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Pirated software is an attractive choice for cybercriminals seeking to spread malicious software, known as malware. This paper attempts to quantify the occurrence of malware concealed within pirated software. We collected samples of pirated software from various sources from Southeast Asian countries, including hard disk drives, optical discs purchased in eight different countries, and online platforms using peer-to-peer services. Our dataset comprises a total of 750 pirated software samples. To analyze these samples, we employed seven distinct antivirus (AV) engines. The malware identified by the AV engines was classified into four categories: adware, Trojans, viruses, and a miscellaneous category termed others. Our findings reveal that adware and Trojans are the most prevalent types of malware, with average infection rates of 34% and 35%, respectively, among our pirated software samples. Notably, our evaluation of AV detection performance highlights variations in sensitivity, ranging from a high of 132% to a low of 30% across all AV engines. Furthermore, upon installing pirated software, the most adversely affected operating system settings are the firewall and user account control configurations. Given the potential for malware to steal information or create malicious backdoors, its high prevalence within pirated software poses a substantial security risk to end users.

Amid the withdrawal of foreign software developers from the Russian market, policymakers continue to discuss the option of legalising software parallel import. The purpose of the article is to assess the expected effects of the software parallel import introduction. The methodological basis of the study is industrial organization theory and new institutional economics theory. Among the research methods are theoretical and mathematical modelling and comparative analysis. The empirical evidence includes publicly available data on the pirated content consumption retrieved from the web source I Know (iknowwhatyoudownload.com) and financial statements of Russian software developers (SPARK-Interfax database). The article presents a theoretical model describing the consumer’s choice between original and pirated versions of programs and analyses the situation, where the most popular software product gets inaccessible. Our analysis shows that when costs of piracy are low, users of ‘out-of-the-box’ programs will not switch to another software and prefer the pirated version of the previously used program. The results of the model are compared with data on the pirated software consumption in Russia. We have found that consumers prefer foreign software to Russian counterparts, which means that if parallel import is legalised, Russian software developers will fail to occupy the niche of home-use software, which remains an important reserve for the industry’s further development. Free access to foreign software distorts consumer incentives. The institution of parallel imports should be modified so that the consumer keeps paying the price of the original’s, the state guarantees such software is secure, and intellectual property violations are strictly controlled.

We study how private intellectual property rights protection affects equilibrium prices in a duopoly competition between firms that offer a product variety of distinct qualities (vertical product differentiation) in a setup that is closely related to that put forward by Jain where firms offer the same qualities in equilibrium (horizontal product differentiation). Consumers may make a choice to buy a legal version, use an illegal copy (if they want to and can), or not use a product at all. Using an illegal version violates intellectual property rights protection and is thus punishable when discovered. Thus, both private and public (copyright) intellectual property rights protection are available on scene. [ABSTRACT FROM AUTHOR]

In this paper, we attempt to investigate the effect of usage of pirated software on productivity by utilizing three distinct indicators of productivity for developing countries and an unbalanced panel data set containing the years between 2003 and 2017. Our hypothesis claims that increase in the use of pirated software enhance the productivity level in developing countries. Firstly, we implemented univariate analyses and the results of univariate analyses implied that the usage of pirated software and productivity are positively and significantly related in all of three models. Secondly, three control variables (i.e., education, investment, and openness) were employed in our three productivity models in order to check if the findings of univariate analyses remain valid and robust. After inclusion of the three control variables, the statistically significant positive association between the use of pirated software and productivity were observed in all models. Regarding to control variables, they take expected signs whenever they are statistically significant. Based on the estimated coefficients of PROD1 models, a 1% positive change in usage of pirated software leads to a rise in a growth in productivity by 0.1023% and 0.0623% in univariate and multivariate models, respectively while a 1% positive change in usage of pirated software leads to a rise in a growth in productivity by 0.1072% and 0.0684% in univariate and multivariate models of PROD2, respectively. Besides a 1% positive change in usage of pirated software induce to an increase in productivity level by 0.0881 and by 0.0601, respectively in PROD3 models. Secondly, three control variables, namely education, investment, and openness, were included in our three productivity models to test if the finding of univariate analyses keeps its validity. EDUC, INVEST, and OPEN variables are taken the anticipated positive influences and they are statistically significant at least at the level of 5%. More specifically, in estimation results for PROD1 model, one percent increase in EDUC, INVEST, and OPEN variables cause to a jump in productivity by 0.2309%, 0.1198%, and 0.7359%, respectively. Openness of an economy has the most explanatory power among all independent variables. In addition to PROD1 model, in estimation results for PROD2 model, one percent increase in EDUC, INVEST, and OPEN variables cause to a jump in productivity by 0.2482%, 0.0893%, and 0.7211%, respectively. Besides a 1% positive change in EDUC, INVEST, and OPEN variables induce to an increase in productivity level by 0.3345%, 0.0341%, and 0.2238%, respectively in PROD3 models. [ABSTRACT FROM AUTHOR]

