The Multi-Generation Repackaging Hypothesis

App repackaging is a common threat in the Android ecosystem. To face this threat, the literature now includes a large body of work proposing approaches for identifying repackaged apps. Unfortunately, although most research involves pairwise similarity comparison to distinguish repackaged apps from their “original” counterparts, no work has considered the threat to validity of not being able to discover the true original apps. We provide in this paper preliminary insights of an investigation into the Multi-Generation Repackaging Hypothesis: is the original in a repackaging process the outcome of a previous repackaging process? Leveraging the Androzoo dataset of over 5 million Android apps, we validate this hypothesis in the wild, calling upon the community to take this threat into account in new solutions for repackaged app detection

Repackaging Louisiana’s Crawfish Production and Marketing to Generate Revenue and Employment

Louisiana accounts for 90% to 95% of the total U.S. production of Crawfish from year to year, either from wild waters of the state, or on farms. Even though, the commercial sales of crawfish in Louisiana date back to the late 1800s—the state is still actively engaged in crawfish industry to provide millions of pounds harvested from farms and natural waterways in the Bayou State. The harvesting of wild crawfish from natural habitats such as bayous, swamps and marshes provides a significant number of jobs for Louisiana residents. The Atchafalaya Basin is world famous for its crawfish production. More than 800 commercial fishermen harvest crawfish from wetlands, mostly in the Atchafalaya Basin. The governor making an attempt to set the favorable environment and also give incentives to the crawfish farmers may boost its production to add to the GDP of the economy. Because revenue generation and employment diversification are very critical to the state of Louisiana, this particular study is devoted to unearth the numerous repackaging techniques for Louisiana crawfish production and its marketing strategies to assist the state in diversifying or broaden its revenue base and employment avenues to ensure growth and development. As a result the study used 200 sample size of crawfish farmers across the state of Louisiana. To better inform policymakers, the study used binomial logistic regression to analyze the perceived determinants of crawfish production in Louisiana. The study found out that the Louisiana State can diversify its marketing strategies to employ more people to work on the promotion of the crawfish production in the state of Louisiana. The following marketing strategies (deployment, channel management, contact database, email marketing, event triggered actions, lead management, multi-campaign and the use of social media platform) revealed in the study to assist the state of Louisiana to improve upon it employment avenues through sales and also expected to generate more revenue for the state through taxes. The study reveals that crawfish farmers continue to be in business due to the following factors: price/profit, government regulations, transport assistance, and the market trends/demand for the product. The study further revealed that repackaging the Louisiana crawfish farming will lead to revenue generation, employment creation, cultural enrichment & promotion and also improve upon the export earnings associated with crawfish products. Above all, the study strongly recommends that the governors and the federal government should support the repackaging of the old marketing tools used by the farmers to adapt to the modern forms of sales-marketing in order to enhance more jobs creation and also promote the sales of the crawfish products to boost the nation’s GDP and revenue generation. Keywords: Employment, Revenue, Crawfish, Logistic Regression, Regulations, Sales, Cultural, and Transport DOI: 10.7176/JESD/11-12-05 Publication date:June 30th 202

mSpace Mobile: Exploring Support for Mobile Tasks

In the following paper we compare two Web application interfaces, mSpace Mobile and Google Local in supporting location discovery tasks on mobile devices while stationary and while on the move. While mSpace Mobile performed well in both stationary and mobile conditions, performance in Google Local dropped significantly. We postulate that mSpace Mobile performed so well because it breaks the paradigm of the page for delivering Web content, thereby enabling new and more powerful interfaces to be used to support mobility

Do Stronger Patents Induce More Innovation? Evidence from the 1988 Japanese Patent Law Reforms

Does an expansion of patent scope induce more innovative effort by firms? This article provides evidence on this question by examining firm responses to the Japanese patent reforms of 1988. Interviews with practitioners suggest the reforms significantly expanded the scope of patent rights in Japan, but that the average response in terms of additional R&D effort and innovative output was quite modest. Interviews also suggest that firm organizational structure is an important determinant of the level of response. Econometric analysis using Japanese and U.S. patent data on 307 Japanese firms confirms that the magnitude of the response is quite small.

Delving into Android Malware Families with a Novel Neural Projection Method

[Abstract] Present research proposes the application of unsupervised and supervised machine-learning techniques to characterize Android malware families. More precisely, a novel unsupervised neural-projection method for dimensionality-reduction, namely, Beta Hebbian Learning (BHL), is applied to visually analyze such malware. Additionally, well-known supervised Decision Trees (DTs) are also applied for the first time in order to improve characterization of such families and compare the original features that are identified as the most important ones. The proposed techniques are validated when facing real-life Android malware data by means of the well-known and publicly available Malgenome dataset. Obtained results support the proposed approach, confirming the validity of BHL and DTs to gain deep knowledge on Android malwar

Delving into Android Malware Families with a Novel Neural Projection Method

Present research proposes the application of unsupervised and supervised machine-learning techniques to characterize Android malware families. More precisely, a novel unsupervised neural-projection method for dimensionality-reduction, namely, Beta Hebbian Learning (BHL), is applied to visually analyze such malware. Additionally, well-known supervised Decision Trees (DTs) are also applied for the first time in order to improve characterization of such families and compare the original features that are identified as the most important ones. The proposed techniques are validated when facing real-life Android malware data by means of the well-known and publicly available Malgenome dataset. Obtained results support the proposed approach, confirming the validity of BHL and DTs to gain deep knowledge on Android malware.This work is partially supported by Instituto Nacional de Ciberseguridad (INCIBE) and developed by Research Institute of Applied Sciences in Cybersecurity (RIASC)

Embedded Foundations: Advancing Community Change and Empowerment

· Embedded funders are foundations that have made long-term commitments to the communities in which they are located or work. · Foundations have a long history in funding community development, often with few concrete results. · Political conditions, the increasing divide between rich and poor, inaccessibility of education, lack of housing, and continued segregation and racial discrimination are issues that need be addressed concurrently and resources need to be drawn from a variety of sources, particularly the neighborhoods themselves. This complexity has created an impetus for embedded philanthropy. · Embedded funders work participatively with the community and frame evaluations in less theoretical, more actionable ways. · While the future of embedded philanthropy remains to be seen, there is now a group of funders committed to this way of working