This document discusses improving the classification of terrorist attacks in Iraq through data preprocessing techniques applied to the Global Terrorism Database. It analyzes different methods for dealing with missing data values and data discretization and evaluates various classifiers. The study finds that data preprocessing significantly reduces classification error rates and adding GPS coordinates for attack locations can further improve accuracy. Traditional statistical modeling of terrorism has limitations that computational analysis and visualization tools can help address by revealing patterns in the data.
Since the terrorist attacks of September 11, 2001 debate has circulated around the nature and success of counterterrorism policies. Considering after thirteen years, the world has not faced a major attack on the same scale as those witnessed in 2001; counterterrorism policies by some have been argued to be a phenomenal success. This article will focus on counterterrorism policies by the United States, positing the argument that the success of these policies cannot be determined by the mere lack of terrorist attacks, but by the effects of these policies
Insurgents in motion: Counterinsurgency and insurgency relocation in IraqUNU-MERIT
http://youtu.be/zqcM1jE_BoY
Recent studies in general are positive regarding the effectiveness of US counterinsurgency programs in Iraq. The right mix of coercion, ethnic strategy, and public goods provision, it is argued, makes Iraqis less likely to rebel against the US army and the Iraqi government, thus reducing insurgent violence. In fact, the number of insurgent attacks dramatically declined shortly after the change in the counterinsurgency strategy in 2007. How robust is the positive finding? A common assumption behind previous analyses is that insurgent attacks have a strong local root and is unlikely to be reproduced in other areas. Violation of this spatial independence assumption, however, can potentially bias towards the positive result. Based on the novel spatial dynamic panel data (SDPD) model, my analysis shows that spatial dependence should be addressed and cannot be assumed away. Results based on the new model also reveal that, conditional upon other strategies, the effects of a counterinsurgency strategy vary considerably both in magnitude and direction, suggesting that some policy mixes could be counterproductive. Policy makers seeking to adopt similar strategies in Afghanistan should take the relocation into account in their policy evaluations.
Since the terrorist attacks of September 11, 2001 debate has circulated around the nature and success of counterterrorism policies. Considering after thirteen years, the world has not faced a major attack on the same scale as those witnessed in 2001; counterterrorism policies by some have been argued to be a phenomenal success. This article will focus on counterterrorism policies by the United States, positing the argument that the success of these policies cannot be determined by the mere lack of terrorist attacks, but by the effects of these policies
Insurgents in motion: Counterinsurgency and insurgency relocation in IraqUNU-MERIT
http://youtu.be/zqcM1jE_BoY
Recent studies in general are positive regarding the effectiveness of US counterinsurgency programs in Iraq. The right mix of coercion, ethnic strategy, and public goods provision, it is argued, makes Iraqis less likely to rebel against the US army and the Iraqi government, thus reducing insurgent violence. In fact, the number of insurgent attacks dramatically declined shortly after the change in the counterinsurgency strategy in 2007. How robust is the positive finding? A common assumption behind previous analyses is that insurgent attacks have a strong local root and is unlikely to be reproduced in other areas. Violation of this spatial independence assumption, however, can potentially bias towards the positive result. Based on the novel spatial dynamic panel data (SDPD) model, my analysis shows that spatial dependence should be addressed and cannot be assumed away. Results based on the new model also reveal that, conditional upon other strategies, the effects of a counterinsurgency strategy vary considerably both in magnitude and direction, suggesting that some policy mixes could be counterproductive. Policy makers seeking to adopt similar strategies in Afghanistan should take the relocation into account in their policy evaluations.
Mohan Guruswamy's presentation at a recent seminar on how to respond to another state sponsored terrorist attack from Pakistan. A tit for tat reaction may not dissuade Pakistan from more of it, but the GOI owes it to the Indian public to get satisfaction. Turning the other cheek is not policy.
Many of the world's poorest citizens live in peripheral spaces their states have chosen
not to control. Leaving these spaces ungoverned poses challenges for development, global
terrorism, and conflict. Can the international community induce countries to invest in
controlling their territory? I consider the Bush Administration's foreign policy, which,
following the September 11th attacks, demanded countries take active steps to reduce
terrorist safe havens or risk a US invasion. Drawing upon recent work on the determinants
of government control, I develop a difference-in-difference strategy to test for evidence
of government expansions and implement this test using subnational conflict data from Africa. Across a wide range of specifications and measures, I consistently find precise
estimates suggesting African states did not engage in these expansions. The results suggest that broad-based deterrence is an ineffective policy strategy to reduce ungoverned spaces.
Statement of Erroll G. Southers before the US House of Representatives Commit...Elsevier
Counterterrorism expert and Elsevier Author Erroll Southers testifies at the Congressional Homeland Security Committee's first hearing on the Boston bombings.
In this Microsoft word file you can have a complete file of what is terrorism what are its various types and what are its impacts and also can have recommendations off how to control it and in last there are also a brief conclusion about the complete document
Mohan Guruswamy's presentation at a recent seminar on how to respond to another state sponsored terrorist attack from Pakistan. A tit for tat reaction may not dissuade Pakistan from more of it, but the GOI owes it to the Indian public to get satisfaction. Turning the other cheek is not policy.
Many of the world's poorest citizens live in peripheral spaces their states have chosen
not to control. Leaving these spaces ungoverned poses challenges for development, global
terrorism, and conflict. Can the international community induce countries to invest in
controlling their territory? I consider the Bush Administration's foreign policy, which,
following the September 11th attacks, demanded countries take active steps to reduce
terrorist safe havens or risk a US invasion. Drawing upon recent work on the determinants
of government control, I develop a difference-in-difference strategy to test for evidence
of government expansions and implement this test using subnational conflict data from Africa. Across a wide range of specifications and measures, I consistently find precise
estimates suggesting African states did not engage in these expansions. The results suggest that broad-based deterrence is an ineffective policy strategy to reduce ungoverned spaces.
Statement of Erroll G. Southers before the US House of Representatives Commit...Elsevier
Counterterrorism expert and Elsevier Author Erroll Southers testifies at the Congressional Homeland Security Committee's first hearing on the Boston bombings.