Recent developments in computer networks and Internet of Things (IoT) have enabled easy access to data. But the government and business sectors face several difficulties in resolving cybersecurity network issues, like novel attacks, hackers, internet criminals, and so on. Presently, malware attacks and software piracy pose serious risks in compromising the security of IoT. They can steal confidential data which results in financial and reputational losses. The advent of machine learning (ML) and deep learning (DL) models has been employed to accomplish security in the IoT cloud environment. This article presents an Enhanced Artificial Gorilla Troops Optimizer with Deep Learning Enabled Cybersecurity Threat Detection (EAGTODL-CTD) in IoT Cloud Networks. The presented EAGTODL-CTD model encompasses the identification of the threats in the IoT cloud environment. The proposed EAGTODL-CTD model mainly focuses on the conversion of input binary files to color images, where the malware can be detected using an image classification problem. The EAGTODL-CTD model pre-processes the input data to transform to a compatible format. For threat detection and classification, cascaded gated recurrent unit (CGRU) model is exploited to determine class labels. Finally, EAGTO approach is employed as a hyperparameter optimizer to tune the CGRU parameters, showing the novelty of our work. The performance evaluation of the EAGTODL-CTD model is assessed on a dataset comprising two class labels namely malignant and benign. The experimental values reported the supremacy of the EAGTODL- CTD model with increased accuracy of 99.47%. [ABSTRACT FROM AUTHOR]

Applications for the Internet of Things (IoT) have been employed in a broad range of industries, including smart homes, healthcare, smart energy, and Industrial 4.0. IoT offers many advantages, such as ease and efficiency, but it also adds a lot of new risks. The problem is often made worse by the potential number of linked IoT devices and the ad hoc nature of such networks. IoT management now faces substantial difficulties related to safety and confidentiality. Current research has shown that deep learning algorithms are quite effective and have numerous benefits over previous approaches for doing security assessments of IoT devices. An integrated deep learning approach is created in this work to identify files containing malware and pirated software through the Internet of Things network The Hybrid Dual-Channel Convolution Neural Network (DCCNN) with Spider Monkey Optimization (SMO) is called DCCNN-SMO advocated leveraging stolen reference code to detect software piracy. For the purpose of examining software piracy, the dataset was gathered via Google Code Jam (GCJ). To research the suggested strategy, collected 100 input data for internet users from GCJ. In addition, the DCCNN-SMO is utilized to visualize colored images to identify harmful intrusions in IoT networks. From the Leopard Mobile database, malware samples were taken for testing. The actual results demonstrate that the recommended method for calculating the cyber security risks in IoT performs categorization more over current approaches. The proposed DCCNN-SMO + SVM approach provides better resultant value of 98.55% whereas the other existing approaches like GIST + SVM is 86.1%, CLGM + SVM is 92.06% and DNN + SVM is 97.46%, LBP + SVM is 78.05%.

While the intention and participation in media and software piracy have been widely investigated, little is known concerning the determinants associated with electronic book piracy. With the adoption of e-book reader devices, Internet piracy remains a global concern that impacts multiple stakeholders, including authors, publishers, and libraries. The current study aims to examine the factors associated with electronic book piracy among college students. Results indicate that peer association and perceived risk are significantly linked to one's participation in e-book piracy. However, techniques of neutralization are not statistically significant. Libraries and publishers must educate students and raise awareness about the potential outcomes and risks related to e-book piracy. [ABSTRACT FROM AUTHOR]

Measures of ethical behaviours in research may be subject to social desirability bias (SDB). Most behavioural aspects of software piracy research are a subset of ethical research. Few studies of software piracy have explicitly addressed the issue of SDB. In this article, the extent of SDB that may be present in software piracy is empirically assessed. This was done by comparing SDB in software piracy under three conditions using the 40-item Balanced Inventory of Desirable Responding (BIDR) scale. First, software piracy behaviour was examined in an experimental setting with actual money at stake. This allowed subject behaviour to be observed rather than inferred from self-report responses. Second, a survey was conducted to test the extent of software piracy based on subject self-report responses. Third, the extent of software piracy was also assessed based on peer-report responses (i.e.: the subject reported whether their peers would pirate). A comparison of the responses in the three conditions allows us to draw inferences about SDB in software piracy research. Self-report surveys exhibited high levels of SDB. The behaviour in the experimental condition, and responses in the peer-report survey method, did not exhibit SDB. [ABSTRACT FROM AUTHOR]

Piracy is a significant source of concern facing software developers, music labels, and movie production companies, to name a few. Digital goods producers and government entities argue that there are victims of piracy, whereas pirates may perceive their actions to be victimless. Regarding implications of our research, we extend the theory of planned behavior (TPB) by theorizing that attitudes, subjective norms, and perceived behavioral control could influence perceptions of moral obligations as a consequence of the desire to rationalize unethical behavior. Unlike prior literature, we manipulate the rationalization of moral obligations due to the victimless view toward piracy and show how moral obligations become important determinants of piracy behavior. Accordingly, our demonstrated malleability of morals may be an important path through which individuals are able to continue past behaviors. We also conduct a second study to identify the effect of implementing an educational message from a fictitious software company to exogenously nudge the pirate and influence the impact of perceived moral obligations on intentions to pirate. Our results show that the introduction of an exogenous educational message is an effective piracy mitigation strategy. [ABSTRACT FROM AUTHOR]

