A Lone Wolf vs. an Affiliated Terrorist

A radicalization is a worldwide event that impacts multiple nations and is present in various historical contexts. In the study of radicalization of persons who work autonomously from more radicalized communities, psychologists may support it. As there is no unique identity, these single actors or lone wolves are more difficult to spot because they behave as self-determined people. The current chapter's emphasis is on the mechanisms and methods of radicalization in adults, including children and women’s radicalization. In the study of radicalization, there is little probability of direct contact with the target community (terrorists, lone wolves, and radical groups) that is much of the time distant, dangerous, and shielded from media attention. In this instance, the application of ethnographic studies also through Internet outlets has yielded adequate results. Focus is also given to the growth of radicalized ideology and how radicalization can be viewed in terms of the lone wolf terrorist’s cognitive and social progress. The writers often discuss how a radicalized leader can exploit the insecurity of individual citizens to radicalize them. Besides, as a logical fallacy and a symptom of dualistic thinking, the writers researched radicalized thought. Therefore, in their propensity to radicalize, a combination of perceptual, mental, and psychological stimuli is analyzed.

Far-right–inspired violence in the United States is on the rise (Perliger, 2013), and there is a growing realization within policy circles of the increasing threat from so-called "lone wolf" terrorists of different ideological hues (Simon, 2013). A more in-depth understanding of individual offenders and their behaviors (both antecedent and offense-commission) is therefore of great importance not only to the academic literature but also for practitioners tasked with countering the problem. The need for such research is also driven by the fact that a preponderance of studies have focused on violent Islamist organizations for more than a decade. Given the nature of the threat presented by al-Qaeda, this is understandable, but a side effect is that our understanding of the nature of far-right–inspired homicide lags behind our understanding of the behaviors associated with analogous movements. Recognizing these features of the existing literature and the current security environment, Gruenewald, Chermak, and Freilich (2013, this issue) provide an empirical assessment of the behavioral underpinnings of far-right–inspired homicide offenders and compare group-based offenders with lone offenders. Gruenewald et al. (2013) test 23 hypotheses, each of which is derived from a careful examination of the existing literature. Using inferential statistics, they find several significant differences between lone and group offenders. For example, the bivariate analysis suggests that compared with group offenders, far-right lone offenders are statistically more likely to be unmarried, have experience of the military, live alone, use firearms, select government targets, kill more people, and die in the commission of their offense. The multivariate analysis also suggests that age and mental illness also significantly distinguish lone offenders from group offenders (e.g., lone offenders are typically older and more likely to have a history of mental illness). For the remainder of this essay, we consider the salient issues in the available relevant literature in relation to Gruenewald et al.'s (2013) study by identifying and discussing specific and actionable next policy and research steps, as well as this study's potential impact on the current state of knowledge. Reviews of the terrorism research literature have regularly highlighted the paucity of original data that inform analyses (Schmid and Jongman, 1988; Silke, 2001, 2004). In the most recent review of the literature, Silke (2013: 34) noted: "[O]ne feels that a great deal more needs to be done before research is consistently building on past work rather than rehashing old data." Although the use of inferential statistical methods is certainly on the rise with relation to terrorism research, these studies typically tend to be based on terrorist events rather than on the individual offenders. This is largely because of the data available from the Global Terrorism Database. More recently however, there have been a handful of large-N studies of terrorist group membership that primarily use descriptive statistics (Gill and Horgan, in press; Horgan and Morrison, 2011; Magouirk, Atran, and Sageman, 2008; Reinares, 2004; Sageman, 2004). Gruenewald et al.'s (2013) article is a major next step in the study of the individual terrorist. Their development of the U.S. Extremist Crime Database (ECDB) provides a solid empirical basis from which inferential statistical approaches to the study of extremists and most importantly extremist behavior can be conducted. Gruenewald et al.'s (2013) study highlights significant behavioral and personal differences between far-right–inspired lone and group offenders. Although some of these differences were expected based on their survey of research on lone-actor terrorism, they neglected to mention that a few studies of different crimes have found broadly similar results. For example, Alarid, Buron, and Hochstetler's (2009) study of robberies showed that group offenders were more likely to be younger, unmarried, and