Анализ рисков терроризма для населения ряда стран и населения мира в целом, 2011–2020 гг.

Risk assessment and categorization of terrorist attacks can assist enhance awareness of terrorism and give crucial information support for anti-terrorism efforts. This study utilizes quantitative approaches for the risk assessment and categorization of terrorist attacks. A total of 210,454 terrorist attacks that occurred worldwide from 1970 through 2020 were collected in the Global Terrorism Database, and 22 indicators related to the risk of terrorist attacks were selected. Then, the moment estimation theory and four comprehensive evaluation models were utilized to identify the top 10 riskiest terrorist attacks in the world. Furthermore, the five clustering analysis methods and three evaluation criteria were performed for the risk categorization of terrorist attacks, and the visual analysis was carried out using the kernel density estimation method. The research results have identified the top 10 riskiest global terrorist attacks, which were led by the September 11 terrorist attack event, along with their downward counterfactual events. The spatial distribution of global terrorist attack risk is primarily composed of four “turbulent cores” in the region of Central Asia, Middle East & North Africa, South Asia, and Central America & Caribbean. This study also provided insights and recommendations for anti-terrorism efforts. It has realized the risk assessment and categorization of terrorist attacks, aiding in the swift identification of its risk levels, and holds immense significance for safeguarding global national security and societal stability under new circumstances.

The use of chemical weapons in terrorist attacks, though rare, remains a significant challenge and concern due to their ability to inflict mass casualties. Chemical attacks remain a topic of interest for Disaster Medicine (DM) and Counter-Terrorism Medicine (CTM) specialists and are clearly an area in need of enhanced preparedness. This study aims to provide an epidemiological description of all terrorism-related attacks using chemical agents as a primary weapon, sustained from 1970 - 2019. These data will be useful in the development of education programs in CTM and provide an insight into how best to prepare for potential attacks in the future. Data collection was performed using a retrospective database search through the Global Terrorism Database (GTD). The GTD was searched using the internal database search functions for all events using chemical weapons as a primary attack method from January 1, 1970 - December 31, 2019. Years 2020 and 2021 were not yet available at the time of the study. The GTD also details the specific chemical used, when known, in the summary of incidents. Results were exported into an Excel spreadsheet (Microsoft Corp.; Redmond, Washington USA) for analysis. A total of 292 terrorist attacks involving chemical agents as a primary attack method were recorded from 1970 - 2019, registering 284 deaths and 13,267 injuries. Acid (52) was the most commonly used chemical agent, followed by "unspecified poison" (43), "unknown chemical agents" (29), "unspecified gas" (27), tear gas (27), chlorine gas (24), cyanide (21), mercury (9), pepper spray or mace (9), mustard gas (8), insecticide or 1080 (8), diphenylamine chloroarsine (7), phosphate or phosphorous (3), sodium hydroxide or corrosive liquid (3), sarin (2), "unspecified drugs" (2), VX nerve gas and other nerve gas (2), pesticides (2), cleaning chemicals/paint thinner (2), ammonia (2), anesthesia agent (1), arsenic (1), chlorine and mustard gas mix (1), phenarsazine chloride (1), rat poison (1), unknown irritative gas (1), hydrochloric acid and sodium cyanide mix (1), unknown white powder (1), antiseptic dye (1), and chlorine gas and white phosphorous mix (1). The use of chemical weapons in warfare, though prohibited by the Chemical Weapons Convention (CWC), remains a rare but concerning terrorist attack methodology. In recent years, there have been more instances where potentially deadly chemicals have been used in civilian settings. Dual use industrial chemicals, in particular, pose a significant concern. Acid was the most commonly used chemical weapon in 52 attacks. Tear gas, chlorine, and cyanide were each used in over 20 attacks. Both DM and CTM specialists advocate for better preparedness and response training for intentional events in civilian settings.