Why do mainstream consumers who would not typically engage in illegal behaviour routinely resort to online piracy of copyrighted software? This paper provides answers to this research query by applying routine activity theory and the theory of reasoned action. The paper’s study analyses consumers’ role as possible offenders that can have the opportunity to engage in online software piracy as part of their routine online activities. Although it is problematic to measure the exact magnitude of the negative impact on the US economy, as stated by the Government Accountability Office it is sizeable. After analysing the conceptual model using a US national consumer sample of over 700 consumers, results show the influence of proximity to motivated offenders, target suitability, and capable guardianship on consumers’ attitudes and perceived subjective norms towards online software piracy, as well as their intentions to engage in this illegal behaviour on the Internet. By integrating routine activity theory, a criminology theory with the theory of reasoned action from psychology and analysing a widespread online software piracy phenomenon, several academic and practical contributions are made. [ABSTRACT FROM AUTHOR]

This paper explores the dynamic long‐term relationship between software protection and software piracy rates across 108 countries over the period of 20 years (1994–2015), with the help of the ARDL model. The analysis employs a new way of utilising the membership duration of Trade related Intellectual Property Rights agreement and World Intellectual Property Organisation Copyright Treaty agreements of different countries in a panel framework, apart from constructing an index of copyright software protection by focusing on enforcement provisions. The paper overcomes various shortcomings of earlier literatures by thoughtful inclusion of independent variables and methodological techniques. Results show that both copyright software protection and income share a negative long‐term relationship with software piracy. Even the enforcement provisions are important in mitigating software piracy. In addition, the model finds a negative relationship between demand for intellectual property protection and software piracy rates. [ABSTRACT FROM AUTHOR]

This study analyzes the effect of usage of pirated software on poverty by using six prominent poverty indicators for the samples of developing and Latin America countries. The data utilized in models is unbalanced and employ the period between 2003 and 2017. Our hypothesis asserts that increases in usage of pirated software diminish poverty in developing and Latin America countries. Firstly, univariate analyses are conducted, and the results of univariate analyses are demonstrated that there is a statistically significant opposite relationship between usage of pirated software and poverty in all six distinct poverty models. Secondly, three control variables (i.e., unemployment, health expenditure, and human capital) were included to our six poverty models to find out if the finding of univariate analyses retains its validity. The statistically significant reverse relationship between usage of pirated software and poverty remained the same after the inclusion of the three covariates. In other words, usage of pirated software maintains its negative significant effect on poverty in all models for both developing and Latin America countries samples. In consideration of the control variables, statistically significant negative coefficients were obtained for health expenditure and human capital whereas a positive coefficient was obtained for unemployment. [ABSTRACT FROM AUTHOR]

This paper focuses on one of the topics of copyright economics: the study of software piracy and its determinants. The efficiency of OECD countries regarding the consumption of illegal software is analyzed. In this vein, efficiency is associated with the minimal consumption of software piracy according to the socioeconomic characteristics of a nation. Data Envelopment Analysis is the methodology employed, which assigns an efficiency score to the countries in order to establish a ranking of efficiency. Additionally, a relationship is established between the legal origin of the copyright law of a country and its efficiency level. The results of the efficiency analysis show that the efficient countries are Austria, Hungary, Japan, Korea, Mexico and Slovakia; this leads to the affirmation that the countries with lower levels of piracy are not always efficient. According to the legal origin of copyright law, countries with a German origin are the most efficient. Consequently, the efficiency score is not related to the level of software piracy but to the legal origin. [ABSTRACT FROM AUTHOR]

Sci-Hub is a project that uses stolen log-in credentials to access pay-walled scientific articles and journals, and then makes them available for free on its website. It has had a significant impact on medical journals. The HEC Digital Library does not cover all research areas. The Higher Education Commission (HEC) has acknowledged that Sci-Hub could fill a gap in the availability of research materials for Pakistani researchers but cautioned that the use of Sci-Hub is illegal and could have negative consequences for the scientific community. Sci-Hub has faced legal challenges in some countries but has generally been able to operate without interference. The legality of Sci-Hub is complex, with legal challenges varying by country. There are legal ways to access scientific manuscripts. The Sci-Hub project has significantly impacted research in Pakistan, but the HEC does not condone the use of Sci-Hub, and it could have negative consequences for the scientific community. [ABSTRACT FROM AUTHOR]