In this Microsoft word file you can have a complete file of what is terrorism what are its various types and what are its impacts and also can have recommendations off how to control it and in last there are also a brief conclusion about the complete document
Nos ajude a escolher o Antenado do ANO. Leia os perfis e vote pelo email: antenados@ramacrisna.org.br
Conheça o projeto: www.projetoantenados.blogspot.com
Nos ajude a escolher o Antenado do ANO. Leia os perfis e vote pelo email: antenados@ramacrisna.org.br
Conheça o projeto: www.projetoantenados.blogspot.com
Smart society in Smart cities: lezioni per la PA e per i professionisti dell'...Marco Dal Pozzo
La cultura digitale dve andare di pari passo con quella teconologica. Questo significa intercettare i nuovi processi di comunicazione e saperne gestire i flussi e gli strumenti. Una nuova responsabilità per chi all'interno della PA lavora nella comunicazione e per chi nel mondo dell'informazione approfondisce i temi della nuova società e della comunicazione pubblica.
Forum PA, Roma 24 Maggio 2016
Cyber Weapons Proliferation
Name:
Date: 03-30-2021
TOPIC: CYBER WEAPON PROLIFERATION
Currently there is no widely accepted definition on the concept of cyber weapon, but it can be described as a tool which has been modified for the purpose of carrying out malicious threats or attacks in the cyber space.
The use of Cyber space as a weapon is gradually gaining recognition, to the extent that it is currently been considered a Weapon of Mass Destruction.
In the US. For Instance, the Department of Homeland Security is tasked with the responsibility of protecting its citizens against any form of threat including cyber-attacks. The US has traditionally been perceived to be the world's most dominant cyber force in terms of this kind. Both their capabilities (defensive and offensive) have been actively developed over the last two decades, and appear to be superior to others. In order to strengthen U.S. space defense, the United States Cyber Command (US CYBER) was established in 2010 to ensure freedom of action in cyberspace for the US government and its allies, but prevent adversaries from doing the same.
The three service elements that comprise USCYBER are the Army Cybercom, the Air Force Cybercom, and the Fleet Cybercom. In August 2017 the United States Cyber Command was elevated to the status of a Unified Combatant Command. The National Defense Strategy for 2018 stated that the US government will prioritize the integration of cyber capabilities into the full spectrum of military operations.[footnoteRef:1] [1: Cristian Barbieri, Jean-Pierre Darnis & Carolina Polito
“Non-proliferation Regime for Cyber Weapons. A Tentative Study” http://www.iai.it/sites/default/files/iai1803.pdf accessed March 30th, 2021]
The proliferations in weaponisation of cyber space by terrorist groups to carry out destructive threats have necessitated the need for in depth analysis on the regulation of the use of cyber space.
In conclusion, although clearly resembling weapons, others say cyberspace might have a different potential to do great harm without actually inflicting financial or human loss, often cyber weapons may be used as less dangerous "conventional" weapons and canolays.
However, due to the fast pace of cyber-related technological developments, leadership changes, senior defense officials must be up to speed with how these technologies impact national security and defense mechanisms so they can have updated or revisions to the current laws regulating cyber usage.
Furthermore, it is suggested that in other to combat the use of cyber space as a weapon, one has to disable the source of the threat in order to neutralize the "cyber weapon" used to attack a target, thereby rendering them ineffective.
In my opinion, limited reliance on cyber space is recommended to effectively combat cyber space terrorism.
Running head: TERRORISM
TERRORISM
TER ...
CJ513Unit 3 DQTopic #1The Definition of CyberterrorismDiVinaOconner450
CJ513
Unit 3 DQ
Topic #1
The Definition of Cyberterrorism
Discuss the current debate surrounding the definition of cyberterrorism. Why is there no common definition? What are some of the challenges associated with establishing a common definition? Provide examples of two competing definitions of cyberterrorism from different sources and discuss the differences between the definitions. What are the implications of these differences? Be sure to properly cite and reference sources used
Topic #1: Student Response #1(Respond to Joe)
Joe Cacioppo
Good evening class,
This was an interesting topic to research and had not given much thought to the nuances in defining and making a distinction between cyberterrorism and cybercrime. I was also surprised to hear there was not a common definition of cyberterrorism. I reviewed the United States Department of Justice Federal Bureau of Investigation website and found an article written by Tafoya (2011), who defined cyberterrorism as “the intimidation of civilian enterprise through the use of high technology to bring about political, religious, or ideological aims, actions that result in disabling or deleting critical infrastructure data or information.”
An alternate definition according to the Center for Strategic and International Studies (CSIS) defined cyberterrorism as, ““the use of computer network tools to shut down critical national infrastructures (e.g., energy, transportation, government operations) or to coerce or intimidate a government or civilian population.” (Tafoya, 2011.)
In comparing the two different definitions given, the similarities include the use of technology to coerce or intimidate to produce a change. The differences in the FBI definition have a better defined group of targeted populations for change, for example political, religious or ideological change. I have not seen an implication between the differences in the two given definitions. The end result, and the methods for cyberterrorism is similar.
Additional research on cyberterrorism described the activity as any premeditated, politically motivated attack against information systems, programs and data that results in violence against noncombatant targets by subnational groups of clandestine agents, (Hanna, et. al., nd.)
References:
Hanna, H.T., Ferguson, K, Rosencrance, L. (nd.) Techtarget network. Cyberterrorism. https://searchsecurity.techtarget.com/definition/cyberterrorism
Tafoya, W.L. 2011. The United States Department of Justice. Cyber Terror. https://leb.fbi.gov/articles/featured-articles/cyber-terror
Topic #1: Student Response #2(Respond to Elizabeth)
Elizabeth Stuart
Cyberterrorism, while understood by some on a basic level, remains an elusive concept to many. There is no agreed upon definition in academia or government for this term. Due to this, it can be difficult to pinpoint what exactly constitutes cyberterrorism. In their article, Klein (2018) utilized a definition by Denning (2000), who described cyber ...
The psychological effects of cyber terrorismMichael L. Gross.docxoreo10
The psychological effects of cyber terrorism
Michael L. Gross , Daphna Canetti and Dana R. Vashdi
ABSTRACT
When ordinary citizens think of cyber threats, most are probably worried about their passwords
and banking details, not a terrorist attack. The thought of a shooting in a mall or a bombing at an
airport is probably more frightening than a cyber breach. Yet terrorists aim for mental as well as
physical destruction, and our research has found that, depending on who the attackers and the
victims are, the psychological effects of cyber threats can rival those of traditional terrorism.