Terrorism is the evolving phenomenon which has been increased to a huge extent in the past few decades which threatens the stability of a country / region. Government Officials like FBI, CIA etc. could not depend upon only telecommunications, satellite activities etc. to capture activities of terrorists as they are prone to these technologies and can easily plan attacks against it. Real time collection of terrorism data can be a source of great use for counter terrorism measures. But to process such huge growing data one need the efficient methodologies to practically visualize the complex unstructured data. Data Science provides efficient way to process infinite growing data with time with distributive frame works, statistical and mathematical computation modeling, clusters etc.. We had developed a model to analyze real time terrorism data with the help of data science in python to solve the existing and growing problem of terrorism in India. The Data Science Model is based on the Global Terrorism Database (GTD) which contains the records off terrorist attacks since 1970. The model is used for the visualization of the Real-Time-Data of the terrorist attacks with the help of data manipulation tools in python. It is an intelligent early warning model which includes the Terrorist attack in India since 1970. The model proposes the statistical model, analysis, correlation and findings in the Punjab region. It includes the analysis of geospatial data, REST API (Foursquare API), data manipulation with pandas, clustering with folium, seaborn, plotly and other data visualization tools.

The rapid popularization of unmanned aerial vehicles (UAVs; also referred to as drones), in both the recreational and industrial sectors, has paved the way for rapid developments in drone capabilities. Although the threat of UAVs used by terrorists has been recognized by specialists in both Counter-Terrorism and Counter-Terrorism Medicine (CTM), there are limited data on the extent and characteristics of drone use by terrorist organizations. Data collection was performed using a retrospective database search through the Global Terrorism Database (GTD). The GTD was searched using the internal database search functions for all terrorist attacks using UAVs from January 1, 1970 - December 31, 2019. Years 2020 and 2021 were not yet available at the time of the study. Primary weapon type, number and type of UAVs used, related attacks, location (country, world region), and number of deaths and injuries were collated. Results were exported into an Excel spreadsheet (Microsoft Corp.; Redmond, Washington USA) for analysis. There were 76 terrorist attacks using UAVs. The first attack occurred in 2016, and the number of attacks per year varied considerably (range: 4-36). Forty-seven of the 76 attacks (70%) were successful. Twenty-seven individually listed events (36%) were related and part of nine coordinated, multi-part incidents. A total of 50 deaths and 132 injuries were recorded, which equated to 1.09 deaths (range: 0-6) and 2.89 injuries (range: 0-20) per successful attack. The mean number of UAVs used in an attack was 1.28 (range: 1-5) and multiple UAVs were used in 22% of attacks. The use of UAVs to carry out terrorist attacks is on the rise. Seventy-six terrorist attacks using this novel method were recorded since 2016, killing 50 and injuring 132 people. While the use of UAV-related explosives appears less lethal than traditional explosive attacks, advancing technologies and swarming capabilities, increasing ability to carry larger payloads, and the possibility of UAVs to disperse chemical, biological, radiological, and nuclear (CBRN) weapons will likely increase UAV lethality in the future, requiring CTM specialists be more proactive.

Recent studies suggest an association between sympathies for violent protest and terrorism, and major depression, anxiety, post-traumatic stress disorder and psychiatric disorders in subgroups of radicalised people and in lone-actor terrorists. The aim of this study is to identify and analyse all documented terrorist attacks in the Global Terrorism Database (GTD), where the motive for terrorism is questioned due to suspected mental health issues. This study is based on a semi-quantitative, epidemiological analysis of all incidents from 1970 to the first half of 2021, as reported in the GTD. Incidents in which the act of terrorism was questionable because of alleged mental illness were included. Temporal factors, location, target type, attack and weapon type, perpetrator type and number of casualties were collated. One hundred and two incidents in the period 1970-2020 and five incidents in 2021 were studied. The majority occurred in the period 2011-2020. The incidents resulted in a total of 99 fatal and 217 non-fatal injuries. Twenty-nine perpetrators died during the attacks.The majority of the attacks occurred in the USA, followed by France and the West Bank and Gaza Strip. Armed assaults were the most frequently identified attack type (67%).In North America, the incidence was as high as 8.2 and 3.4% of the total number of terrorist attacks in the periods 2001-2010 and 2021, respectively. Most of the perpetrators acted as lone actors. Five assailants were detained in a psychiatric facility after the judicial probe, 18 were convicted and 9 had not been sentenced. The possible relation between terrorism and mental illness or addiction is a recent phenomenon in the GTD. The prototypical case consists of a lone actor suffering from an assumed mental illness committing an armed assault. Only a minority of perpetrators were unable to stand trial in this series.