Purpose: This research aims to develop and test a conceptual model for shaping small and medium enterprise (SME) employees' avoidance behaviour towards using pirated software. The model specifies the components of morality, spirituality, emotional intelligence and ethical values that influence employees' avoidance behaviour towards using pirated software. Design/methodology/approach: A conceptual framework was developed and tested on the basis of information technology and management literature by using data from 275 influential and active employees of SMEs. Data were collected via a survey and analysed through covariance-based structural equation modeling (CB-SEM). Findings: In the context of SMEs, employees' avoidance behaviour towards using pirated software is motivated by significant moral antecedents. Moral equity and judgement significantly influence employees' avoidance behaviour towards using pirated software when moral emotion mediates such a relationship. In addition, individual spirituality significantly moderates the relationship between moral equity and moral emotion. Employees' emotional intelligence optimises the strength of the relationship between moral judgement and moral emotion. Employees' likelihood to engage in unethical behaviour decreases when they exhibit strong ethical values in the relationship between moral emotion and their behaviour towards using pirated software. Research limitations/implications: This study offers theoretical support for employees' avoidance behaviour towards using pirated software. The findings of this cross-sectional work have limited generalisability. Single-country data may not be generalised to SME employees in other countries. Thus, cross-country analysis and additional measures and antecedents must be developed and identified in the future. Practical implications: Policymakers and managers should consciously review the proposed seven-component model that causes SME employees to avoid the use of pirated software. Ethical standards that lessen the use of pirated software can be improved if managers and policymakers understand the components of moral equity and judgement that influence moral emotions. Originality/value: This study is the first to examine the specific antecedents of the ethical standards and avoidance behaviours of SME employees towards the use of pirated software. As such, it provides a foundation for further studies on this critical area and software piracy in the context of SMEs in an emerging economy, which is limited in current literature. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) -based systems need to be up to date on cybersecurity threats. The security of IoT networks is challenged by software piracy and malware attacks, and much important information can be stolen and used for cybercrimes. This paper attempts to improve IoT cybersecurity by proposing a combined model based on deep learning to detect malware and software piracy across the IoT network. The malware’s model is based on Deep Convolutional Neural Networks (DCNNs). Apart from this, TensorFlow Deep Neural Networks (TFDNNs) are introduced to detect software piracy threats according to source code plagiarism. The investigation is conducted on the Google Code Jam (GCJ) dataset. The conducted experiments prove that the classification performance achieves high accuracy of about 98%. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) -based systems need to be up to date on cybersecurity threats. The security of IoT networks is challenged by software piracy and malware attacks, and much important information can be stolen and used for cybercrimes. This paper attempts to improve IoT cybersecurity by proposing a combined model based on deep learning to detect malware and software piracy across the IoT network. The malware’s model is based on Deep Convolutional Neural Networks (DCNNs). Apart from this, TensorFlow Deep Neural Networks (TFDNNs) are introduced to detect software piracy threats according to source code plagiarism. The investigation is conducted on the Google Code Jam (GCJ) dataset. The conducted experiments prove that the classification performance achieves high accuracy of about 98%.

This study extends the literature on fighting software piracy by investigating how Intellectual Property Rights (IPRs) regimes interact with technology to mitigate software piracy when existing levels of piracy are considered. Two technology metrics (internet penetration rate and number of PC users) and six IPR mechanisms (constitution, IPR law, main IP laws, WIPO Treaties, bilateral treaties and multilateral treaties) are used in the empirical analysis. The statistical evidence is based on (i) a panel of 99 countries for the period 1994–2010 and (ii) interactive contemporary and non-contemporary quantile regressions. The findings show that the relevance of IPR channels in the fight against software piracy is noticeably contingent on the existing levels of technology embodied in the pirated software. There is a twofold policy interest for involving modern estimation techniques such as interactive quantile regressions. First, it uncovers that the impact of IPR systems on software piracy may differ depending on the nature of technologies used. Second, the success of initiatives to combat software piracy is contingent on existing levels of the piracy problem. Therefore, policies should be designed differently across nations with high, intermediate and low levels of software piracy. [ABSTRACT FROM AUTHOR]

The IoT (Internet of Things) connect systems, applications, data storage, and services that may be a new gateway for cyber-attacks as they continuously offer services in the organization. Currently, software piracy and malware attacks are high risks to compromise the security of IoT. These threats may steal important information that causes economic and reputational damages. In this paper, we have proposed a combined deep learning approach to detect the pirated software and malware-infected files across the IoT network. The TensorFlow deep neural network is proposed to identify pirated software using source code plagiarism. The tokenization and weighting feature methods are used to filter the noisy data and further, to zoom the importance of each token in terms of source code plagiarism. Then, the deep learning approach is used to detect source code plagiarism. The dataset is collected from Google Code Jam (GCJ) to investigate software piracy. Apart from this, the deep convolutional neural network is used to detect malicious infections in IoT network through color image visualization. The malware samples are obtained from Maling dataset for experimentation. The experimental results indicate that the classification performance of the proposed solution to measure the cybersecurity threats in IoT are better than the state of the art methods.

