Predictive Liability Models and Visualizations of High Dimensional Retail Employee Data

Employee theft and dishonesty is a major contributor to loss in the retail industry. Retailers have reported the need for more automated analytic tools to assess the liability of their employees. In this work, we train and optimize several machine learning models for regression prediction and analysis on this data, which will help retailers identify and manage risky employees. Since the data we use is very high dimensional, we use feature selection techniques to identify the most contributing factors to an employee's assessed risk. We also use dimension reduction and data embedding techniques to present this dataset in a easy to interpret format

Portable Tor Router: Easily Enabling Web Privacy for Consumers

On-line privacy is of major public concern. Unfortunately, for the average consumer, there is no simple mechanism to browse the Internet privately on multiple devices. Most available Internet privacy mechanisms are either expensive, not readily available, untrusted, or simply provide trivial information masking. We propose that the simplest, most effective and inexpensive way of gaining privacy, without sacrificing unnecessary amounts of functionality and speed, is to mask the user's IP address while also encrypting all data. We hypothesized that the Tor protocol is aptly suited to address these needs. With this in mind we implemented a Tor router using a single board computer and the open-source Tor protocol code. We found that our proposed solution was able to meet five of our six goals soon after its implementation: cost effectiveness, immediacy of privacy, simplicity of use, ease of execution, and unimpaired functionality. Our final criterion of speed was sacrificed for greater privacy but it did not fall so low as to impair day-to-day functionality. With a total cost of roughly $100.00 USD and a speed cap of around 2 Megabits per second we were able to meet our goal of an affordable, convenient, and usable solution to increased on-line privacy for the average consumer.Comment: 6 pages, 5 figures, IEEE ICCE Conferenc

Secure and Decentralized Swarm Behavior with Autonomous Agents for Smart Cities

Unmanned Aerial Vehicles (UAVs), referenced as drones, have advanced to consumer adoption for hobby and business use. Drone applications, such as infrastructure technology, security mechanisms, and resource delivery, are just the starting point. More complex tasks are possible through the use of UAV swarms. These tasks increase the potential impacts that drones will have on smart cities, modern cities which have fully adopted technology in order to enhance daily operations as well as the welfare of it's citizens. Smart cities not only consist of static mesh networks of sensors, but can contain dynamic aspects as well including both ground and air based autonomous vehicles. Networked computational devices require paramount security to ensure the safety of a city. To accomplish such high levels of security, services rely on secure-by-design protocols, impervious to security threats. Given the large number of sensors, autonomous vehicles, and other advancements, smart cities necessitates this level of security. The SHARK protocol (Secure, Heterogeneous, Autonomous, and Rotational Knowledge for Swarms) ensures this kind of security by allowing for new applications for UAV swarm technology. Enabling drones to circle a target without a centralized control or selecting lead agents, the SHARKS protocol performs organized movement among agents without creating a central point for attackers to target. Through comparisons on the stability of the protocol in different settings, experiments demonstrate the efficiency and capacity of the SHARKS protocol.Comment: 8 pages, 1 figure, 1 chart, 8 table

Engineering Education Collaboration: Innovative Pedagogical Methods for High School and University Environmentalists

This paper presents an innovative teaching approach, how it is implemented, student response results of the implementation, and the assessment of impact on student learning. The findings are based on surveys given to the students after each lab lesson taught in partnership with university (Project STEP) and community members. The purpose of this paper is to showcase authentic molecular technology research methods that have been incorporated into a high school level water quality study in cooperation with a watershed restoration program. Typically, water quality studies focus on chemical analysis such as pH, dissolved oxygen, biochemical oxygen demand, orthophosphates, nitrates, temperature, turbidity, macro-invertebrate survey and fecal coliform cultures. This paper shows that by using molecular technology, the source of pollution in the watershed can be determined. Students in these high school science classes are engaged in authentic experiences to identify and analyze human impact on the environment and local ecosystems. Students also are able to collect and analyze data using computer and molecular technology. With help from the local watershed managers, the AP high school students filter bacteria, isolate their DNA, use the polymerase chain reaction (PCR) to amplify the DNA, and finally use gel electrophoresis to trace the DNA to its source (human, cow or intestinal bacteria). In this way, both AP and Physical Science students can extend the water quality study to trace the pollution to a point source. This is a unique approach to high school science laboratory activities. All watershed data is collected and organized using Microsoft Excel spreadsheets and graphing software. Students are able to form conclusions using technology that is used in today\u27s workplace. Initial findings regarding student response to this innovative teaching approach indicate that the actual application of molecular technology methods, employed to solve a problem with an unknown conclusion, is very meaningful to students. Unlike other traditional classroom labs, neither the teacher nor the students know what the results of the watershed tests are before-hand. This type of innovative teaching approach, supported by research on inquiry lessons, provides a more memorable experience for the students - actually performing technology that they would otherwise only read about in textbooks and articles. This paper will provide other instructors with a kind of roadmap, but one where there are experiences of many partners and students that highlight both successes and challenges