less educated. In terms of target selection, there was little difference between the difficulty levels of robberies chosen by group and solo offenders, which runs counter to much theorizing concerning "strength in numbers," and offending (see Felson, Baumer, and Messner, 2000, for example). Using vastly different samples, studies comparing lone and group rapists have found that the former tended to be significantly older (Bijleveld and Hendriks, 2003; Hauffe and Porter, 2009; Ullman, 1999; Wright and West, 1981), significantly more likely to be married and have children, significantly less likely to have a history of substance abuse (Hauffe and Porter, 2009), significantly more likely to have previous convictions and problematic personality structures (Bijleveld and Hendriks, 2003), and significantly more likely to be employed (Ullman, 1999). Hickle and Roe-Sepowitz's (2010) study of female juvenile arsonists found solo offenders more often came from unstable homes; more often experienced school difficulties, behavioral problems, and negative emotions; and expressed suicidal thoughts more regularly (the latter finding is particularly relevant to Gruenewald et al.'s study when we consider their finding that lone offenders were more likely to die in the commission of their offense). Block's (1985, 1986) study of Chicago-based homicides illustrated that group offenders were significantly younger than lone offenders. Cheatwood and Block's (1990) study on homicides in Baltimore also found a disproportionate number of juvenile offenders engaging in homicides as members of groups rather than as individuals. In the most comprehensive of such analyses, Clark (1995) analyzed data across nine U.S. cities. Again, group offenders were significantly younger. Similar to Hauffe and Porter's (2009) results (discussed previously), lone offenders were less likely to have a history of substance abuse than group offenders. Unlike research on robberies, group homicide offenders were more likely to have previous criminal convictions (Clark, 1995). Aggregating a large number of crimes, Van Mastrigt and Farrington (2011) analyzed U.K. police data; group offenders were significantly younger than lone offenders and tended to have more criminal convictions. This finding is common when the offender sample is aggregated across crime types (Erickson, 1971; Hindelang, 1976; Reiss and Farrington, 1991). Collectively, these studies should raise future questions about what factors drive these differences across crime types. For example, answers may lie in individual decision making, gatekeeper selection effects, and group dynamics and influences. The collective findings also suggest that some factors may be crime specific (e.g., previous convictions), whereas others may be crime general (e.g., age and mental illness). These studies also highlight, from a policy and practitioner perspective, whether desistance and disengagement from crime is a different process for solo and group offenders. The importance of Gruenewald et al.'s (2013) study lies not only in its use of inferential statistical methods and in its delineation between far-right–inspired lone and group offenders, but also the findings have important implications for issues long debated within the literature, particularly issues concerning mental illness and terrorist involvement, as well as issues concerned with group processes. In the 1970s, the first wave of studies on the individual terrorist offered psychopathological interpretations that perceived terrorist behavior to be essentially deviant. An underlying assumption in this research strand is that compulsion to join the militant organization, or the vulnerability to recruitment, is inherent in those who become engaged in militancy. Motivation to participate is therefore situated within the individual in isolation. To this end, researchers have postulated deviant characteristics of the terrorist. For Victoroff (2005), this field was "largely characterized by theoretical speculation based on subjective interpretation of anecdotal observations" (p. 3). In the 1980s, psychoanalytic approaches (with a particular emphasis on the concept of narcissism) largely replaced psychopathological explanations. These findings are reasonably similar to the preceding assumptions of the terrorist personality being essentially abnormal but perceive this abnormality as determined by unconscious drives and urges originating from childhood rather than inherent personality flaws. Over the past 15 years or so, a growing awareness of the need to understand the group process has come to fruition. This has largely been aided by empirical studies that have engaged in first-hand interviews and by the incorporation of theory from social psychology. This stream of research has been successful at downplaying the role of personality and mental health issues with regard to terrorist involvement to the extent that one noted academic, who in the past championed psychoanalytical interpretations of terrorist motivation, argued that "a clear consensus exists that it is not individual psychology, but group, organizational and social psychology, that provides the greatest analytical power in understanding this complex phenomenon" (Post, 2005: 7). Although the studies of the 1970s and 1980s were correctly debunked on methodological grounds, Gruenewald et al.'s (2013) findings suggest that the existing consensus that mental