The presentation and sharing of information, especially in digital environments, have become significantly easier with information and communication technologies and this has caused an increase in copyright problems. The aim of this study is to reveal the levels of awareness of academic and postgraduate students of copyrights in relation to digital products. The survey model was used in research conducted with the participation of academicians working at different universities in Turkey and postgraduate students in the 2018-2019 academic year. According to the findings, the knowledge level of the participants regarding copyrights, license agreements and fair use is moderate, their knowledge level about open source software, free software and copyleft is low, and they do not commit copyright infringements apart from downloading computer programs. Those working in the field of informatics commit more copyright infringement than others (such as using unlicensed software, distributing license serial numbers, illegally downloading music, videos etc., using without reference), as also do those in the 20-25 age range. The majority of participants stated that policies to prevent infringement of copyright digital products were insufficient, there is a lack of information about enforcement and their reasons for the situation include the belief in not getting caught and no one getting hurt, as well as not seeing it as a crime. [ABSTRACT FROM AUTHOR]

Summary: The Software plagiarism, which arises the problem of software piracy is a growing major concern nowadays. It is a serious risk to the software industry that gives huge economic damages every year. The customers may develop a modified version of the original software in other types of programming languages. Furthermore, the plagiarism detection in different types of source codes is a challenging task because each source code may have specific syntax rules. In this paper, we proposed a methodology for software plagiarism detection in multiprogramming languages based on machine learning approaches. The Principal Component Analysis (PCA) is applied for features extraction from source codes without losing the actual information. It extracts features by factor analysis and converts the dataset into normalized linear principal components which are further useful for predictions analysis. Then, the multinomial logistic regression model (MLR) is applied to these components to classify the source codes documents based on predictions. It gives the generalization of logistic regression to handle multiclass problems. Further, the predictors' performance in MLR is evaluated by 2 tailed z test. To apply the experiment, the dataset is collected in five different and popular languages, ie, C, C++, Java, C#, and Python. Each programming language taken in two different case studies, ie, binary search and Stack. [ABSTRACT FROM AUTHOR]

Abstract. Many studies have investigated why users engage in digital piracy. The theoretical explanations are particularistic, and the empirical findings are fragmented, sometimes divergent, and reveal unexplained variations of effects. [...]

Introduction Pirating is a way of life now. I have pirated movies for my grandma, pirated software for my dad to get back to work, pirated music for my mom, [...]

This paper examines the role of software piracy in digital platforms where a platform provider makes a decision of how much software to produce in-house and how much to outsource from a third-party software provider. Using a vertical differentiation model, we theoretically investigate how piracy influences the software outsourcing decision. We find that when piracy is intermediate, the loss in in-house software profits due to piracy outweighs the loss in licensing fee profits. As a result, an increase in piracy leads to more outsourcing. However, when piracy is high, it becomes too expensive for the platform provider to subsidize the software provider, resulting in a decrease in outsourcing. Moreover, when software variety is also endogenously chosen by firms, the platform provider's incentive to develop software variety in-house depends not only on the return from software profits but also on the return from hardware profits. Under such a situation, an increase in piracy always leads to less outsourcing and less total software variety. To provide additional insights on the outsourcing decision, we conduct empirical analyses using data from the U.S. handheld video game market between 2004 and 2012. This market is a classical two-sided market, dominated by two handheld platforms (Nintendo DS and Sony PlayStation Portable) and is known to have suffered from software piracy significantly. Our regression results show that in this market, piracy increases outsourcing but has no effect on the total software variety. [ABSTRACT FROM AUTHOR]

Software piracy has numerous negative effects. The concern of software piracy is not limited to software developers but also educational institutions. The purpose of the current study was to investigate the factors contributing to the behavioral intention of Generation Z students' to comply with educational software anti-piracy laws by utilizing the Protection Motivation Theory (PMT). The results indicated that self-efficacy and response efficacy had significant relationships with the behavioral intention of Generation Z's intention to comply with educational software anti-piracy laws. Several insights from practical and managerial perspective were also discussed. In the end, software developer and academic institutions could use this model to promote anti-piracy behavior in the future. [ABSTRACT FROM AUTHOR]

Globalization has been linked with many social problems, though little research has examined its relationship with software piracy. The ramifications of software piracy may vary across countries leading to varied criminal justice responses. More developed countries, which produce the most software and stand to gain the most from its protection, use diplomatic leverage to strengthen piracy laws in less developed countries. Consequently, lesser-developed countries are forced to adopt rigorous policies for IP protection. As such, we hypothesize that globalization will decrease software piracy rates over time. Using a modified random effect model, the current study examines the within and between countries effects of globalization on software piracy rates over time in 103 countries across a period of 14 years. Results indicate that globalization is significantly associated with a decrease in software piracy within and between countries over time while controlling for important time-varying and time invariant predictors. Interaction effects suggest that the relationship between globalization and software piracy is less pronounced in Asian countries and more pronounced in Latin American countries. In sum, some crimes, like software piracy, may be deterred if there are strong enough incentives and international pressures to regulate such crime through legislative and policy reforms. [ABSTRACT FROM AUTHOR]