KEYWORDS
Cyber security; cyber
terrorism
Cyber aggression has become a daily fact of life in the
21st century, yet for most people it’s still only a reality
in the form of cyber crime – hackers targeting financial
information or other personal details. Politically moti-
vated attacks might threaten them as well, but they
tend to be the concern of governments and corpora-
tions rather than ordinary citizens. The thought of a
terrorist shooting in a mall or bombing in an airport
probably seems far more frightening to the average
person than Russian hackers disrupting government
networks in Estonia or Anonymous breaking into the
police department of Ferguson, Missouri. Cyber terror-
ists, after all, have yet to actually kill or injure anyone.
Yet our research has found this perception of cyber
aggression might not be entirely accurate. The aim of
terrorism, after all, is not just physical destruction, and
depending on who the attackers and the victims are,
the psychological effects of cyber terrorism can be just
as powerful as the real thing.
Defining cyber terrorism
People face cyber aggression on an almost daily basis.
Hackers appropriate, erase, or ransom data, defraud
bank customers, steal identities, or plant malevolent
viruses. In many cases, hackers are criminals out for
pecuniary gain. But sometimes their motives are poli-
tical. Some are “hacktivists,” or cyber activist groups,
like Anonymous, others are terror groups like Hamas
or Islamic State, and still others are agents of national
states like Iran, North Korea, or Russia. They are not
usually after money but pursue a political agenda to
foment for social change, gain political concessions, or
cripple an enemy. Sometimes their means are peaceful,
but other times they are vicious and violent. The lines
often blur. Anonymous will hack the Ferguson police
department just as it will initiate an “electronic
Holocaust” against Israel in support of the Palestinian
cause (Rogers 2014). Islamic activists will use the
Internet not only to recruit members and raise funds
for social welfare projects but also to steal money for
terrorist activities or disseminate information to stoke
fear and demoralize a civilian population. States will
pursue online espionage but also wreak havoc by crash-
ing multiple systems – as did the Russians, allegedly, in
Estonia in 2007, with mass denial-of-service attacks on
gove ...
10Liberty University School of Graduate CounterterroriBenitoSumpter862
10
Liberty University
School of Graduate
Counterterrorism
Submitted to Dean Curry
Course: PPOG540
Abdirahim M Muhumed
December 11, 2021
Contents
Counterterrorism 1
Definition of terms 1
Terrorism 1
Counterterrorism 2
Attacks 2
Malicious 2
Suspect 2
Why counterterrorism? 2
The 9/11 attacks 3
How counterterrorism is addressed 4
Effects of counterterrorism regulations 6
Conclusion and recommendations 8
References 10
Counterterrorism
Over numerous years, terrorism has continued to present severe threats to the security and peace of nations, which affects the overall population's rights and socio-economic development. It seeks to undermine the values that unite a given country. Ultimately, the global threat is a persistent act. It does not have any border, religion, or nationality. The international community must come together to tackle the challenge by implementing various ways.[footnoteRef:1] For most law enforcement agencies, policymakers, and the population, the topic of terrorism threats and the means to fight it is an essential concern. The government's responsibility is to protect the people within their jurisdiction from any attacks. [1: Huq, Aziz Z. "Community-led counterterrorism." Studies in Conflict & Terrorism 40.12 (2017): 1040]
The overall strategy and way to fight terrorism is counterterrorism. After extensive research, while utilizing the library resources, I learned that counterterrorism monitors terrorists identify individuals who may be radicalized, provides at-risk people, and builds additional security.[footnoteRef:2] It is a strategy that contributes to safeguarding the security of a country through government approaches, collaboration, and coordinating working arrangements. [2: Silke, A., 2018. The study of terrorism and counterterrorism. In Routledge handbook of terrorism and counterterrorism, 1.]
Definition of terms
A few terms will repeatedly appear throughout the study, thus the need to define them. This includes:
Terrorism is the use of intimidation and violence unlawfully, mainly in the quest for political aims against a civilian.[footnoteRef:3] [3: Silke, A., 2018. The study of terrorism and counterterrorism, 1]
Counterterrorism- refers to measures designed to prevent or combat terrorism.
Attacks are the act of taking an aggressive military action against n civilian or enemy forces using armed forces or weapons [footnoteRef:4] [4: Huq, Aziz Z. "Community-led counterterrorism." (2017): 1042]
Malicious- intended or intending to harm.
Suspect- Having an impression or idea of the presence, existence, or truth of a given something without having much proof. Why counterterrorism?
Counterterrorism is an integral and exciting topic to explore in relation to America's foreign policy. It is efforts against terrorism to engender attempts or conditions that terrorist organizations could engage in when carrying their malicious activities. From research, the essential part of the t ...
10Liberty University School of Graduate CounterterroriSantosConleyha
10
Liberty University
School of Graduate
Counterterrorism
Submitted to Dean Curry
Course: PPOG540
Abdirahim M Muhumed
December 11, 2021
Contents
Counterterrorism 1
Definition of terms 1
Terrorism 1
Counterterrorism 2
Attacks 2
Malicious 2
Suspect 2
Why counterterrorism? 2
The 9/11 attacks 3
How counterterrorism is addressed 4
Effects of counterterrorism regulations 6
Conclusion and recommendations 8
References 10
Counterterrorism
Over numerous years, terrorism has continued to present severe threats to the security and peace of nations, which affects the overall population's rights and socio-economic development. It seeks to undermine the values that unite a given country. Ultimately, the global threat is a persistent act. It does not have any border, religion, or nationality. The international community must come together to tackle the challenge by implementing various ways.[footnoteRef:1] For most law enforcement agencies, policymakers, and the population, the topic of terrorism threats and the means to fight it is an essential concern. The government's responsibility is to protect the people within their jurisdiction from any attacks. [1: Huq, Aziz Z. "Community-led counterterrorism." Studies in Conflict & Terrorism 40.12 (2017): 1040]
The overall strategy and way to fight terrorism is counterterrorism. After extensive research, while utilizing the library resources, I learned that counterterrorism monitors terrorists identify individuals who may be radicalized, provides at-risk people, and builds additional security.[footnoteRef:2] It is a strategy that contributes to safeguarding the security of a country through government approaches, collaboration, and coordinating working arrangements. [2: Silke, A., 2018. The study of terrorism and counterterrorism. In Routledge handbook of terrorism and counterterrorism, 1.]