With over 14% of all terrorist attacks since 1970 targeting law enforcement, terrorist attacks on police is a problem in need of scholarly attention. Police serve as symbolic targets of the government and strategic targets of terrorist attacks, yet we know little about such attacks. This article explores terrorist attacks targeting police in heavily hit countries, drawing from the Global Terrorism Database. While Iraq and India have the most terrorist attacks targeting police, these countries also have a high number of terrorist attacks against all targets. To account for the total number of terrorist attacks, proportions are explored, finding Macedonia, Russia, and Georgia have the highest proportions of terrorist attacks targeting police between 1998 and 2010. A common thread among these heavily hit countries is a rapidly changing governing regime coupled with societal schism—in other words, these countries seem to share low governmental legitimacy. Implications for future research are discussed.

Background Terrorist attacks have the potential to be mass casualty events, causing multiple injuries and deaths. High injury rate attacks will particularly place a high burden on emergency medical systems. This study aimed to assess if there is a difference between attacks with high injury rates and high fatality rates. Methods The top 100 terrorist events causing the highest number of fatalities versus the highest number of injuries were selected from the Global Terrorism Database. Analyses were performed on temporal factors, location, target type, attack and weapon type, and perpetrator type. Results The 9/11 attacks caused the highest number of both fatalities and injuries. With regards to injury rates, the sarin attacks in Tokyo, Japan ranked second. Events with high fatality rates were overrepresented in Sub-Saharan Africa, whereas events with high injury rates were predominant in the Middle East & North Africa. High fatality rates were most often associated with armed assaults and hostage takings. Bombings were responsible for the highest number of injuries. CBRN attacks were overrepresented in the top 100 injuries, and accounted for 11% of the incidents. Conclusion High injury rate incidents place a heavy burden on the health care system as the number of injuries is nearly ten times as high as the number of injuries in high fatality rate incidents. Epidemiological analysis of high impact terrorist events may contribute to counter-terrorism preparedness, to an increased focus on dealing with CBRN-events, and thus to a proper medical response to future terrorist events.

The global terrorism database (GTD) shows that 3,207 out of the total 191,464 terror incidents across the world from 1970 to 2018 were targeted at other terrorists and non-state militias. This study investigated why terrorists attack other terrorists. The GTD has three variables on terrorism criteria that indicate the motive of an attack. The criteria include criteria 1: the attack incident was aimed to attain a political, economic, religious, or social goal; criteria 2: the attack incident was aimed to coerce, intimidate, or publicize to larger audiences; criteria 3: the attack incident was an action outside international humanitarian law. Obviously, all terror attacks satisfy criteria 3 by default. The risk ratio was deployed on the GTD to evaluate which of the two criteria (criteria 1 and 2) has an association with terror attacks on terrorists. It was discovered that terrorists attack other terrorists when the purpose is to attain a political, economic, religious, or social goal (criteria 1). However, when the purpose of an attack is to coerce, intimidate, or publicize to larger audiences (criteria 2), it is very unlikely that such an attack would be targeted at other terrorists. The relevance of these findings in counterterrorism is discussed.

