Use of a Multitheoretic Model to Understand and Classify Juvenile Computer Hacking Behavior

• Author: Thomas J. Holt,Bryanna Fox
• DOI: 10.1177/0093854820969754
• Published date: 01 July 2021
• Date: 01 July 2021
• Subject Matter: Articles

CRIMINAL JUSTICE AND BEHAVIOR, 2021, Vol. 48, No. 7, July 2020, 943 –963.

DOI: https://doi.org/10.1177/0093854820969754

Article reuse guidelines: sagepub.com/journals-permissions

© 2020 International Association for Correctional and Forensic Psychology

943

USE OF A MULTITHEORETIC MODEL TO

UNDERSTAND AND CLASSIFY JUVENILE

COMPUTER HACKING BEHAVIOR

BRYANNA FOX

University of South Florida

THOMAS J. HOLT

Michigan State University

Criminological inquiry has identified a range of risk factors associated with juvenile delinquency. However, little research

has assessed juvenile computer hacking, despite the substantial harm and opportunities for delinquent behavior online.

Therefore, understanding the applicability of criminological risk factors among a cross-national sample of juvenile hackers

is important from a theoretical and applied standpoint. This study aimed to address this gap using a logistic regression and

latent class analysis (LCA) of risk factors associated with self-reported hacking behavior in a sample of more than 60,000

juveniles from around the globe. Results demonstrated support for individual- and structural-level predictors of delinquency,

although distinct risk factors for hacking among three subtypes are identified in the LCA. This study examines criminologi-

cal risk factors for juvenile hacking in a cross-national sample and provides insight into the distinct risk factors of hacking,

so more tailored prevention and treatment modalities can be developed.

Keywords: cybercrime; hacking; juvenile justice; prevention; latent class analysis

A

major focus of criminological inquiry over the last century has been on the etiology of

juvenile delinquency (Loeber & Farrington, 1998). A number of individual-level risk

factors have been shown to increase the risk of juvenile delinquency, including delinquent

peer association (Akers, 1998), low self-control (Gottfredson & Hirschi, 1990; Pratt &

Cullen, 2000), victimization/abuse (Fox et al., 2015; Lauritsen & Laub, 2007), and

structural-level factors such as neighborhood disorganization and socioeconomic status

(SES; Bursik & Grasmick, 1993; Pratt & Cullen, 2005). Research also suggests that these

risk factors “do not operate in isolation” (Kendziora & Osher, 2004, p. 182) and that most

justice-involved youth display multiple risk factors that span across theoretical domains

(Loeber & Farrington, 1998; Thornberry et al., 1995). Moreover, these risk factors appear

to operate in a cumulative fashion, resulting a nonlinear effect on risk of future offending

(Herrenkohl et al., 2000; Loeber & Farrington, 1998).

These findings have led to a notable shift in the juvenile justice field over the past two

decades, with researchers aiming to “identify the key risk factors for offending, and tool

AUTHORS’ NOTE: Correspondence concerning this article should be addressed to Bryanna Fox, Department

of Criminology, University of South Florida, 4202 E. Fowler Avenue, SOC 107, Tampa, FL 33620; e-mail:

bhfox@usf.edu.

969754CJBXXX10.1177/0093854820969754Criminal Justice and BehaviorFox, Holt / Juvenile Hacker Risk Factors

research-article2020

944 CRIMINAL JUSTICE AND BEHAVIOR

prevention methods designed to counteract them” (Farrington, 2000, p. 1; Farrington et al.,

2012). This approach is focused on prevention, not punishment, and aims to develop strate-

gies to specifically counteract these risk factors (Farrington, 2000). In a related vein,

research on the heterogeneity of those who offend has also spurred efforts to identify the

distinct risk factors among justice-involved youth (Fox & DeLisi, 2018; Muniz et al., 2019).

Together, these efforts suggest that we can identify unique risk factors among youth and

develop tailored prevention and intervention strategies for youth with varied risk factors,

rather than the “one-size-fits-most” approach to juvenile justice (Andrews & Bonta, 2010;

Farrington & Welsh, 2006).

JUVENILE CYBERCRIME AND HACKING

A recent challenge to the treatment and prevention of delinquency is that computers and the

internet have enabled crime to occur in ways that cannot be as easily monitored by parents,

teachers, and police (Holt & Bossler, 2015; Yar, 2005). Cybercrime, or the misuse of technol-

ogy to offend, has become a global problem, although available research on the risk factors

varies by cybercrime type (Holt & Bossler, 2015). There is a particularly small body of

research on the risk factors for computer hacking, broadly defined as the use of specialized

knowledge of technology to gain access to sensitive data and computer networks (Holt &

Bossler, 2015; Taylor, 1999). Hacking is a unique form of cybercrime, as the same action and

knowledge can be used to secure a system from compromise or illegally gain access to critical

system functions and data (Holt, 2007; Jordan & Taylor, 1998). In fact, the computer security

industry is predicated on understanding the malicious application of hacking to defend sensi-

tive networks from compromise by hackers and nation-state actors (Holt & Bossler, 2015).

As a consequence, social scientists typically use specific questions to assess computer

hacking in general population surveys (see Holt & Bossler, 2015, for review). Often overtly

illegal but simplistic forms of hacking have been measured in the past, such as password

guessing and adding or changing data (Holt & Bossler, 2015; Leukfeldt, 2017). More seri-

ous forms of hacking like malware use and theft of personal information have very low

prevalence rates and are often absent from juvenile surveys (Holt & Bossler, 2015; Leukfeldt,

2017). Similarly, questions related to simple forms of digital piracy have been treated as

distinct from hacking due to the ease with which music and media piracy are performed in

the modern computing age (Holt & Bossler, 2015). As a result, researchers have been lim-

ited in their ability to assess involvement in legitimate or legally questionable hacks, imped-

ing our understanding of pathways to hacking and variations to involvement in legal and

illicit hacks across populations.

JUVENILE HACKING

Despite these measurement issues, hacking has increasingly been linked to serious crimi-

nal activity over the past three decades, particularly economic harms stemming from the

loss of sensitive data and degradation of computer hardware and software functionality

(Furnell, 2002; Grabosky, 2016; Holt, 2007). There has also been a growing concern over

the increased engagement of youth in hacking, with the near ubiquitous access to home

computing and internet connectivity since the 1980s (Calce & Silverman, 2008; Slatalla &

Quittner, 1995). Qualitative examinations have found youth with early access and interest

in computers may become involved in hacking (Holt, 2007; Taylor, 1999). Initial hacks

may often be simplistic in nature, such as guessing passwords to remotely access user