This article analyzes how software pirates who formed the 'warez scene' appropriated telephone network infrastructures and Bulletin Board System (or BBS) technology to circulate computer software across national borders. This paper is shedding more light on the roots of contemporary internet-based software piracy by investigating how appropriation of international telephone networks contributed to the globalization of digital software distribution. It also highlights the mundane aspects of the organization of media convergence on the junction between analog and digital technologies. Here I argue that the use of telephone networks as a means of transnational software distribution is an instance of actors setting up a convergent media environment driven by the cultural logic of a specific subculture. My paper provides an overview of BBS technology to demonstrate how it linked analog and digital domains and then outlines its cultural significance, ultimately discussing the appropriation of BBSes and their role in transnational expansion of 'the scene'. [ABSTRACT FROM AUTHOR]

In March of 2011, several news media outlets published articles announcing the opening of a "pirate prison" in the northwest region of Somalia. Over the next five years, news articles about East African prisons holding piracy prisoners en masse were among the few ways in which the public came to know pirate prisons—what they look like, who they punish, and how they punish. Our analysis of the text and imagery in news articles about these prisons reveals that pirate prison narratives reflects the unique political, social, and economic issues of each location. The geographically-specific narratives are created, promoted, and in some cases silenced by different actors and entities to shape public perception of pirate prisons and motivate funding decisions. This case study aims to theorize what these pirate prison narratives tells us more broadly about the complexities underlying the promotion of criminal justice reforms in the media and the political economy of punishment in East Africa. We contend that the production and maintenance of particular pirate prison narratives helps various actors and agencies maximize benefits tied to a broader penal market where piracy prisoners are detained and transferred in exchange for development aid. [ABSTRACT FROM AUTHOR]

Software piracy has been known as unauthorised reconstruction or illegal redistribution of a licenced software. Detecting pirated from base software is a major concern since pirated software can lead to significant financial losses as well as serious security vulnerabilities. To detect software piracy, we have recently proposed Metamorphic Analysis for Automatic Software Piracy Detection (MetaSPD) with a proof-of-concept evaluation. The core idea of MetaSPD was inspired from metamorphic malware detection due to its similarity of software piracy detection. MetaSPD works primarily based on mining the opcode graph of the base software to extract micro-signatures. Then, it leverages a classifier model to decide whether a given suspicious file is a pirated version of the base software. This paper extends our prior work in several respects. First, we present a retrospective appraisal of the main literature aiming at laying bare the status quo of software piracy detection and arguments on the current problems of the field to motivate our work. We then elaborate on MetaSPD itself and the constituent components. We provide two extensive experiments to evident the effectiveness of MetaSPD. The experiments have been carried out on two different datasets. Each dataset comprises 1300 morphed variants of the respective base software that act as pirated versions of that software. We conducted our experiments using three different classifiers. The paper is also enriched with a detailed discussion of the different properties and concerns of MetaSPD. The results corroborate that an attacker, who is using a pirated version of the given software, can hardly hide illegal usage of the software even by applying superabundant obfuscations to the code. [ABSTRACT FROM AUTHOR]

This study attempted to confirm the existence of a suppression situation among social learning, low self-control, and software piracy measures. Using a cross-sectional study of middle and high school students, structural equation modeling was used to confirm the measurement of a second-order social learning factor and the existence of a mediated suppression situation of low self-control through social learning on software piracy. The existence of a suppression situation was confirmed when low self-control was modeled with an indirect effect through social learning: The direct effect of low self-control on software piracy flipped direction from positive to negative and social learning's direct effect size increased. This suppression situation was only demonstrated when social learning was modeled as a second-order latent factor. Future research of social learning should consider how its indicators are measured and the importance for the use of all social learning subdomains. [ABSTRACT FROM AUTHOR]

Software watermarking is a software protection technique used to defend the intellectual property of proprietary code. In particular, software watermarking aims at preventing software piracy by embedding a signature, i.e. an identifier reliably representing the owner, in the code. When an illegal copy is made, the owner can claim his/her identity by extracting the signature. It is important to hide the signature in the program in order to make it difficult for the attacker to detect, tamper or remove it. In this work, we present a formal framework for software watermarking, based on program semantics and abstract interpretation, where attackers are modelled as abstract interpreters. In this setting, we can prove that the ability to identify signatures can be modelled as a completeness property of the attackers in the abstract interpretation framework. Indeed, hiding a signature in the code corresponds to embed it as a semantic property that can be retrieved only by attackers that are complete for it. Any abstract interpreter that is not complete for the property specifying the signature cannot detect, tamper or remove it. We formalize in the proposed framework the major quality features of a software watermarking technique: secrecy, resilience, transparence and accuracy. This provides a unifying framework for interpreting both watermarking schemes and attacks, and it allows us to formally compare the quality of different watermarking techniques. Indeed, a large number of watermarking techniques exist in the literature and they are typically evaluated with respect to their secrecy, resilience, transparence and accuracy to attacks. Formally identifying the attacks for which a watermarking scheme is secret, resilient, transparent or accurate can be a complex and error-prone task, since attacks and watermarking schemes are typically defined in different settings and using different languages (e.g. program transformation vs. program analysis), complicating the task of comparing one against the others. [ABSTRACT FROM AUTHOR]