The global terrorism database (GTD) shows that 3.5% of the total terror attacks across the world between 1970 to 2019 were targeted at tourists. A terror attack can be perpetrated by either a lone wolf or an affiliated terrorist. The analysis of the GTD conducted in this study shows that a terror attack targeted at tourists is 4.3 times more likely to have been perpetrated by a lone wolf than by affiliated terrorists. Since lone wolves operate individually, this finding implies that access control measures at tourist centers must regard individuals such as hawkers, newspaper vendors, freelance journalists, etc. who come around to do various businesses around tourists as potential terrorists until proven otherwise. Since lone wolves do not work for a terror group, tourist attraction centers located in the regions, territories, and countries with no presence of terror groups must not relax their counterterrorism control measures under the impression that they are safe from terror attacks.

The past years have witnessed increasingly widespread terrorism, violently destroying world peace and regional prosperity. Therefore, uncovering terrorist plots has become the most crucial step for eliminating terrorist attacks. However, with the terrorist scheme being disguised under the huge amount of data flow on the internet, identifying terrorist organizations still remains challenging. Since many terrorist organizations are prone to launch terrorist attacks together, here, we model their relationships as a Terrorist Organization Alliance (TOA) network and propose a novel method to identify the key terrorist organizations in the TOA network. The TOA network utilizes existing key nodes in order to extract useful information, and, with the help of the entropy weight method, the new solution to the TOA network is effective and precise. The experiments are performed on the dataset from the Global Terrorism Database, and the results are statistically validated through t-tests and convergence analysis. Compared with the traditional methods, our method is proven to be superior in terms of measure the harm of terrorist attack organizations and find the key terrorist organizations.

High profile terrorist attacks in major capital cities have seemingly become a regular occurrence and the resultant mass-casualty events continue to challenge health care systems. Counter-Terrorism Medicine (CTM) addresses unique terrorism-related issues relating to the mitigation, preparedness, and response measures to asymmetric, multi-modality terrorist attacks. This study is an epidemiological examination of all terrorism-related events sustained from 1970-2019, analyzing historical weapon types used and the resulting fatal injuries (FI) and non-fatal injuries (NFI) sustained. The Global Terrorism Database (GTD) was searched for all attacks from 1970-2019. Attacks met inclusion criteria if they fulfilled the three terrorism-related criteria, as set by the GTD codebook. Ambiguous events were excluded. State-sponsored terrorist events do not meet the codebook's definition, and as such, are excluded from the study. Available counts of FI and NFI in each incident were then sorted and aggregated by weapon type to enable mean and standard deviation calculations. In total, 168,003 events were recorded from the years 1970-2019. Explosives, bombs, and/or dynamite (E/B/D) were the most commonly used weapon type and accounted for 48.78% of all terrorism events, followed by the use of firearms in 26.77% of events. A total of 339,435 FI and 496,225 NFI resulted from all terrorism events that occurred during the study period. Combined, E/B/D and firearms accounted for 75.55% of all events, 67.1% of all FI, and 79.3% of all NFI. Each individual terrorism event inflicted a mean FI rate of 2.14 FI per event (SD = 10.2) and a mean NFI rate of 3.22 NFI per event (SD = 45.19). Although terrorism is complex and does not solely rely on death tolls as a measure of success, this analysis shows a historic mean FI rate of 2.14 and NFI rate of 3.22 per event over the past 50 years. Proven weapons such as E/B/D and firearms combine to account for over 75% of weapon types used in all events. Use of weapons of mass destruction (WMDs) such as chemical, biological, radiation, and nuclear (CBRN) weapons has been rare (0.2%), yet has extreme high potential to inflict mass casualties with mean NFI rates of 49.62 and 28.75 for chemical and biological weapons, respectively.

