A Deep Learning Approach for Malware and Software Piracy Threat Detection

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%.

Comparative analysis on different software piracy prevention techniques

Numerous type of software piracy known today, have several prevention techniques which has been established against them. Although, different software piracy techniques have been established, but the choice of which one should be the best to develop any software is the challenge for most software developers. Consequently, example of the types of piracy in software development can be categorise as follows: cracks and serials, softlifting and hard disk loading, internet piracy and software forging, mischaneling, reverse engineering, and tampering. We have several types of prevention techniques which aimed to resolved piracy in software development, although the methods have been wrecked. In this work a critical analysis has been carryout on different software piracy techniques and a simple model software was designed using the best technique to validate the results of the analysis.

Perceived Formal and Informal Sanctions in Deterring Cybercrime in a College Sample

The threat of formal sanctions is the criminal justice system’s primary tool to discourage online and offline deviant behavior. Yet, scholars have expressed strong concerns about the effectiveness of formal sanctions to deter cybercrime. Even more surprising is the sparsity of deterrence research in the cybercrime literature. This study examined the effects of perceived formal and informal sanctions on digital piracy, computer hacking, and online harassment in a large American college sample. Perceived formal sanctions was negatively correlated with software piracy, media piracy, password cracking, accessing accounts, sending mean messages privately online, and posting mean messages. Higher levels of perceived formal sanctions did not significantly predict any form of cybercrime, however, when controlling for informal sanctions and deviant peer associations. The implications of the findings for our ability to deter deviant behavior in cyberspace are explored.

Intellectual Property Regulation, and Software Piracy, a Predictive Model

In recent years, a number of studies have considered the impact of IPRs on software piracy, specifically TRIPS and more recently U.S. USTR 301 reporting, pursuant to the Trade Act. The work of Shadlen (2005) supports the assertion that a number of recent IPR reforms directly influence rates of copyright infringement. Shadlen (2005) is a significant study into the impact of the IPRs such as TRIPS, Out of Cycle reviews and USTR 301 reporting on software piracy. The study identified a number of key IPR reforms and sought to determine the impact of IPR reform differentials on observed piracy rates. The current study extends upon Shadlen (2005), comparing the pooled panel model framework to an alternative model of prediction, a backward propagation, multilayer perceptron network model. The analysis conducted herein focuses specifically on ASEAN member countries. The study employs the Garson (1991) and Goh (1995) methods of independent variable analysis to offer further insight into relative importance of the IPR reform variables.

Software Piracy Awareness, Policy, and User Perspective in Educational Institutions

Software theft and piracy are rapidly ever-increasing problems of the present-day software industry. Software piracy is the illegal copy and use of software in a way other than that is officially documented by exclusive rights of the developer in the form of an individual or organization as described in the relevant sale agreement (license). Owing to the evolution in software development and Internet, software piracy has become a main concern for many software companies. Software companies are confronted with extremely high losses due to the piracy of software. Pirates achieve a lot of money by doing business with pirated software. General end-users of the software are not aware of this serious crime and of the legal consequences of breaking the law. Even most of the time, end-users and consumers think that it is none of their concern and not an important issue for them. Although, in reality, if an organization is working with pirated software, there is a risk of failure of the software, and it might put their organization at risk as pirated software does not receive any support from the development organization. This ultimately puts the consumer organization in huge financial loss. Due to these reasons, software piracy has turned out to be a major concern, more emergent due to the extravagant development of the software industry and the availability of software(s) on the Internet. In this paper, we analyzed and identified the ratio of software piracy, awareness regarding piracy, and the policy of the licensed software provided. Based on the results of the study, some suggestions are proposed by which the level of piracy can be reduced.

Modelling Features-Based Birthmarks for Security of End-to-End Communication System

Feature-based software birthmark is an essential property of software that can be used for the detection of software theft and many other purposes like to assess the security in end-to-end communication systems. Research on feature-based software birthmark shows that using the feature-based software birthmark joint with the practice of software birthmark estimation together can deliver a right and influential method for detecting software piracy and the amount of piracy done by a software. This can also guide developers in improving security of end-to-end communication system. Modern day software industry and systems are in demand to have an unbiased method for comparing the features-based birthmark of software competently, and more concretely for the detecting software piracy and assessing the security of end-to-end communication systems. In this paper, we proposed a mathematical model, which is based on a differential system, to present feature-based software birthmark. The model presented in this paper provides an exclusive way for the features-based birthmark of software and then can be used for comparing birthmark and assessing security of end-to-end communication systems. The results of this method show that the proposed model is efficient in terms of effectiveness and correctness for the features-based software birthmark comparison and security assessment purposes.

Software Piracy in Nigeria

The enormity of software piracy varies in different countries and Nigeria is not an exception. Software piracy occurs in diverse forms such as soft lifting, hard disk loading, counterfeiting and unauthorized renting. Many reasons are behind software piracy. Software piracy has many negative economic consequences: Competition distorted by pirated software at the expense of local industries, loss of tax revenue and jobs because of the lack of a legitimate market, increase in cost recovery which, overall, affects social well-being of the citizenry. Findings have revealed that Nigeria has the highest case of software piracy, intellectual property theft and other sharp practices in the IT industry in Africa. Hence, this work investigates software piracy in Nigeria; revealing the concepts, causes, effects; and proffered solutions. We adopted the descriptive survey design. The research instrument used was online questionnaire with a sample size of 3270 people drawn from a population of respondents from the six (6) Geopolitical Zones of Nigeria. The results show that software piracy has statistically significant effect on the economy of Nigeria and that high standard of living is the biggest cause of software piracy in Nigeria.