Side channel attack resistance: Migrating towards high level methods

Our world is moving towards ubiquitous networked computing with unstoppable momentum. With technology available at our every finger tip, we expect to connect quickly, cheaply, and securely on the sleekest devices. While the past four decades of design automation research has focused on making integrated circuits smaller, cheaper and quicker the past decade has drawn more attention towards security. Though security within the scope of computing is a large domain, the focus of this work is on the elimination of computationally based power byproducts from high-level device models down to physical designs and implementations The scope of this dissertation is within the analysis, attack and protection of power based side channels. Research in the field concentrates on determining, masking and/or eliminating the sources of data dependent information leakage within designs. While a significant amount of research is allocated to reducing this leakage at low levels of abstraction, significantly less research effort has gone into higher levels of abstraction. This dissertation focuses on both ends of the design spectrum while motivating the future need for hierarchical side channel resistance metrics for hardware designs. Current low level solutions focus on creating perfectly balanced standard cells through various straight-forward logic styles. Each of these existing logic styles, while enhancing side channel resistance by reducing the channels' variance, come at significant design expense in terms of area footprint, power consumption, delay and even logic style structure. The first portion of this proposal introduces a universal cell based on a dual multiplexer, implemented using a pass-transistor logic which approaches and exceeds some standard cell cost benchmarks. The proposed cell and circuit level methods shows significant improvements in security metrics over existing cells and approaches standard CMOS cell and circuit performance by reducing area, power consumption and delay. While most low level works stop at the cell level, this work also investigates the impact of environmental factors on security. On the other end of the design spectrum, existing secure architecture and algorithm research attempts to mask side channels through random noise, variable timing, instruction reordering and other similar methods. These methods attempt to obfuscate the primary source of information with side channels. Unfortunately, in most cases, the techniques are still susceptible to attack - of those with promise, most are algorithm specific. This dissertation approaches high-level security by eliminating the relationship between high level side channel models and the side channels themselves. This work discusses two different solutions targeting architecture level protection. The first, deals with the protection of Finite State Machines, while the seconds deals with protection of a class of cryptographic algorithms using Feedback Shift Registers. This dissertation includes methods for reducing the power overhead of any FSM circuit (secured or not). The solutions proposed herein render potential side channel models moot by eliminating or reducing the model's data dependent variability. Designers unwilling to compromise on a doubling of area can include some sub-optimal security to their devices

Ants Go Marching—Integrating Computer Science into Teacher Professional Development with NetLogo

There is a clear call for pre-collegiate students in the United States to become literate in computer science (CS) concepts and practices through integrated, authentic experiences and instruction. Yet, a majority of in-service and pre-service pre-collegiate teachers (instructing children aged five to 18) lack the fundamental skills and self-efficacy to adequately and effectively integrate CS into existing curricula. In this study, 30 pre-collegiate teachers who represent a wide band of experience, grade-levels, and prior CS familiarity participated in a 16-day professional development (PD) course to enhance their content knowledge and self-efficacy in integrating CS into existing lessons and curricula. Using both qualitative and quantitative methodology, a social constructivist approach guided the researchers in the development of the PD, as well as the data collection and analysis on teacher content knowledge and perceptions through a mixed-methods study. Ultimately, participants were introduced to CS concepts and practices through NetLogo, which is a popular multi-agent simulator. The results show that although the pre-collegiate teachers adopted CS instruction, the CS implementation within their curricula was limited to the activities and scope of the PD with few adaptations and minimal systemic change in implementation behaviors