reoffending than those who completed treatment. The predictors of nonsexual violent recidivism and general (any) recidivism were similar to those predictors found among nonsexual criminals (e.g., prior violent offenses, age, juvenile deliquency). Our results suggest that applied risk assessments of sexual offenders should consider separately the offender's risk for sexual and nonsexual recidivism. Assessing chronicity is crucial for clients whose sexual behaviors have brought them into conflict with the law. Many exceptional criminal justice policies, such as postsentence detention (e.g., Anderson & Masters, 1992), lifetime community supervision, and community notification, target those sexual offenders likely to reoffend. Clinicians need to judge whether the client's behaviors are truly atypical of the individual (as the client would like us to believe) or whether the client merits a virtually permanent label as a sexual offender.

/pdf/predicting-relapse-a-meta-analysis-of-sexual-offender-ml492rgh0h.pdf

Predicting relapse: a meta-analysis of sexual offender recidivism studies.

Meta-analytic techniques were used to determine which predictor domains and actuarial assessment instruments were the best predictors of adult offender recidivism. One hundred and thirty-one studies produced 1,141 correlations with recidivism. The strongest predictor domains were criminogenic needs, criminal history/history of antisocial behavior, social achievement, age/gender/race, and family factors. Less robust predictors included intellectual functioning, personal distress factors, and socioeconomic status in the family of origin. Dynamic predictor domains performed at least as well as the static domains. The LSI-R was identified as the most useful actuarial measure. Recommendations for developing sound assessment practices in corrections are provided.

/pdf/a-meta-analysis-of-the-predictors-of-adult-offender-4glo6e6fys.pdf

A meta‐analysis of the predictors of adult offender recidivism: what works!*

A meta-analysis of 82 recidivism studies (1,620 findings from 29,450 sexual offenders) identified deviant sexual preferences and antisocial orientation as the major predictors of sexual recidivism for both adult and adolescent sexual offenders. Antisocial orientation was the major predictor of violent recidivism and general (any) recidivism. The review also identified some dynamic risk factors that have the potential of being useful treatment targets (e.g., sexual preoccupations, general self-regulation problems). Many of the variables commonly addressed in sex offender treatment programs (e.g., psychological distress, denial of sex crime, victim empathy, stated motivation for treatment) had little or no relationship with sexual or violent recidivism.

/pdf/the-characteristics-of-persistent-sexual-offenders-a-meta-19hgzia124.pdf

The Characteristics of Persistent Sexual Offenders: A Meta-Analysis of Recidivism Studies.

Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Pippa Norris. New York: Cambridge University Press, 2002. 303 pp. $60 hbk., $20 pbk. Forecasts that the Internet heralds a world of more democracy and less poverty seem as inflated as dot.com stocks. This rosy view has electronic voting, political chat rooms, and email access re-engaging apathetic publics in politics. Digital technologies redress economic disparities, and the benefits of the Internet percolate down to transform poor societies. Equally exaggerated is the gloom of naysayers. The Internet Age has done little to narrow the gap between rich and poor countries, the information haves and havenots, cyber-skeptics contend. Indeed, digital technologies could create new inequalities and reinforce the dominance of power elites. In her new book, Digital Divide, Pippa Norris, associate director of the Joan Shorenstein Center on the Press, Politics and Public Policy at Harvard University, steps into this fusillade of cyber-hyperbole, lowers the decibel with a well-written and thoughtful examination of Internet use and access in 179 countries and dissects the claims and counter-claims. Her research and findings place her on middle ground, somewhere between current reality and optimism. The Internet era seems to be changing "politics as usual" in a number of countries, expanding and loosening information about governments and politics, allowing the entrance of new political players, and fostering international movements on the environment, women's rights, and other issues across borders. The disappointment is that digital technologies are activating the already politically active and passing up the disengaged and uninterested. A major challenge to digital democracy is the gulf between the United States, Scandinavia, and other early Internet adopters and the rest of the world. That gap is now so wide that at the turn of the century, more than three-quarters of the online community lived in the developed world. Internet use tracks the path of economic and technological development. But that situation could begin to change, Norris says. The Internet is in its technological adolescence. Costs of access are falling. And governments can make a difference if policymakers take the initiative. We have the historical patterns of other communication technologies to study. Norris examines theories of technological diffusion and points out that the American response to the Internet is more akin to the rapid spread of televisions and VCRs than the slower adoption of telephones and radios. American dominance could recede as Internet access grows worldwide. Contrary to what officials of the Bush Administration contend, Norris finds that the digital divide between rich and poor within the United States remains substantial. Europe mirrors that trend. In the long run, the Internet could become more accessible to the excluded: lower income families, minorities, and women. …

Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide

Machine learning techniques are being widely used to develop an intrusion detection system (IDS) for detecting and classifying cyberattacks at the network-level and the host-level in a timely and automatic manner. However, many challenges arise since malicious attacks are continually changing and are occurring in very large volumes requiring a scalable solution. There are different malware datasets available publicly for further research by cyber security community. However, no existing study has shown the detailed analysis of the performance of various machine learning algorithms on various publicly available datasets. Due to the dynamic nature of malware with continuously changing attacking methods, the malware datasets available publicly are to be updated systematically and benchmarked. In this paper, a deep neural network (DNN), a type of deep learning model, is explored to develop a flexible and effective IDS to detect and classify unforeseen and unpredictable cyberattacks. The continuous change in network behavior and rapid evolution of attacks makes it necessary to evaluate various datasets which are generated over the years through static and dynamic approaches. This type of study facilitates to identify the best algorithm which can effectively work in detecting future cyberattacks. A comprehensive evaluation of experiments of DNNs and other classical machine learning classifiers are shown on various publicly available benchmark malware datasets. The optimal network parameters and network topologies for DNNs are chosen through the following hyperparameter selection methods with KDDCup 99 dataset. All the experiments of DNNs are run till 1,000 epochs with the learning rate varying in the range [0.01-0.5]. The DNN model which performed well on KDDCup 99 is applied on other datasets, such as NSL-KDD, UNSW-NB15, Kyoto, WSN-DS, and CICIDS 2017, to conduct the benchmark. Our DNN model learns the abstract and high-dimensional feature representation of the IDS data by passing them into many hidden layers. Through a rigorous experimental testing, it is confirmed that DNNs perform well in comparison with the classical machine learning classifiers. Finally, we propose a highly scalable and hybrid DNNs framework called scale-hybrid-IDS-AlertNet which can be used in real-time to effectively monitor the network traffic and host-level events to proactively alert possible cyberattacks.

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Deep Learning Approach for Intelligent Intrusion Detection System

Purpose – Addresses the rapid expansion of computer connectivity and the opportunities provided for criminals to exploit security vulnerabilities in the online environment.Design/methodology/approach – International efforts to combat cyber‐crime are reviewed by evaluating the forms of mutual legal assistance (MLA) now in place.Findings – Cyber‐crime is often traditional crime (e.g. fraud, identify theft, child pornography) albeit executed swiftly and to vast numbers of potential victims, as well as unauthorised access, damage and interference to computer systems. Most detrimental are malicious and exploit codes that interrupt computer operations on a global scale and along with other cyber‐crimes threaten e‐commerce. The cross‐national nature of most computer‐related crimes have rendered many time‐honoured methods of policing both domestically and in cross‐border situations ineffective even in advanced nations, while the “digital divide” provides “safe havens” for cyber‐criminals. In response to the threa...

/pdf/developments-in-the-global-law-enforcement-of-cyber-crime-43camf3c0h.pdf

Developments in the global law enforcement of cyber‐crime

This paper explores the nature of groups engaged in cybercrime. It briefly outlines the definition and scope of cybercrime, theoretical and empirical challenges in addressing what is known about cyber offenders, and the likely role of organized crime groups. The paper gives examples of known cases that illustrate individual and group behaviour, and motivations of typical offenders, including state actors. Different types of cybercrime and different forms of criminal organisation are described drawing on the typology suggested by McGuire (2012). It is apparent that a wide variety of organisational structures are involved in cybercrime. Enterprise or profit-oriented activities, and especially cybercrime committed by state actors, appear to require leadership, structure, and specialisation. By contrast, protest activity tends to be less organized, with weak (if any) chain of command.

Organizations and Cyber crime: An Analysis of the Nature of Groups engaged in Cyber Crime

Five hundred and sixty sex offenders released from prisons over the period 1975-87 were followed for up to twelve years. A failure rate analysis (Wetbull mixture' model) provided estimates of probabilities of recidivism (re-incarceration) for any offence of 0.35 (for 95 per cent confidence interval it should lie between 0.25 and 0.46) for non-Aborigines and 0.80 (confidence interval 0.68-0.88) for Aborigines. Estimates or probabilities of committing further offences of violence, including further sex offences, were 0.21 (confidence interval 0.08-0.48) and 0.62 (confidence interval 0.13-0.95) respectively, but these figures are imprecise. A method of covariate analysis for recidivist data demonstrated that prior record, age, and race were crucial determining factors, but little evidence of specialization was found. It is argued that the evaluation of interventions should proceed on the basis of estimates of violent rather than repeat offending. The utility of incapacitation strategies and problems of crime prevention are discussed.

The recidivism of sex offenders in the western australian prison population

This paper explores the nature of groups engaged in cyber crime. It briefly outlines the definition and scope of cyber crime, theoretical and empirical challenges in addressing what is known about cyber offenders, and the likely role of organized crime groups. The paper gives examples of known cases that illustrate individual and group behaviour, and motivations of typical offenders, including state actors. Different types of cyber crime and different forms of criminal organization are described drawing on the typology suggested by McGuire (2012). It is apparent that a wide variety of organizational structures are involved in cyber crime. Enterprise or profit-oriented activities, and especially cyber crime committed by state actors, appear to require leadership, structure, and specialisation. By contrast, protest activity tends to be less organized, with weak (if any) chain of command.

/pdf/organizations-and-cyber-crime-an-analysis-of-the-nature-of-1bdno3egmy.pdf

Roderic Broadhurst

Papers

Developments in the global law enforcement of cyber‐crime

Organizations and Cyber crime: An Analysis of the Nature of Groups engaged in Cyber Crime

The recidivism of sex offenders in the western australian prison population

Organizations and Cyber crime: An Analysis of the Nature of Groups engaged in Cyber Crime

Homicide–suicide in Hong Kong, 1989–1998