The success of terrorist attacks reflects the capability of terrorists and the vulnerability of the security defense, explainable prediction of the average attack success rate at the country-annual level is crucial for governments. In this study, terrorist attack data from 146 countries between 2002 to 2020 was obtained from the global terrorism database (GTD), and a two-stage prediction task was conducted. First, multiple machine learning models, including XGBoost and Random Forest (RF), are used to predict the average success rate of terrorist attacks in the next year, considering terrorism root factors and statistical results from the previous year. The results show that the RF model performs the best. Second, the prediction outputs of the RF model are explained using interpretable methods, including Accumulate Local Effect (ALE) and SHapley Additive exPlanation (SHAP), to provide counterterrorism insights applicable to countries around the world.

ABSTRACTThe introduction of the Global Terrorism Database (GTD) nearly a decade ago sparked a revolution in terrorism studies. However, one major flaw in the database continues to plague GTD users. Data lost prior to digitalization, along with unsuccessful data recollection efforts, have left GTD without data on events that took place during the year 1993. The missing data prevents researchers from using the entirety of GTD's annual range (1970–2014) to conduct reliable time-series analyses. Additionally, it has likely contributed to the formation of theories and claims on faulty empirical ground. To remedy the problem, we have collected data on 4,206 unique terror-attack incidents, with the aim of documenting the universe of 1993 terrorism events. This article showcases our 1993 dataset and illustrates the importance of terrorism events in 1993 for the development of conflicts in Israel, Afghanistan, Colombia, and India.

Recent literature has described a rise in the activity of right-wing extremists in the United States. Several studies have examined this phenomenon in relation to the actions of President Trump. Comparatively, little research has examined the impact of the Obama presidency on right-wing extremism despite a peak in the number of right-wing extremist groups during his second term. Using a power-threat framework, this study examines the unique effects of the presidential candidacies and elections of Obama and Trump on the frequency of attacks committed by right-wing extremists in the U.S. as documented in the Global Terrorism Database (GTD). Autoregressive Integrated Moving Average (ARIMA) modeling is applied to monthly counts (n = 151) of 141 domestic terrorist attacks committed by right-wing extremists that occurred in the U.S. between June 3, 2006, and December 31, 2018. Consistent with the political threat hypothesis, our findings indicate that the re-election of President Obama was associated with a gradual, permanent increase in the frequency of attacks by right-wing extremists. Yet, none of the intervention components associated with his first candidacy or election were associated with statistically significant changes in right-wing terrorist attacks. In contrast, and in accordance with the emboldenment hypothesis, all intervention components associated with the candidacy and election of Donald Trump predicted permanent increases in the frequency of attacks-and most were abrupt in nature. In view of these findings, political leaders on the left and right must anticipate the ability of their rhetoric and behavior to both alienate and embolden extremist groups and individuals, particularly within the far-right. As our findings demonstrate, failure to do so risks contributing to increased activity among far-right extremists as a product of either political threat or emboldenment.

We investigate whether terrorist activity abroad affects worry regarding terrorism in Sweden, and the possible mediating effect of news media. Terrorism uses violence to obtain political or social objectives: in addition to the impact on the immediate victims, terrorism affects a much wider audience emotionally by spreading fear and insecurity. Previous research shows that terrorist attacks in a country cause worry for the people in that country; however, little is known about the relationship between public worry and terrorist attacks abroad. This study draws from the Global Terrorism Database (GTD), the Norwegian Defence Research Establishment (FFI), the Swedish press archive Mediearkivet, and the Swedish National Annual Survey (SOM), producing a theoretical model using Generalized Structural Equation Modelling (GSEM). The results show that public worry about terrorism co-varies with the frequency of terrorist activity occurring in the wider geo-cultural region, even if outside of the country of residence. It also shows that public worry is affected not only by single, impactful attacks – so-called ‘one-off’ attacks – but also by an increase in the number of total (even if less individually impactful) attacks in the region. Notably, media coverage ameliorates the impact of terrorism on public worry to some degree. For policy makers these results are particularly important since they show that even in countries free of terrorist events, public fear needs to be managed.