Duplication in software systems is an important issue in software quality assurance. While many methods for software clone detection in source code and structural models have been described in the literature, little has been done on similarity in the dynamic behaviour of interactive systems. In this paper, we present an approach to identifying near-miss interaction clones in reverse-engineered UML sequence diagrams. Our goal is to identify patterns of interaction (“conversations”) that can be used to characterize and abstract the run-time behaviour of web applications and other interactive systems. In order to leverage existing robust near-miss code clone technology, our approach is text-based, working on the level of XMI, the standard interchange serialization for UML. Clone detection in UML behavioural models, such as sequence diagrams, presents a number of challenges—first, it is not clear how to break a continuous stream of interaction between lifelines (representing the objects or actors in the system) into meaningful conversational units. Second, unlike programming languages, the XMI text representation for UML is highly non-local, using attributes to reference-related elements in the model file remotely. In this work, we use a set of contextualizing source transformations on the XMI text representation to localize related elements, exposing the hidden hierarchical structure of the model and allowing us to granularize behavioural interactions into conversational units. Then we adapt NICAD, a robust near-miss code clone detection tool, to help us identify conversational clones in reverse-engineered behavioural models. These conversational clones are then analysed to find worrisome interactions that may indicate security access violations. [ABSTRACT FROM AUTHOR]

This study examines the persistence of software piracy with internet penetration vis-à-vis of PC users, conditional on Intellectual Property Rights (IPRs) institutions. The empirical evidence is based on a panel of 99 countries for the period 1994-2010 and the Generalised Method of Moments. The main finding is that, compared to internet penetration, PC usage is more responsible for the persistence of global software piracy. Knowing how technology affects the persistence of piracy is important because it enables more targeted policy initiatives. We show that the sensitivity of software piracy to IPR mechanisms is contingent on the specific technology channels through which the pirated software is consumed. [ABSTRACT FROM AUTHOR]

This paper studies the determinants of software piracy losses along five major macro­economic dimensions: Technological, Educational, Institutional, Access to Information and Labor force. The study was conducted based on a large dataset available from 1995 to 2010 and comprising 81 countries. As for the Technological dimension, more patents by residents increases piracy losses while the effect of R&D is the opposite (decreases piracy losses). In terms of the Educational dimension, the results show that more spending on education increase the piracy losses but, at the same time, more schooling years have the contrary effect. Concerning the Institutional dimension, nations with less corruption have lower piracy levels. Regarding the Access to Information, it seems that access to Internet diminishes the losses while the share of Internet broadband subscriptions has no effect. The results also show that, regarding the Labor dimension, employment in services has a deterrent effect while labor force with higher education and youth unemployment increases piracy losses. First published online 20 October 2015

This study examines the efficiency of tools for fighting software piracy in the conditional distributions of software piracy. Our paper examines software piracy in 99 countries over the period 1994-2010, using contemporary and non-contemporary quantile regressions. The intuition for modelling distributions contingent on existing levels of software piracy is that the effectiveness of tools against piracy may consistently decrease or increase simultaneously with the increasing levels of software piracy. Hence, blanket policies against software piracy are unlikely to succeed unless they are contingent on initial levels of software piracy and tailored differently across countries with low, medium and high levels of software piracy. Our findings indicate that GDP per capita, research and development expenditure, main intellectual property laws, multilateral treaties, bilateral treaties, World Intellectual Property Organisation treaties, money supply and respect for the rule of law have negative effects on software piracy. Equitably distributed wealth reduces software piracy, and the tendency not to indulge in software piracy because of equitably distributed wealth increases with the increasing software piracy levels. Hence, the negative degree of responsiveness of software piracy to changes in income levels is an increasing function of software piracy. Moreover, the relationships between policy instruments and software piracy display various patterns: U-shape, Kuznets-shape, S-shape and negative thresholds. A negative threshold represents negative estimates with the increasing negative magnitude throughout the conditional distributions of software piracy. We also discuss the policy implications of our study. [ABSTRACT FROM AUTHOR]

Software piracy continues to be a growing problem on a global scale. This study conducts a cross-cultural comparison of individuals' intent to pirate software using two subsamples: Jordan and U.S. respondents. Our results suggest TRA provides a strong predictive ability for our U.S. subsample, but not for our Jordanian subsample. Furthermore, while our culturally-related factors varied in their ability to moderate the relationships of TRA across cultural groups, their inclusion dramatically improved the ability to predict software pirating intentions for our Jordanian subsample. Overall, our results suggest culture plays an important role in affecting software piracy. [ABSTRACT FROM AUTHOR]