illness never plays a role in terrorism and that terrorist behavior can be purely explained by group processes is likely to be a fallacy. With regard to group processes, Gruenewald et al.'s (2013) study supports recent work that has started to reexamine the role of group processes in terrorism. For example, the debate has been widened by Taylor (2010: 121), who argued that "group-focused causal accounts fail to offer sufficient explanations of the behaviors identified" in his case studies, whereas Gill (2012) attempted to refine the nature of role-specific qualities and group-based behavior. Although many studies of the individual terrorist are fixated with understanding motive and/or radicalization (this is also true for media accounts if we examine the coverage regarding the recent Boston Marathon bombings), Gruenewald et al. instead focus on behavior. Their findings that lone offenders are significantly more likely to have experience of the military and live alone also importantly provide insight into capability. Group membership provides individuals not only the operational capabilities necessary to perform a terrorist attack but also the mechanism for moral disengagement (Gill, 2012). Research literature from military psychology has suggested that many factors inhibit individuals from engaging in fatal violence against others. For example, Marshall concluded that "the average and healthy individual … has such an inner and usually unrealized resistance towards killing a fellow man that he will not of his own volition take life if it is possible to turn away from that responsibility … at the vital point" (cited in Grossman, 1995: 29). Absent a group setting, terrorist violence may be difficult to commit for practical and psychological reasons. In the absence of a group, an individual may need other factors to (a) provide security, (b) help overinhibitions against committing violence, (c) help develop the necessary practical skills, and (d) finance an operation. Here, variables found to be significant in the current study such as living alone at the time of the attack and military training provide the capabilities to turn motivation into action for lone offenders. This is also true for hypotheses that were unsupported, such as lone offenders being more likely to be unemployed. Without a group to help an individual plan, prepare, and carry out a successful attack, the lone offender must have a steady source of income. This observation is highlighted in the case of Anders Breivik in Norway, who financed his operations through several legal and illegal activities in the years before his attack and avoided delaying his attack further because he was having liquidity issues and feared he could not (a) keep renting the farm where he built his improvised explosive device and (b) rent a car for the operation itself. With regard to mental illness and terrorism, Gruenewald et al.'s (2013) finding that more than 40% of lone offenders had previously been diagnosed with mental illness is one of the most statistically significant findings from the multivariate analysis. Despite its importance, this finding receives minimal attention in the concluding remarks and policy implications. This may be born out of discrepancies across the literature concerning mental illness and terrorism, leading to the current existing false dichotomy that an act of targeted violence was either the actions of a terrorist or the actions of someone who was mentally ill. Gruenewald et al. do suggest important methods for identifying diagnoses, but we hold the opinion that future research should use mental illness as a central unit of analysis. In doing so, it would provide a better understanding of the complexity of mental illness with relation to terrorist behavior and provide the possibility to examine how the other variables would affect and be affected by the offender suffering from mental illness. In other words, the mental illness variable is likely to stem from several other variables accounted for in the ECDB database and impact many other variables also. For example, research by Elisha, Castle, and Hocking (2006) illustrated that social isolation is highly prevalent among those diagnosed with a mental illness. Of their 3,800 observations of individuals diagnosed with a psychotic illness, 58% were also characterized as being socially withdrawn. Butterworth and Rodgers (2008) demonstrated that couples with at least one spouse diagnosed with a mental illness suffer higher rates of marital disruption than non–mentally-ill couples. Using mental illness as a central variable with relation to the criminogenic factors may also be a promising approach. As Anderson (1997) explained, the symbiotic relationship between mental illness and criminal behavior is complex. Comorbidity of mental illness with other behaviors is well documented across the literature and includes substance abuse (Todd et al., 2004) and violent and criminal convictions (Anderson, 1997). It is also a common understanding in psychiatric practice (Diagnostic and Statistical Manual [DSM] and International Classification of Diseases [ICD]). Gruenewald et al.'s (2013) study found that 34% of lone offenders had substance abuse problems and that 61.7% had prior arrests. Taking into consideration the complexities that comorbidity brings, it may be necessary in the future to distinguish between lone offenders who were mentally ill and those who