Machine Learning-Based Android Malware Detection Using Manifest Permissions

The Android operating system is currently the most prevalent mobile device operating system holding roughly 54 percent of the total global market share. Due to Android’s substantial presence, it has gained the attention of those with malicious intent, namely, malware authors. As such, there exists a need for validating and improving current malware detection techniques. Automated detection methods such as anti-virus programs are critical in protecting the wide variety of Android-powered mobile devices on the market. This research investigates effectiveness of four different machine learning algorithms in conjunction with features selected from Android manifest file permissions to classify applications as malicious or benign. Case study results, on a test set consisting of 5,243 samples, produce accuracy, recall, and precision rates above 80%. Of the considered algorithms (Random Forest, Support Vector Machine, Gaussian Naïve Bayes, and K-Means), Random Forest performed the best with 82.5% precision and 81.5% accuracy

Validating the Right to Counsel

This Essay, written as part of a Symposium celebrating the 50th Anniversary of Gideon v. Wainwright, focuses on the elaboration of the Gideon right in the context of ineffective assistance of counsel litigation. First, I describe how ineffective assistance of counsel claims came to dominate and define federal habeas corpus litigation, changing the structure of state post-conviction rules in reaction to the new prominence of ineffective assistance of counsel claims at the federal level, expanding to consider assistance of counsel during plea bargaining, and raising complex questions for post-conviction courts. Despite the ubiquity of ineffective assistance of counsel claims, the constitutional test is shot through with a prejudice analysis, as well as with a set of strong substantive blinders: judgments that only certain types of failures by counsel will be regulated. Second, I ask whether the approach towards judging effectiveness of defense counsel could be “validated” by social science evidence, or at least be better informed by it. The bar has increasingly engaged with science and social science to provide improved standards for effective defense representation. In turn, social scientists might more closely study the effectiveness of defense lawyering across stages of the criminal process. Over time, this work may help to validate the right to counsel

Rule Based Forecasting [RBF] - Improving Efficacy of Judgmental Forecasts Using Simplified Expert Rules

Rule-based Forecasting (RBF) has emerged to be an effective forecasting model compared to well-accepted benchmarks. However, the original RBF model, introduced in1992, incorporates 99 production rules and is, therefore, difficult to apply judgmentally. In this research study, we present a core rule-set from RBF that can be used to inform both judgmental forecasting practice and pedagogy. The simplified rule-set, called coreRBF, is validated by asking forecasters to judgmentally apply the rules to time series forecasting tasks. Results demonstrate that forecasting accuracy from judgmental use of coreRBF is not statistically different from that reported from similar applications of RBF. Further, we benchmarked these coreRBF forecasts against forecasts from (a) untrained forecasters, (b) an expert system based on RBF, and (c) the original 1992 RBF study. Forecast accuracies were in the hypothesized direction, arguing for the generalizability and validity of the coreRBF rules

Who watches the watchers: Validating the ProB Validation Tool

Over the years, ProB has moved from a tool that complemented proving, to a development environment that is now sometimes used instead of proving for applications, such as exhaustive model checking or data validation. This has led to much more stringent requirements on the integrity of ProB. In this paper we present a summary of our validation efforts for ProB, in particular within the context of the norm EN 50128 and safety critical applications in the railway domain.Comment: In Proceedings F-IDE 2014, arXiv:1404.578

Coupled thermodynamic and biologic modelling of Legionella pneumophila proliferation in domestic hot water systems

The production of Domestic Hot Water (DHW) dominates the total energy demand. One of the main reasons for the high energy demand is that DHW is stored and distributed at temperatures above 55°C to mitigate the risk of infecting the DHW system with Legionella Pneumophila. At these temperatures, Legionella bacteria are effectively killed. For most of the applications of DHW, temperatures of only 30-40°C are required. This disparity (between 55 and 30-40°C) doubles the temperature difference between the DHW system and the environment and has a detrimental effect on the efficiency of DHW production units. A simulation model will be developed that allows to investigate the infection risk for Legionella in the design phase of a DHW system and to test the effectiveness of disinfection techniques on an infected system. In addition to the modeling work, a test rig will be built and the relevant temperature and use profiles will be measured in DHW systems of several buildings. With the thermodynamically validated model, the Legionella infection risk of 5 to 10 DHW system configurations will be assessed and new design guidelines will be proposed based on an optimization study that looks for the trade-off between infection risk and energy efficiency

ILR Research in Progress 2011-12

The production of scholarly research continues to be one of the primary missions of the ILR School. During a typical academic year, ILR faculty members published or had accepted for publication over 25 books, edited volumes, and monographs, 170 articles and chapters in edited volumes, numerous book reviews. In addition, a large number of manuscripts were submitted for publication, presented at professional association meetings, or circulated in working paper form. Our faculty's research continues to find its way into the very best industrial relations, social science and statistics journals.Research_in_Progress_2011_12.pdf: 46 downloads, before Oct. 1, 2020