response; (d) when the attacker uses game theoretic response while the defender falsely believes that the attacker uses quantal response, the expected equilibrium loss will be higher than the ones from the other three scenarios; and (e) the quantal response model gives a closer resource allocation to the real allocation than the game theoretic model does. This paper provides some novel insights to defensive resource allocation when considering that the attacker is bounded rationality.

Terrorism and the Varieties of Civil Liberties

Abstract How do government protections, and violations, of its citizens’ civil liberties influence the country's exposure to terrorism? Existing research remains divided. We contribute clarity to these debates by examining the distinct effects of specific types of civil liberties: physical integrity (e.g., freedom from extra-judicial torture and killing), political liberties (e.g., freedom of expression and assembly), and private liberties (e.g., freedom of thought and religion and property rights). We distinguish these civil liberties dimensions from the role of institutions for political selection (e.g., elections) and horizontal accountability (e.g., checks and balances, executive constraints). We argue physical integrity rights decrease terrorism, by reducing grievances against and increasing trust in the state, while political liberties increase terrorism, by both incentivizing violence among those with extremist goals and protecting their ability to organize. Empirically, we measure a country's exposure to terrorism using the Global Terrorism Database. We isolate the effects of government actions on these civil liberties dimensions from each other, and from the effects of the state's political institutions, by leveraging the Varieties of Democracy data. Our sample covers 177 states from 1970 to 2018. We find evidence consistent with our hypotheses regarding the effects of the distinct component dimensions of civil liberties.

Five Decades of Global Chemical Terror Attacks: Data Analysis to Inform Training and Preparedness.

Chemical weapons attacks during the recent conflict in Syria and Iraq highlight the need to better understand the changing epidemiology of chemical weapons use, especially among non-state actors. Public health professionals and policy-makers require this data to prioritize funding, training, chemical weapons preparedness, disaster response, and recovery. The purpose of this investigation is to provide descriptive data that can be used by policy-makers and public safety officials to better prepare for these potential attacks. A five-decade descriptive retrospective review of The Global Terrorism Database, maintained by the National Consortium for the Study of Terrorism and Responses to Terrorism, was conducted to understand trends in chemical agents, targets, and routes of exposure. We reviewed and analyzed data specific to these documented chemical attacks between 1970 and 2017. 383 terror attacks involved chemical weapons over the study period. A specific agent was named in 154 incidents, while 124 incidents could be classified into traditional chemical weapons categories (eg, vesicant, choking agents). A route of exposure was identified in 242 attacks, with the most common routes of exposure being dermal-mucosal and inhalational. Caustic agents were used in the highest portion of attacks (25%) where the route of exposure was known. Explosive devices were used in 21% of attacks to deliver these chemical agents. Of particular note, private citizens and educational facilities were targeted in 25% and 12% of attacks, respectively. The average number of attacks increased from 6 per year between 1970 and 2011 to 24.9 per year between 2011 and 2017 (coinciding with the start of the Syria conflict). The most commonly utilized chemicals were chlorine (26.0%), tear gas (20.8%), and cyanide (15.6%). Blood agent incidents declined from 32.6% before the September 11, 2001 attacks to 13.6% after 2001, while nerve agent attacks fell from 9.3% to 1.2%. In contrast, choking (namely chlorine) and vesicant (mustard) agent use increased from 7% to 48.1% and from 2.3% to 6.2% of attacks, respectively. Chemical weapon use in global terrorism remains an increasingly common occurrence that requires better characterization. The average number of chemical terrorist attacks per year is increasing, with a large proportion resulting from the conflicts in Iraq and Syria. Choking (chlorine) and vesicant (mustard) agents have become the predominant chemical terror agent since 2001, with a decreased incidence of blood (cyanogenic) and nerve (sarin) agents. Future preparedness initiatives should focus on vulnerable targets such as private citizens and educational institutions. Improving blast injury response is essential, along with prioritizing disaster training focused on choking agents, vesicants, and caustics.

<em>MACHINE LEARNING</em> PER CARATTERIZZARE GLI ATTACCHI TERRORISTICI

For security departments understanding the dynamics of terrorist events finding significant and recurrent patterns can have an important impact in the counter-terrorism strategy development. Machine learning techniques coupled with domain knowledge are useful to understand terrorist behaviours with high accuracy, thus helping policy makers for time-sensitive understanding of terrorist activity, which can enable precautions to avoid against future attacks. In this paper different computational techniques, able to derive relationships among terrorist attacks and detect terrorist behaviours, are used on the Global Terrorism Database. The analysis proposed in this paper could help security and government departments to prevent terrorist attacks and to reduce financial, human and political losses. Furthermore, this information can be useful for law enforcement agencies to propose reactive strategies.