Definition of terms
A few terms will repeatedly appear throughout the study, thus the need to define them. This includes:
Terrorism is the use of intimidation and violence unlawfully, mainly in the quest for political aims against a civilian.[footnoteRef:3] [3: Silke, A., 2018. The study of terrorism and counterterrorism, 1]
Counterterrorism- refers to measures designed to prevent or combat terrorism.
Attacks are the act of taking an aggressive military action against n civilian or enemy forces using armed forces or weapons [footnoteRef:4] [4: Huq, Aziz Z. "Community-led counterterrorism." (2017): 1042]
Malicious- intended or intending to harm.
Suspect- Having an impression or idea of the presence, existence, or truth of a given something without having much proof. Why counterterrorism?
Counterterrorism is an integral and exciting topic to explore in relation to America's foreign policy. It is efforts against terrorism to engender attempts or conditions that terrorist organizations could engage in when carrying their malicious activities. From research, the essential part of the t ...
Predictive analysis of terrorist activities in Thailand's Southern provinces:...IJECEIAES
Terrorist activities have been on the rise globally, with Thailand experiencing significant challenges, particularly in its three southern border provinces. This study offers a comprehensive analysis aiming to predict forthcoming terrorist events in these provinces. We employed historical data, categorized into nine groups based on military expert recommendations, to train our prediction model. This research tested the prediction capabilities of various methodologies, including decision trees, naïve Bayesian learning techniques, and deep learning artificial neural networks. Notably, the deep neural network emerged as the superior predictive tool, achieving an impressive accuracy of 98.21% and a root mean square error (RMSE) of 0.59%. The primary anticipated events include bombings, shootings, assaults, and acts of vandalism. Our findings also revealed that Pattani Province was the most affected, accounting for 45% of incidents. Specific districts, such as Panare and Yarang, exhibited high crime rates of 40% and 36.84%, respectively. Yala Province, particularly Bannang Sata District, was identified as the hotspot for shooting incidents, with a rate of 34%.
Running head ASSIGNMENT 4ASSIGNMENT 4Assignment 4 Da.docxjoellemurphey
Running head: ASSIGNMENT 4
ASSIGNMENT 4
Assignment 4: Data Collection
Student Name
Affiliate Institution
Evidence-based researched data to indicate there is a problem
Terrorism is considered a historical and major problem for the U.S. Since 2001, the significance of the problem has increased. Therefore, several organizations and facilities collect and store terrorism data for events like attempted and occurred activities. The main data source for terrorism activities is the U.S. Department of Homeland Security. The mandate of this arm of government is to protect Americans both in locally and internationally against crime activities but terrorism seems the greatest enemy of American citizen wherever they are in the world.
Numerous and most useful data for terrorism is found from the following federal agency and private databases:
· The National Security Agency (NSA)
· Federal Bureau of Investigation (FBI)
· National Consortium for the Study of Terrorism and Response to Terrorism (NCSTRT) and
· Global Terrorism Database (GTD). (FBI, 2014; GTD, 2014)
Information from the above databases are analyzed to present diverse quantitative and qualitative terrorism data that cover several years including life threats to the U.S. soil. According to these databases, terrorism is an old problem and continues to intensify due to availability of uninterrupted new technology as well as growing financial power of their organizations. The Federal Agencies data bases provide information on terrorism activities and information on several strategies that have been used in the past and are currently used to curb the vice (FBI, 2014).
The other terrorist’s data sources are the media agencies. News agencies such as online newspapers and broadcasting corporations provide terrorism data as it occurs. Although these agencies might not provide analyzed data, their role is to increase public awareness about terrorism occurrences and development.
References
Federal Bureau of Investigation (2014). Crime Statistics. Retrieved on May 22, 2015 from http://www.fbi.gov/stats-services/crimestats
Global Terrorism Database (2014). Overview of the GTD. Retrieved on May 22, 2015 from http://www.start.umd.edu/gtd/about/
2
Running Head: Terrorism Stakeholders
Terrorism
Terrorism Stakeholders
Student name
Affiliate Institution
Terrorism
Modern day terrorism has caused sufficient harm to the society both in the political, social and the economic sectors. External and internal forces have influenced terrorism activities within the governments therefore increasing the intensity of the terrorism acts (Chong, 2007). After the terror attack that occurred in the U.S on the 9/11, 2001, it was realised that there have been low information sharing amongst the agencies that conducts the security surveillance of the country. Various institutions and agencies directly or indirectly are linked to the terrorist attack that takes p ...
US POLICIES ON TWO TRANSNATIONAL CRIMES, ILLICIT DRUG .docxdickonsondorris
US POLICIES ON TWO TRANSNATIONAL CRIMES, ILLICIT DRUG
TRAFFICKING AND CYBER-LAUNDERING, WILL NOT SECURE THE
HOMELAND FROM TERRORIST THREATS
A Master Thesis
Submitted to the Faculty
of
American Public University
by
First Name Last Name
In Partial Fulfillment of the
Requirements for the Degree
of
Master of Arts
April 2012
American Public University
Charles Town, WV
1
Introduction and Purpose Statement
The threats to America that are imposed from transnational crimes are constantly changing.
The threats may originate from other nations throughout the world; but, the impacts throughout
America is surreal. The US Government fight against transnational crimes are nothing less than
intricate. US interests abroad are impacted by these threatening networks. Weapons trafficking,
intellectual property theft, cybercrime, human smuggling, trafficking in persons, and illicit drug
trafficking contribute to other crimes that evolves around these transnational crimes. The bottom
line is that the threats created by these crimes are not isolated to one specific nation or a specific
region in the world. The US Government policies that are designed to combat transnational
crimes must address both present-day threats and potential future threats.
