Search results

This chapter explains how economic analysis can contribute to the delineation of the lone wolf’s opportunities and choices in a manner that allows operationally relevant advice to be contributed to the investigative process.

Using a risk-reward analytical framework we examine the lone wolf’s attack method opportunities and choices and identify those attack methods that would be chosen by lone wolves with different levels of risk aversion. We also use prospect theory as an alternative methodology for the determination of the lone wolf’s preference orderings over the available attack methods in a context where he references his actions against those of a predecessor whom he wishes to emulate.

We find that lone wolf terrorists with different levels of risk aversion can be expected to choose different attack methods or combinations of attack methods. More risk averse lone wolf terrorists will choose attack methods such as assassination. Less risk averse lone wolf terrorists will choose attack methods such as bombing, hostage-taking and unconventional attacks. Also, we find that lone wolf terrorists who reference their actions against ‘predecessor’ lone wolf terrorists will choose differently from among the available attack methods depending on which predecessor lone wolf is being referenced.

The analysis provides two different perspectives on terrorist choice but by no means exhausts the analytical alternatives. The analysis focuses on the fatalities and injuries inflicted whereas other perspectives might include different ‘payoffs’ series, including news or media coverage.

The chapter contributes an analysis of the order in which lone wolf terrorists with particular characteristics will choose from a set of available attack methods. During the course of our discussion we point out the consistency between the ‘rise’ of the lone wolf terrorist and the diseconomies to scale that are evident within the terrorism context. This presents the opportunity for new debates.

An investigation of parallels between homegrown, international, and domestic terrorism.

A comparative method is used to analyze data from two main sources, ITERATE data on international and the TWEED data on domestic terrorism. The similarities are tested in various dimensions – target types, severity, and the method of the attacks.

Homegrown terrorism is inherently motivated by domestic issues. Moreover, variables of ethnic heterogeneity, political inclusiveness of fringe groups, and problems in the democratization process are good predictors of the occurrence of other forms of domestic and homegrown terrorism alike.

Number of observable cases of homegrown terrorism are low. The two main datasets have potentially overlapping incidents.

Provides and operational definition of homegrown terrorism and test empirically the similarity between homegrown and other types of terrorisms.

When modeling environmental jolts from terrorist attacks, various aspects should be analyzed in order to properly present an accurate configuration. The following article discusses how asymmetrical warfare has an impact on the outcomes of a terrorist attack. The several dimensions of terrorist attacks can be extracted to deduce the ways that asymmetrical warfare can damage the health care system. The article will relate real life terrorist attacks and hypothetical scenarios to better inform the reader about the weak attacking the strong, and then explain how this relates to health care providers.

A zero-day vulnerability is a complimentary ticket to the attackers for gaining entry into the network. Thus, there is necessity to device appropriate threat detection systems and establish an innovative and safe solution that prevents unauthorised intrusions for defending various components of cybersecurity. We present a survey of recent Intrusion Detection Systems (IDS) in detecting zero-day vulnerabilities based on the following dimensions: types of cyber-attacks, datasets used and kinds of network detection systems.

Purpose: The study focuses on presenting an exhaustive review on the effectiveness of the recent IDS with respect to zero-day vulnerabilities.

Methodology: Systematic exploration was done at the IEEE, Elsevier, Springer, RAID, ESCORICS, Google Scholar, and other relevant platforms of studies published in English between 2015 and 2021 using keywords and combinations of relevant terms.

Findings: It is possible to train IDS for zero-day attacks. The existing IDS have strengths that make them capable of effective detection against zero-day attacks. However, they display certain limitations that reduce their credibility. Novel strategies like deep learning, machine learning, fuzzing technique, runtime verification technique, and Hidden Markov Models can be used to design IDS to detect malicious traffic.

Implication: This paper explored and highlighted the advantages and limitations of existing IDS enabling the selection of best possible IDS to protect the system. Moreover, the comparison between signature-based and anomaly-based IDS exemplifies that one viable approach to accurately detect the zero-day vulnerabilities would be the integration of hybrid mechanism.

Cyber threats present constantly evolving and unique challenges to national security professionals at all levels of government. Public and private sector entities also face a constant stream of cyberattacks through varied methods by actors with myriad motivations. These threats are not expected to diminish in the near future. As a result, homeland security and national security professionals at all levels of government must understand the unique motivations and capabilities of malicious cyber actors in order to better protect against and respond to cyberattacks. This chapter outlines the most common cyberattacks; explains the motivations behind these attacks; and describes the federal, state, and local efforts to address these threats.