An XGBoost-based casualty prediction method for terrorist attacks

Terrorist attacks have been becoming one of the severe threats to national public security and world peace. Ascertaining whether the behaviors of terrorist attacks will threaten the lives of innocent people is vital in dealing with terrorist attacks, which has a profound impact on the resource optimization configuration. For this purpose, we propose an XGBoost-based casualty prediction algorithm, namely RP-GA-XGBoost, to predict whether terrorist attacks will cause the casualties of innocent civilians. In the proposed RP-GA-XGBoost algorithm, a novel method that incorporates random forest (RF) and principal component analysis (PCA) is devised for selecting features, and a genetic algorithm is used to tune the hyperparameters of XGBoost. The proposed method is evaluated on the public dataset (Global Terrorism Database, GTD) and the terrorist attack dataset in China. Experimental results demonstrate that the proposed algorithm achieves area under curve (AUC) of 87.00%, and accuracy of 86.33% for the public dataset, and sensitivity of 94.00%, AUC of 94.90% for the terrorist attack dataset in China, which proves the superiority and higher generalization ability of the proposed algorithm. Our study, to the best of our knowledge, is the first to apply machine learning in the management of terrorist attacks, which can provide early warning and decision support information for terrorist attack management.

Microcycles of Terrorist Violence in Turkey: a Spatio-temporal Analysis of the PKK Attacks

Geography and time are the two constraints on illegal acts. The extant research on terrorism suggests that terrorists make an expected cost-benefit analysis, and thus make bounded, rational choices regarding their attacks. They carry out attacks that are likely to benefit their organizational goals, and they commit attacks choosing the easiest way with the least effort. This assumption leads to the conclusion that their attacks are likely to be clustered over space and time, and hence predictable. The purpose of this study is to examine whether the attacks of the PKK—a separatist terrorist organization—form microcycles in Turkey. In this study, we use the Global Terrorism Database (GTD) to examine 1261 terrorist attacks of which locations are known and attributed to the PKK. Our research findings suggest significant evidence to conclude that a pattern exists over both space and time regarding distribution of the terrorist attacks. Results from our logistic regression model demonstrate that non-lethal attacks or those occurring in Istanbul or Ankara are more likely to be contagious. We argue that our research findings and policy implications could be useful to create more effective terrorism prevention strategies and policies.

Provoking Ordinary People: The Effects of Terrorism on Civilian Violence

Research on the effects of terrorism mostly focuses on the coercive effects of violence on the macrolevel, while other effects like provocation, particularly on the microlevel, do not receive the same attention. In this article, we seek to address previous omissions. We argue that terrorism can provoke ordinary people into a violent reaction. By reducing perceived security and creating a desire for revenge terrorism may lead civilians to attack uninvolved members of the terrorists’ constituency. Using geo-referenced data on terrorism (Global Terrorism Database) and violent riots (Social Conflict Analysis Database), we assess with a matched wake analysis if the treatment of terrorist violence against civilians causes an increase in violent behavior. The results of our analyses show that terrorism significantly increases violent riots. We thus conclude that terrorism can not only provoke governments but also civilians into an overreaction.

Data Mining Approach to Counterterrorism

Terrorism has long been a major threat to the world for many years and different governments have used different approaches to tackle it. This study reports on the use of available data about terrorist incidents all around the world in combating terrorism with the application of deep learning. There was a comprehensive literature review and the analysis of existing systems and ideas gathered were used to develop the system. This project is done in order to improve on the work carried out by Trisha J. (2018). To improve on the work, extra features were introduced in the dataset and a deep neural network (DNN) model for predicting the success of terrorist attacks was developed. Dataset from the Global Terrorism Database (GTD) were used to train the model. Our proposed model achieved performance accuracy of 91.371% as opposed to that of Trisha J. (2018) which achieved the performance accuracy of 91.18%. Keywords: Terrorism, deep neural network, global terrorism database, data mining

Features of Terrorist-Oriented Criminality in the Socialist Republic of Vietnam and Measures of Legal Response to Fight it at the Present Stage

This article examines distinguishing features of terrorist-oriented criminality in the Socialist Republic of Vietnam, exploring quantitative indicators of certain types of crimes. It is concluded that the current level of political violence in Vietnam is low. Using a wide range of data sources on composite indicators (Global Terrorism Index, Global Terrorism Database and Global Peace Index), it is concluded that to date Vietnam has recorded a low level of political violence. The research explores basic «criminogenic» conditions or factors that lead to relevant risk of growth of political violence. It should be noted that to some extent ethnic tensions still exist in Vietnam. There is also a great concern about criminal activity of a number of domestic and international terrorist organizations, which, in the short or long term, could disrupt domestic political situation and escalate terrorism. The researchers argue that although political and religious motives (e.g. establishing an Islamic state) underlie certain terrorist activities of international terrorist organizations and the fact that Muslims in Vietnam make up about 0,1 % of the countrys population, Vietnams international commitment to counter-terrorism is likely to make it a target of retaliation by these organizations. In addition, there is a possibility that these organizations may commit terrorist acts within the territory of the Socialist Republic of Vietnam to support and fund terrorist activities in the future. We summarized that as at present in force Criminal Code of the Socialist Republic of Vietnam includes special provisions that carry liability for individual acts showing signs of terrorism (arts. 113, 299, 300 CC SRV) and norms within international obligations that cover criminal liability for other crimes of terrorist nature (crimes with indicators of terrorization). The comparative legal analysis of anti-terrorist statutes presented in the 2015 version of the Criminal Code of the Socialist Republic of Vietnam reveals legal and technical defects in certain material elements of terrorist offences. It is noted that Vietnamese legislator distinguishes two forms of terrorism: «traditional» terrorism, which pursues political aims (criminal acts against the peoples government, committed for the purpose of combating it) and terrorism aimed at creating a climate of fear in society.