The purpose of this paper is to explore US Government policies targeting illicit drug
trafficking and cyber-laundering while identifying vulnerabilities within the policies (if any) and
their impact on threats from terrorist organizations. Transnational crime, narcotics, and terrorism
financing are not geographical concerns. All three can be linked specifically by having potential
effect across national borders. Transnational Organized Crime (TOC) has established a
significant and increasing threat to national and international security, with dire implications for
public safety, public health, democratic institutions, and economic stability across the globe
(Finckenauer 2006, 124). The US Government have many Presidential Directives (PD) and
policies that target these areas, but are they really having an impact? Without a shadow of a
doubt, drug trafficking has resulted in funding that has supported terrorism and in some cases
such as the Madrid bombing, drugs were being utilized as the currency. The same scenario can
happen in any small or large city in America. US Government policies must be able to
compliment or supplement other Nations policies in the fight against transnational crime.
2
Because of varies religious beliefs and political views of western nations, the tasking will be
equivalent to finding a cotton ball in the field of snow.
Cybercrime is such a lucrative criminal adventure because anyone can be anyone and
anywhere in a digital environment. The utilization of electronic funding transactions
domestically and or internationally can create difficult detective efforts for an ...
How does Terrorism Effect on Business and Relation Between Countriesijtsrd
The international business or IB is threatened by the indirect and direct effects of terrorism. Since the moment governments have tightened the safety of public sites, the various businesses have turned into exponential attractive targets for terrorist attacks, with vital implications for the performance and operations of the companies that are multinational in nature. Though, substantial studies have been done in different fields about terrorism, less scholarly research has been done on the various challenges which it inflicts upon international business as well as how to address terrorism as a problem. Through this particular article we would conceptualize the terrorism concerned with international business. The background on effects and dimensions of terrorism as well as developing theoretical grounding for researching terrorism by sketching on literature provided by international business, political science, economics and different sectors; shall be provided by us. Once discussion on findings from review of the literature is done, a comprehensive program for subsequent research concerning the connection between international business and terrorism is offered by us. The program that we offer emphasizes on the effects of organizational preparedness, terrorism, company performance and its strategy, global distribution and global supply channels, as well as the issues pertaining human resource. The review that we render, aid in establishing a baseline that further assists in empirical research in the future. This consistent with research in an early stage, international business scholars get encouragement to offer perspectives as well as effective solution that are useful and throw required light on the various aspects of terrorism and also aid in reducing its devastating effects for multinational firms and international business.. Prof. Sidharth S. Raju | Pooja"How does Terrorism Effect on Business and Relation Between Countries" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-6 , October 2017, URL: http://www.ijtsrd.com/papers/ijtsrd4598.pdf http://www.ijtsrd.com/management/international-business-issues/4598/how-does-terrorism-effect-on-business-and-relation--between-countries/prof-sidharth-s-raju
How does Terrorism Effect on Business and Relation Between Countries
E059
1. Improving the Classification of Terrorist Attacks
A Study on Data Pre-processing for Mining the Global Terrorism Database
José V. Pagán
Electrical & Computer Engineering and Computer Science Department
Polytechnic University of Puerto Rico
San Juan, Puerto Rico
e-mail: jvpagan@msn.com
Abstract—The objective of this paper is to analyze different
data preprocessing techniques for mining the Global
Terrorism Database to improve the classification of terrorist
attacks by perpetrator in Iraq. Four methods for dealing with
missing values (Case Deletion, Mean Imputation, Median
Imputation and KNN imputation), three discretization
methods (1R, Entropy and Equal Width), and three different
classifiers (Linear Discriminant Analysis, K-Nearest Neighbor
and Recursive Partitioning) are evaluated using ten-fold cross-
validation estimates of the misclassification error. The study
concludes (i) that data preprocessing can significantly reduce
the classification error rate for this dataset, and (ii) that adding
Global Positioning System coordinates for the location of the
incidents can further reduce the classification error rate.
Keywords- classification; data mining; data preprocessing;
terrorism.
I. INTRODUCTION
Data is usually far from perfect. A focus on improving
the quality of data typically improves the quality of the
resulting analysis. Because data quality problems cannot
always be prevented, data mining focuses on detection and
correction of data problems and on the use of algorithms that
can tolerate poor data quality [1].
In this paper, we analyze how different data
preprocessing techniques can improve the classification of
terrorist attacks by perpetrator in Iraq. Section II discusses
the evolution of terrorism, its causes, and its exponential
growth in Iraq over the last 30 years. Section III discusses
the different techniques and tools available for analyzing
terrorism data, including the Global Terrorism Database
(GTD) and related tools developed by the Human-Computer
Interaction Lab and START at the University of Maryland.
Section IV discusses data preprocessing techniques for
treating outliers and missing values, and a classification of
various discretization techniques. Section V describes the
experimental methodology used and the results. Finally,
section VI provides a conclusion and a discussion of the
results.
II. TERRORISM
Over the last 20 years, terrorism has evolved, expanded
and become a significant influencing factor in international
politics. The most recent definition of terrorism by the
United States State Department, Department of Defense, and
Central Intelligence Agency, defines terrorism as
“premeditated, politically motivated violence perpetrated
against non-combat targets by sub-national groups or
clandestine agents, usually intended to influence an
audience” [2].
In the past, terrorism events were mostly assassinations
intended to influence political changes. Today, terrorist
events are choreographed spectacles that reverberate in
seconds around the globe, uniting extremists and shocking
public audiences. Technological advances in media
coverage and globalization have given terrorist events new
added meaning, urgency and complexity. Consequently,
Terrorism has become less predictable, its motivations less
understandable and its logic of violence less clear and
restrained [3].
Probably the most contested cause of terrorism is an
aggrieved group resorting to violence for nationalist or
separatist reasons. Depending on one's point of view, this
violence can be considered as resistance against an (external)
oppressor. Colonized states nationalism movements
commonly turn to terrorism, it being "the resort of an
extremist faction of this broader movement" within an ethnic
minority [4]. To generalize it further, ethnic conflict arises
from a "complex combination" of class, inequality, political
opportunity, mobilization resources and "ethnic strength” [5,
6].