were not to determine and compare the rates of substance abuse and criminal convictions, as well as compare these with group actors. Many different mental illnesses display impulsivity as a problem behavior (DSM and ICD), which affects many aspects of living and may affect the attack types of offenders, as well as the primary weapon usage. The current study found that 84.8% of lone offenders used a gun, compared with 40.2% of group offenders. This finding is highly significant, but if one takes into account the country that the data were taken from (the United States) and the gun control laws, it could be hypothesized that lone offenders were more likely to use a gun because nearly half struggled with impulse control and guns are freely and immediately available. It is also interesting to note the potential link between the highly significant finding that lone offenders were more likely to partake in a suicide mission compared with group offenders given the higher levels of mental illness found in lone actors. This finding is interesting because suicide risks are much higher in the mentally ill population, and if non–mentally-ill lone actors were investigated separately, this figure may decrease to a value approaching that of group-based offenders. Finally in relation to mental illness, Gill, Horgan, and Deckert (in press), and many of the group versus solo offender studies cited previously, also found the average age of lone offenders to be older than that of group offenders. This finding may provide support for the idea that a different temporal trajectory into criminality is at play for lone- and group-based offenders. It may be necessary to consider and examine whether the increased age range is a result of the later onset of mental illness. For example, military service personnel are at high risk of developing posttraumatic stress disorder (PTSD) (Sundin et al., 2010), which again may in part explain the highly significant discrepancies between lone and group offenders Gruenewald et al. (2013) identified three policy recommendations that should be tailored from preexisting policies to fit the problem of lone offenders. Importantly, Gruenewald et al. make the point that lone offender attacks are preventable, which runs counter to several current studies that have not had the benefit of the high-quality data sets or rigorous methodologies that Gruenewald et al. used (Barnes, 2012; Michael, 2012; Simon, 2013). The first recommendation is to increase intelligence partnerships between law enforcement and other organizations such as military intelligence units and social service agencies. This suggestion stems from the finding that lone offenders were significantly more likely to have military experience and a history of mental illness. We suggest that this could go further. The policy implications of our suggestions regarding the future study of mental illness with relation to terrorism suggests using multiple agencies at numerous intervention stages (social services, policing agencies, the courts, military organizations, psychiatric hospitals, weapons providers, community programs, financial agencies, intelligence agencies, and the media), which could all cooperate to aid in prevention and reduction efforts. The second recommendation involves increasing technological surveillance, which spans a wide range of functions including monitoring websites and chat rooms, collecting intelligence, creating fake websites, building relationships with chat room moderators (and thereby increasing guardianship), and countering extremist narratives. These behaviors, if applied correctly, could also help prevent and disrupt online group-based offenders. The final recommendation is to sharpen threat assessment tools, which is similar to recommendations stemming from broadly similar studies of school shooters and politically motivated assassins (Fein and Vossekuil, 1999; Vossekuil et al., 2002). The significant behavioral differences between lone and group offenders found using the ECDB data suggest the need for a tailored response to both subgroups. It also serves to raise further questions about whether these differences hold true for other ideological motivations. Gill, Horgan, and Deckert's (in press) study suggests that identifiable behavioral differences exist among al-Qaeda–inspired, extreme right-wing, and single-issue lone-actor terrorists. The ECDB data also focus solely on offenders who commit fatal attacks. It would be interesting to observe what patterns hold for those who committed attacks that caused no fatalities as well as those whose plots were interrupted preattack. Finally, as mentioned, the ECDB data focus on only U.S.-based offenders, which leads to the question of whether this group of offenders is more likely to use firearms because of the smaller opportunity costs involved. In conclusion, hopefully the highly important results found in Gruenewald et al.'s (2013) study will lead to a greater comparative examination of these issues across ideological domains and geographic boundaries. Paul Gill is a lecturer at University College London's Department of Security and Crime Science. His research focuses upon the behavioral underpinnings of terrorist attacks. Emily Corner is a research student at University College London's Department of Security and Crime Science. Her dissertation examines the nature of mental illness in a population of 119 lone-actor terrorists.