Software piracy is a modern day war between malicious software pirates and software developers. Annually, developers lose billions of dollars in revenue to piracy, making it an industry bane that must be controlled by all means. The drive for improved software protection systems has increased the complexity of both proposed and implemented schemes. Some of the methods are cost intensive in terms of development, management and hardware requirement (smart card tokens), while this may be justified for costly software applications, for low cost and basic applications by small scale developers, implementing advanced protection schemes is often economically infeasible and largely and overkill. This study presents a subtle software protection model using serial keys. The model implements a form of obfuscation by using hidden codes, encrypted functions and uses a distraction technique by diverting the attention of potential hackers to the serial key while trickily using coded strings for the actual user authentication. [ABSTRACT FROM AUTHOR]

The habituation of legal software use for students on college campuses is important because it helps future professionals exercise the rules of ethical compliance. In this action research study, over a two-year period, we investigated the effects of planned change interventions (a.k.a. organizational development efforts) on legal software use at an American business school in China. We examined correlations among the unified theory of acceptance and use of technology constructs by using the partial least square structural equation modeling technique. After obtaining the evaluative surveys from undergraduate business students (n = 215), the results indicated that the adoption rate of legal software increased from 40% to 71%, and change interventions accelerated the speed of legal software use. While performance expectancy, effort expectancy, and social influence had significant influences on behavioral intention, we found a substantial gender difference in the effect of facilitating condition on the legal software use behavior. Females are less likely to accept legal software that is mandated by the organizational policy, but they are highly influenced by the social influence. We also found out that participants accept legal software differently according to their respective year in the organization. Relatively new students are sensitive to the organizational policy whereas experienced students give more attention to the benefits of using legal software. Based on these findings, we suggest gender sensitive organizational policy and structured institutional efforts to build a software piracy free organization. [ABSTRACT FROM AUTHOR]

Software piracy is globally a major issue of using software without proper permission as enforced by the software license and agreement. Currently, software industries and organizations face a huge loss of money due to software piracy. Most of the educational institutions/organizations have also been affected from software piracy. To facilitate educational institutions regarding software piracy, it would be ideal to have a detailed study of the awareness of piracy level in education institutions for future development and to help academia to get rid of problems occur from pirated software. The present research aims to study and determine the awareness of piracy level in educational institutions. This study will eventually help academia in determination of level of piracy and awareness of pirated software. [ABSTRACT FROM AUTHOR]

This paper studies the determinants of software piracy losses along five major macroeconomic dimensions: Technological, Educational, Institutional, Access to Information and Labor force. The study was conducted based on a large dataset available from 1995 to 2010 and comprising 81 countries. As for the Technological dimension, more patents by residents increases piracy losses while the effect of R&D is the opposite (decreases piracy losses). In terms of the Educational dimension, the results show that more spending on education increase the piracy losses but, at the same time, more schooling years have the contrary effect. Concerning the Institutional dimension, nations with less corruption have lower piracy levels. Regarding the Access to Information, it seems that access to Internet diminishes the losses while the share of Internet broadband subscriptions has no effect. The results also show that, regarding the Labor dimension, employment in services has a deterrent effect while labor force with higher education and youth unemployment increases piracy losses. [ABSTRACT FROM AUTHOR]

This study aimed to corroborate the generalizability of students-based software piracy (SP) results to nonstudents groups in a Lebanese setting. A research model, grounded in the Theory of Planned Behavior (TPB), was adopted and three sets of hypotheses relating a number of factors to SP attitude, intention, and behavior were tested using a non-student sample. The results were then compared to Seleim and Khalil's (2016) students-based results. The results confirm that SP attitude, intuition, and behavior, as well as the factors influencing them, vary across the two groups. In the two samples, subjective norms (SN) influence SP attitude, and SP intention influences SP behavior. While SP attitude, perceived behavioralcontrol (PBC), and religious commitment (RC) influence students' SP intention, none of the investigated factors influence non-students' SP intention.Also, the students' fitted model has a stronger explanatory power than does the non-students' fitted model, and subsequently, the students-based results are not generalizable to non-students groups in Lebanon. These results along with the research implications, limitations, and future research are further discussed in the paper. [ABSTRACT FROM AUTHOR]

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This study examines the factors that affect a country’s level of software piracy. In addition, we conducted a panel regression to assess the roles of 13 variables on software piracy rates in 77 countries. Since political and regulatory means typically play a direct role in controlling piracy, this study reviews the endogeneity of intellectual property protection to assess its mediatory role. It was found that economic development, trade, individualism, education, country freedom, regulatory protection, and computer penetration all significantly affected the level of software piracy within each country. Economic freedom, power distance, and high-tech export/import only influenced software piracy when mediated by regulatory protection. This paper has implications for the integration of macro and micro factors related to software piracy. [ABSTRACT FROM AUTHOR]