According to David Rothkopf, an intelligence and
emerging markets advisor who served as Senior Trade
Official in the Clinton Administration, the leading cause for
political tension in the world today is the increasing relative
inequality between social classes. Globalization has created
a global super-class of the wealthiest and most elite with the
most power. They run governments, the largest
corporations, the powerhouses of international finance, the
media, world religions, and, from the shadows, the world's
most dangerous criminal and terrorist organizations. These
super-class members have more in common with one another
than with their own countrymen. They have globalized more
rapidly than any other group and control globalization.
Nationalist critics have accused them of feeding the growing
economic and social inequity that divides the world [7].
Rothkopf argues that the history of mankind is one of
elites rising up, overreaching, and being brought back down.
They have been brought back down in revolutions and
2. through (government) innovation. He claims that today there
are many signs of backlash against these relative inequalities
in the world, as evidenced by the rise to power of rulers like
Hugo Chavez in Venezuela, Mahmoud Ahmadinejadseen in
Iraq, and Vladimir Putin in Russia [7].
Lee argues that geopolitics plays an important role in
terrorism. For example, following the demise of the Soviet
Union in 1991, many of the Marxist-Leninist terrorist attacks
in Europe from the 1970s and early 1980s subsided. Today,
the Marxist-Leninist terrorists of the 1970‟s have been
replaced with more religiously oriented jihad-style groups
[8].
This study focuses on terrorism activity in Iraq. Figure 1
below shows a logarithmic chart with the historical annual
number of terrorist attacks in Iraq and the world since 1975
[9].
Figure 1. Historical annual number of terrorist attacks in Iraq.
As evidenced by the chart above, the wars of 1991 and
2003 have caused exponential growth in terrorist activity in
Iraq. The geopolitics of the region, the large inequities in the
country and the current US military occupation make Iraq a
“hotbed” for terrorism.
III. ANALYZING TERRORISM DATA
Prior to 1990, terrorism analysis was qualitative and used
simple summary statistics to show trends in a particular
variable over time. In 1999, Enders and Sandler used time-
series number of domestic terrorist incidents to show that the
end of the cold war resulted in a decrease in transnational
terrorism [10]. They later used a linear model and a threshold
autoregressive model to search for correlations between
terrorism incidents and significant policy changes [11].
In 1996, O'Brien described the relationship between
foreign policy crisis outcomes and terrorist incidents using
Box - Jenkins time-series methods [12]. In 2002, Major used
game theory to develop a probability distribution for
insurance losses related to terrorism [13]. In 2003, Sandler
and Arce used game theory to describe the interaction
between terrorist groups and targeted states as a strategic
game between rational actors. They concluded that tourists,
civilians, and businesses are most likely targets because they
have the least deterrence capability [14].
According to Guo, these modeling approaches are limited
in their ability to formulate and test a valid hypothesis. They
build on rigorous statistical or mathematical models, but
provide limited understanding of the causes, development,
and diffusion of terrorism activities. Moreover, terrorism
data is often incomplete or inaccurate and only represents the
outcome, not the process [15].
To counter these limitations, new approaches for visual
and computational analysis have been developed for the
exploration of terrorism data. These approaches can reveal
unknown trends or regularities, prompt new thoughts, and
help the analyst gain insights to formulate better hypotheses
and models.
For example, Villanova developed a visual analytical
system that focuses on depicting one of the most
fundamental concepts in investigative analysis, the five W‟s
(who, what, where, when, and why) [16]. With this
approach, an investigator can interactively explore terrorist
activities efficiently and discover reasons of attacks (why) by
identifying patterns temporally (when), geo-spatially
(where), between multiple terrorist groups (who), and across
different methods or modes of attacks (what).
Similarly, Ziemkiewicz developed an interconnected
visual analysis tool that provides three interconnected views
of the Global Terrorism Database (GTD) to support the
investigative process [17]. Figure 2 below shows one of the
views from this tool used by investigators to explore the data
in an abstract way by examining correlations across multiple
dimensions.
Figure 2. Visual analysis of correlations across data dimensions. [17]
1
10
100
1000
10000
1975
1977
1979
1981
1983
1985
1987
1989
1991
1994
1996
1998
2000
2002
2004
2006
NumberofTerroristAttacks
Iraq
World
3. The ribbons between categorical dimensions in Figure 2
show the proportion of cases from one category that fall
under a category from another dimension. The visual
analysis above highlights the high rate of incidents in Latin
America during the early 1980s, and how those incidents
break down in terms of type and target.
A. The Global Terrorism Database
The GTD is an open-source database including
information on terrorist events around the world from 1970
through 2007. It includes systematic data on more than
80,000 domestic as well as transnational and international
terrorist incidents that have occurred during this time period.
For each GTD incident, information is available on the date
and location of the incident, the weapons used and nature of
the target, the number of casualties, and—when
identifiable—the group or individual responsible. The GTD
is the most comprehensive unclassified data base on terrorist
events in the world. It includes information on more than
27,000 bombings, 12,000 assassinations, and 2,900
kidnappings since 1970, with information on at least 45
variables for each case. More recent incidents include
information on more than 120 variables. The database is
supervised by an advisory panel of 12 terrorism research
experts. These experts have collected incident data from
over 3,500,000 news articles and 25,000 news sources from
1998 to 2007 alone.
The Human-Computer Interaction Lab and START, both
at the University of Maryland, have developed an
exploratory interactive visual analysis tool for the GTD
called Data Rivers. This tool allows users to investigate
temporal trends in terrorism in the Global Terrorism
Database (GTD) by aggregating important variables from the
database and visualizing them as a comprehensible stack
chart. Five different stack charts can be selected: Countries
Attacked, Regions Attacked, Target Nationalities, Types of
Targets and Types of Weapons. A stack chart analyzes
every incident in the GTD, both domestic and international,
from 1970 to 2007 (over 85,000 discrete events) and
aggregates them according to the selection of the user. A
unique layer is created for each data stream, with each
stream reflecting a value of the variable being displayed. The
thickness of each layer represents its frequency in the
database.
Figure 3 below shows the GTD Data Rivers default chart
(Countries Attacked) with Iraq highlighted in yellow.
Figure 3. Visual analysis of terrorism temporal trends using Data Rivers.