Lone wolf or herd animal? Information choice and learning from others

In the broader context of homegrown jihadist terrorism in the West, most interpretations of the 2013 Boston Marathon attack generally conform to the concept of “jihad of individual terrorism”. This concept effectively blurs the boundary between a network agent and a stand-alone “lone wolf”. The choice between the two often boils down to whether or not one accepts that acting in the name of a universalist extremist ideology suffices for otherwise dispersed and unconnected self-generating cells to qualify as parts of a larger network. While conforming to some general patterns of homegrown jihadist attacks in the United States, the Boston Marathon attack stands out for two less typical, and mutually contradictory, characteristics. For a pure “lone wolve” jihadist act, the Boston bombings were a rarely successful mass-casualty attack. This either makes it a major outlier, or suggests some external connections, training or support. However, the bombers' purported links to the North Caucasus militant underground as the suspected foreign source of such support are most atypical for U.S.-based jihadist terrorists, even if such links have some precedence among jihadist cells in Europe.

The purpose of this paper is to investigate the insights that might be generated into the nature of 'lone wolf terrorism' through the application of economic analysis. Orthodox approaches, particularly (standard) expected utility analysis and game theoretical analysis, are discussed. These tools prove useful in developing preliminary or 'first order' insights. The lone wolf terrorist exhibits a number of idiosyncrasies that present challenges to both economic analysis and government security policy. An alternative analytical framework is constructed wherein a terroristic agent makes choices on the basis of a preference ordering constructed over two moments of the distribution (measured in terms of fatalities generated by terrorist attacks). Seven predictions are yielded from the mean-variance theoretical framework and numerical estimates are computed as preliminary steps towards the full exploration of the implications of the framework. Most importantly, depending on their level of risk aversion (or risk seeking behaviour), lone wolves are expected to predominantly choose assassination, armed attack, bombing, hostage taking or unconventional attacks. Furthermore, within a range of between one and two standard deviations from the mean, it is possible that the quadratic utility function will reach a maximum. Following attacks of a certain magnitude (in terms of fatalities), it might be expected that the lone wolf will withdraw from activity for a period of time. This analytical approach may assist governments and security agencies facing the threat of lone wolf terrorism.

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.

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.

Lone wolf terrorism motivated by right-wing extremism is a real problem, which allows itself to be conclusively delineated from other types of terror, frenzied and spree killings (amok). Lone wolves by no means act out of emotion, do not act madly or irrationally, but—completely the opposite—act after thorough planning and out of political motives. They speak of freedom or redemption, declare a race war or consider themselves to be at war with immigrants and refugees. Their ideologically justified hatred of ethnic minorities spurs them on. Their search for a strike against society turns these introverted, absent-minded, often not taken to be “the full shilling” actors into extroverted, strongly focussed offenders by conviction, whether for one singular bestial act or a series of malicious murders. All of this clearly distinguishes them from terrorist organisations, left-wing and Islamic single actors as well as from people running amok.

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.

Purpose The purpose of this study is twofold; first, it aims to understand the underlying dynamics of the organizations behind the terrorist attacks, and second, to investigate the dynamics of terrorist organizations in relation to one another to detect whether there exist shared patterns of terror between different organizations. Design/methodology/approach To achieve this purpose, the researcher proposes a computational algorithm that extracts data from global terrorism database (GTD); calculates similarity indices between different terrorist groups; generates a network data file from the calculated indices; and apply network analysis techniques to the extracted data. The proposed algorithm includes applying SQL database codes for data extraction, building a tailored C# computer software to calculate similarity indices and generate similarity networks and using GEPHI software to visualize the generated network and calculate network metrics and measures. Findings Applying the proposed algorithm to Egypt, the results reveal different shared patterns of terror among different terrorist groups. This helps us in creating a terror landscape for terrorist groups playing in Egypt. Originality/value The importance of the study lies in that it proposes a new algorithm that combines network analysis with other data-manipulation techniques to generate a network of similar terror groups.

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.

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.

The article examines the subject of religious cyberterrorism, which is remains relevant in the contemporary discourse. The author underlines the possibility for terrorist organizations to form "sleeper cells" and "lone wolves" who can be deployed at any time to complete their missions. The article outlines religious terrorist organizations' goals and propaganda methods, as well as countermeasures and counter-propaganda strategies. The relationship between their goals and propaganda tactics, information, and psychological methods of persuasion employed by propagandists is examined. The purpose of this article is to examine the information strategy of terrorist group propagandists aimed at recruiting new combatants, as well as a qualitative examination of legal, technical, and counter-propaganda methods adopted by various governments throughout the world to counteract terrorist propaganda. The author lists countermeasures and evaluates each one's effectiveness. China is used as an example, as it is now the most effective in technological terms, despite criticism from human rights groups. As part of a counter-agitation approach, the experience of getting clergy to dispute terrorist organizations' religious doctrine is explored. It is concluded that, notwithstanding the defeat of ISIS, the problem of opposing religious terrorist propaganda operations remains relevant today. The most essential feature of the article is the investigation of this subject within the context of Kazakhstan.

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.