The chart creates a layer for every country in the GTD
that has experienced a terrorist attack at some point since
1970. Thick layers represent countries that have had many
attacks, whereas thin layers signify countries that had fewer
attacks. One of the benefits of stack charts is that aggregate
trends emerge as layers stack up like a histogram [18].
B. Missing Data in the Global Terrorism Database
One of the main problems of the GTD is that it is missing
a large amount of data. Figure 4 below shows a distribution
of missing values in the GTD by variable. Missing values
are shown as white space.
Figure 4. Global Terrorism Database distribution of missing values.
As may be seen from the chart above, 42.7% of the
values in the GTD are missing, while 74% of the features
and 100% of the instances have missing values. In addition,
all data for the year 1993 is missing due to an office move.
Since the database includes incidents covered by the media,
the perpetrator remains unidentified in 39% of the terrorist
attacks. Without information concerning the perpetrator of
the event, it is difficult to accurately classify the incident as
terrorism [8].
IV. DATA PREPROCESSING
In this study, we pre-process raw data from the GTD by
eliminating outliers, estimating missing values and
discretizing the data.
A. Eliminating Outliers
Data objects that are grossly different from or
inconsistent with the remaining set of data are called outliers.
Many data mining algorithms attempt to minimize the
4. influence of outliers or totally eliminate them. However,
such action can lead to the loss of important hidden
information [19].
There are several techniques available for identifying
outliers and smoothing noisy data, including clustering,
binning and regression. Clustering groups attribute values in
clusters and then detects and removes outliers; binning sorts
the attribute values and partitions them into bins; and
regression smoothes data by using regression functions.
Another technique is combined human computer interaction;
possible outliers are detected by the computer and checked
by a human [20].
B. Treating Missing Data
Missing data is one of the biggest challenges in statistical
analysis. Improper handling of missing values will distort
analysis. Until proven otherwise, the researcher must
assume that missing cases differ in analytically important
ways from cases were values are present. The problem with
missing data is the possibility that the remaining data set is
biased.
Several methods have been developed for dealing with
missing data, but some have drawbacks when applied to
classification tasks. In 1972, Chan and Dunn considered the
treatment of missing values in supervised classification using
the LDA classifier for two class problems [21]. Dixon
introduced the KNN imputation technique in 1979 for
dealing with missing values in supervised classification [22].
In 1995, Tresp also considered the missing value problem in
a supervised learning context for neural networks [23].
In 2004, Acuña analyzed the treatment of missing values
in supervised classification using the LDA and KNN
classifiers. According to Acuña, missing data rates of less
than 1% are generally considered trivial, rates of 1-5% are
manageable, and rates of 5-15% require handling with
sophisticated methods. Missing data rates of more than 15%
may severely impact any kind of interpretation [24].
In this study we use four methods to treat missing values:
Case Deletion, Mean Imputation, Median Imputation and K-
Nearest Neighbor Imputation.
Case Deletion (CD) consists of discarding all instances
(cases) with missing values for at least one feature. CD
should be applied only in cases in which data are missing
completely at random. It is usually used when the class label
is missing (when doing classification). CD is not effective
when the percent of missing values per attribute varies
considerably [20].
Mean Imputation (MI) consists of replacing the missing
data for a given feature (attribute) by the mean of all known
values of that attribute in the class where the instance with
missing attribute belongs. One of the drawbacks of mean
imputation is that replacing all missing records with a single
value will deflate the variance and artificially inflate the
significance statistical tests.
Median Imputation (MDI) consists of replacing the
missing data for a given feature with the median of all
known values of that attribute in the class where the instance
with the missing feature belongs. This method is the
recommended when the distribution of the values of a given
feature is skewed because it is not affected by the presence
of outliers.
KNN Imputation (KNNI) consists of imputing the
missing values of an instance considering a given number of
instances that are most similar to the instance of interest. The
similarity of two instances is determined using a distance
function.
C. Discretization Techniques
Discretization is a process that transforms quantitative
data into qualitative data to improve the learning process of
machine learning algorithms. Figure 5 below provides a
classification of various discretization methods [25].
Figure 5. Classification of discretization methods. [25]
Splitting methods start with an empty list of cut-points
and keep on adding new ones to the list by „splitting‟
intervals as the discretization progresses. Merging methods
start with the complete list of all the continuous values of the
feature as cut-points and remove some of them by „merging‟
intervals as the discretization progresses. Supervised
methods use the class information when selecting
discretization cut points, while unsupervised methods do not.
In this study, we use three discretization methods: 1R
discretization, Entropy discretization and Equal Width
discretization.
1R is a supervised discretization method using binning.
After sorting the data, the range of continuous values is
divided into a number of disjoint intervals and the
boundaries of those intervals is adjusted based on the class
labels associated with the values of the feature. The
adjustment of the boundary continues until the next values
belong to a class different to the majority class in the
adjacent interval.
Entropy methods find the best split so that the bins are as
pure as possible, i.e. the majority of the values in a bin have
the same class label. It finds the split with the maximum
information gain.
Equal Width discretization divides the range of each
feature into k intervals of equal size. This method is very
straight forward, but it allows outliers to dominate the
presentation and does not handle skewed data well [17].
5. V. EXPERIMENTAL METHODOLOGY
In this paper we carry out experiments to evaluate the
effect of using different missing value and discretization
methods on the misclassification error rate when classifying
terrorist attacks by perpetrator in Iraq. The methods used for
dealing with missing values are case deletion (CD), mean
imputation (MI), median imputation (MDI) and KNN
imputation (KNNI). The discretiztion methods used were
1R, Entropy and Equal Width. The classifiers considered
were Linear Discriminant Analysis (LDA), K-Nearest
Neighbor (KNN), and Recursive Partitioning (RPART).
Our study was carried out using the GTD database
provided by the START program from the University of
Maryland. The data set used for the study is a subset of the
GTD that includes terrorist attacks in Iraq from 1998 to
2007. This region was selected because it has become the
new “hotbed” of terrorist attacks in the world. Also, post-
1997 GTD records were selected because they use a slightly
modified definition of terrorism and include additional
information that identifies them as terrorist incidents.
The dataset was passed through a cleansing process to
minimize the number of imputations necessary. Irrelevant
attributes that do not add significance in the analysis
processes were eliminated. The attributes maintained for the
dataset were the date and city location of the incident, the
type of weapons used to commit the terrorist act, the number
of casualties, the amount of wounded victims, the type of
attack and the identified terrorist group responsible. The
dataset instances with missing terrorist group name
information were eliminated from the database. To eliminate
outliers, reduce noise and simplify the classification process,
we only included the top five terrorist groups shown on
Table I below.
TABLE I. TOP FIVE TERRORIST GROUPS IN IRAQ 1998-2007
Group Name No. of Incidents
Al-Qa`ida in Iraq 101
Al-Qa`ida 18
Ansar al-Islam 17
Islamic State of Iraq (ISI) 17
Tawhid and Jihad 16
Al-Qa`ida in Iraq 101
These five groups account for 169 instances or 60% of all
incidents with a known perpetrator in Iraq. The resulting
dataset has 1.5% of missing values, with 28.6% of the
features and 9.9% of the instances missing at least one value.
Once the data was cleansed, the four methods for treating
missing values and the three discretization techniques were
used to compute the ten-fold cross-validation estimates of the
misclassification error for the LDA, KNN and RPART
classifiers. All computations were run using the R functions
available at www.math.uprm.edu. The results are shown in
Table II below.
TABLE II. CROSS VALIDATION ERROR RATES FOR IRAQ DATASET
Missing Data Discretization LDA KNN RPART
CD None 45.03% 38.41% 36.49%
CD 1R 41.72% 38.41% 29.14%
CD Entropy Error
a
Error
a
Error
a
CD EW 44.37% 38.28% 35.70%
MI None 43.96% 40.24% 36.69%
MI 1R 42.90% 37.63% 28.70%
MI Entropy Error
a
Error
a
Error
a
MI EW 40.95% 38.88% 37.75%
MDI None 43.55% 40.24% 36.15%
MDI 1R 44.08% 37.69% 28.11%
MDI Entropy Error
a
Error
a
Error
a
MDI EW 41.12% 37.75% 35.15%
KNNI None 44.02% 40.24% 36.57%
KNNI 1R 44.73% 38.76% 28.99%
KNNI Entropy Error
a
Error
a
Error
a
KNNI EW 41.60% 38.46% 36.75%
a. Entropy is useless as it partitions variables into one bin.
As an additional test, we added the Global Positioning
System (GPS) coordinates (latitude and longitude) for the
location of the incidents to the dataset and ran the tests a
second time. The results are shown in Table III below.
TABLE III. CROSS VALIDATION ERROR RATES WITH GPS DATA
Missing Data Discretization LDA KNN RPART
CD None 39.30% 34.88% 32.40%
CD 1R 37.98% 34.88% 35.66%
CD Entropy Error
a
Error
a
Error
a
CD EW 40.54% 34.88% 31.86%
MI None 39.82% 39.88% 31.79%
MI 1R 42.32% 34.35% 23.51%
MI Entropy Error
a
Error
a
Error
a
MI EW 36.07% 32.68% 31.49%
MDI None 38.57% 39.88% 33.75%
MDI 1R 39.76% 37.08% 23.81%
MDI Entropy Error
a
Error
a
Error
a
MDI EW 33.39% 34.40% 35.12%
KNNI None 42.20% 39.88% 36.79%
KNNI 1R 43.81% 38.15% 29.76%
KNNI Entropy Error
a
Error
a
Error
a
KNNI EW 39.05% 38.57% 34.64%
a. Entropy is useless as it partitions variables into one bin.
6. VI. CONCLUSIONS AND DISCUSSION
From Table II, we can conclude that the lowest
classification error rate (28.11%) is obtained using MDI to
treat missing values, 1R discretization and the RPART
classifier. RPART provides the lowest classification error
rate in all tests because it provides various advantages for
working with this type of data. Among other things, it has
the ability to work with any type of predictive variable,
works well with missing data, makes automatic selection of
variables, is unaffected by transformations of the predictive
variables, and is robust in the presence of outliers. RPART
is a non-parametric classifier (i.e., it does not require
assumptions) and takes advantage of the relationships that
may exist among the predictive variables. We can therefore
conclude that RPART is a better classifier than LDA and
KNN for this problem, given the characteristics of the
dataset.
We can also conclude that 1R is a better discretization
method than Entropy and EW for this problem. 1R produces
the lowest classification error rate in all tests, which may be
explained by the fact that it is a supervised discretization
method (i.e., it uses class information when selecting
discretization cut points). EW discretization, on the other
hand, cannot be used reliably on this classification problem.
Although it reduced classification error rates for the LDA
and KNN classifiers, it actually increased the error rate for
the RPART classifier 50% of the time. This result may be
explained by the fact that EW is an unsupervised
discretization method which allows outliers to dominate the
presentation and does not handle skewed data well. Entropy
discretization is not useful for this problem because it
partitions variables in this dataset into one bin, making them
useless for classification purposes.
None of the methods used to treat missing values
consistently reduced classification error rates by themselves.
This erratic behavior may be explained by the fact that the
amount of missing values was only 1.5% of the dataset and
was concentrated in two variables. Nevertheless, the MDI
methodology provides a 1% improvement over CD in the
classification error rate when used with 1R discretization and
the RPART classifier.
From Table III we can conclude that adding GPS
coordinates for the location of the incidents reduces the
classification error rate by another 4.6%. This result may be
partly explained by the fact that some cities are not always
entered into the database with the same name. The GPS
coordinates allow classifiers to find stronger relationships
between the predictive variables. These relationships are best
illustrated by the RPART classification tree shown in Figure
6 below.
As may be seen from the tree, the year, number of
wounded, month and latitude of each event are the key
variables used by RPART to classify a terrorist group.
Different groups are active in spurts at particular times and
regions, with varying levels of violence characteristic of their
group.
Figure 6. RPART Classification Tree for Iraq GPS Dataset
None of the top five groups identified in Iraq shows
activity from 1998 to 2002. They all became active after the
U.S. invasion in 2003. Based on these findings, it appears
that terrorism in Iraq is the result of a broad and growing
insurgency whose extremist faction increasingly resorts to
violence.
We strongly recommend that the Global Terrorism
Database include GPS coordinates in the future to facilitate
the classification of terrorist groups.
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