A Quantitative Study of Advanced Encryption Standard Performance as it Relates to Cryptographic Attack Feasibility

The advanced encryption standard (AES) is the premier symmetric key cryptosystem in use today. Given its prevalence, the security provided by AES is of utmost importance. Technology is advancing at an incredible rate, in both capability and popularity, much faster than its rate of advancement in the late 1990s when AES was selected as the replacement standard for DES. Although the literature surrounding AES is robust, most studies fall into either theoretical or practical yet infeasible. This research takes the unique approach drawn from the performance field and dual nature of AES performance. It uses benchmarks to assess the performance potential of computer systems for both general purpose and AES. Since general performance information is readily available, the ratio may be used as a predictor for AES performance and consequently attack potential. The design involved distributing USB drives to facilitators containing a bootable Linux operating system and the benchmark instruments. Upon boot, these devices conducted the benchmarks, gathered system specifications, and submitted them to a server for regression analysis. Although it is likely to be many years in the future, the results of this study may help better predict when attacks against AES key lengths will become feasible

WHAT ABOUT THE WIZARD?: STRESS EFFECTS OF BEING A MENTOR

The purpose of the current study was to examine the influence of negative mentoring, trust and protégé learning on mentor job stress. Surveys were submitted to protégés who identified mentors, who then received mentor-specific surveys. Matched data from mentor- protégé surveys were analyzed using structural equation modeling (SEM). Results support previous research regarding the importance of trust in mentoring relationships and suggest the significance of protégé-perceived personal learning on mentor stress. Further, results suggest that mentor and protégé experiences could be assessed with a single dyadic measure. Additionally, a new measurement instrument to assess mentoring stressors was developed through qualitative research to develop the construct of mentoring stress. To further expand the exploration of the mentor stress construct, mentors were tested through response to the developed measure. Results present psychometric support for the measure as a potential tool to examine mentor stress. Implications for future research and for practitioners managing formal mentoring programs are also presented

Category Learning Research in the Interactive Online Environment Second Life

The interactive online environment Second Life allows users to create novel three-dimensional stimuli that can be manipulated in a meaningful yet controlled environment. These features suggest Second Life's utility as a powerful tool for investigating how people learn concepts for unfamiliar objects. The first of two studies was designed to establish that cognitive processes elicited in this virtual world are comparable to those tapped in conventional settings by attempting to replicate the established finding that category learning systematically influences perceived similarity . From the perspective of an avatar, participants navigated a course of unfamiliar three-dimensional stimuli and were trained to classify them into two labeled categories based on two visual features. Participants then gave similarity ratings for pairs of stimuli and their responses were compared to those of control participants who did not learn the categories. Results indicated significant compression, whereby objects classified together were judged to be more similar by learning than control participants, thus supporting the validity of using Second Life as a laboratory for studying human cognition. A second study used Second Life to test the novel hypothesis that effects of learning on perceived similarity do not depend on the presence of verbal labels for categories. We presented the same stimuli but participants classified them by selecting between two complex visual patterns designed to be extremely difficult to label. While learning was more challenging in this condition , those who did learn without labels showed a compression effect identical to that found in the first study using verbal labels. Together these studies establish that at least some forms of human learning in Second Life parallel learning in the actual world and thus open the door to future studies that will make greater use of the enriched variety of objects and interactions possible in simulated environments compared to traditional experimental situations

Group-size-mediated habitat selection and group fusion-fission dynamics of bison under predation risk

For gregarious animals the cost-benefit trade-offs that drive habitat selection may vary dynamically with group size, which plays an important role in foraging and predator avoidance strategies. We examined how habitat selection by bison (Bison bison) varied as a function of group size and interpreted these patterns by testing whether habitat selection was more strongly driven by the competing demands of forage intake vs. predator avoidance behavior. We developed an analytical framework that integrated group size into resource selection functions (RSFs). These group-size-dependent RSFs were based on a matched casecontrol design and were estimated using conditional logistic regression (mixed and populationaveraged models). Fitting RSF models to bison revealed that bison groups responded to multiple aspects of landscape heterogeneity and that selection varied seasonally and as a function of group size. For example, roads were selected in summer, but not in winter. Bison groups avoided areas of high snow water equivalent in winter. They selected areas composed of a large proportion of meadow area within a 700-m radius, and within those areas, bison selected meadows. Importantly, the strength of selection for meadows varied as a function of group size, with stronger selection being observed in larger groups. Hence the bison-habitat relationship depended in part on the dynamics of group formation and division. Group formation was most likely in meadows. In contrast, risk of group fission increased when bison moved into the forest and was higher during the time of day when movements are generally longer and more variable among individuals. We also found that stronger selection for meadows by large rather than small bison groups was caused by longer residence time in individual meadows by larger groups and that departure from meadows appears unlikely to result from a depression in food intake rate. These group-size-dependent patterns were consistent with the hypothesis that avoidance of predation risk is the strongest driver of habitat selection

So Good It Has to Be True: Wishful Thinking in Theory of Mind

In standard decision theory, rational agents are objective, keeping their beliefs independent from their desires. Such agents are the basis for current computational models of Theory of Mind (ToM), but the accuracy of these models are unknown. Do people really think that others do not let their desires color their beliefs? In two experiments we test whether people think that others engage in wishful thinking. We find that participants do think others believe that desirable events are more likely to happen, and that undesirable ones are less likely to happen. However, these beliefs are not well calibrated as people do not let their desires influence their beliefs in the task. Whether accurate or not, thinking that others wishfully think has consequences for reasoning about them. We find one such consequence—people learn more from an informant who thinks an event will happen despite wishing it was otherwise. People’s ToM therefore appears to be more nuanced than the current rational accounts in that it allows other’s desires to directly affect their subjective probability of an event

Establishing the link between habitat selection and animal population dynamics

Although classical ecological theory (e.g., on ideal free consumers) recognizes the potential effect of population density on the spatial distribution of animals, empirical species distribution models assume that species–habitat relationships remain unchanged across a range of population sizes. Conversely, even though ecological models and experiments have demonstrated the importance of spatial heterogeneity for the rate of population change, we still have no practical method for making the connection between the makeup of real environments, the expected distribution and fitness of their occupants, and the long-term implications of fitness for population growth. Here, we synthesize several conceptual advances into a mathematical framework using a measure of fitness to link habitat availability/selection to (density-dependent) population growth in mobile animal species. A key feature of this approach is that it distinguishes between apparent habitat suitability and the true, underlying contribution of a habitat to fitness, allowing the statistical coefficients of both to be estimated from multiple observation instances of the species in different environments and stages of numerical growth. Hence, it leverages data from both historical population time series and snapshots of species distribution to predict population performance under environmental change. We propose this framework as a foundation for building more realistic connections between a population's use of space and its subsequent dynamics (and hence a contribution to the ongoing efforts to estimate a species' critical habitat and fundamental niche). We therefore detail its associated definitions and simplifying assumptions, because they point to the framework's future extensions. We show how the model can be fit to data on species distributions and population dynamics, using standard statistical methods, and we illustrate its application with an individual-based simulation. When contrasted with nonspatial population models, our approach is better at fitting and predicting population growth rates and carrying capacities. Our approach can be generalized to include a diverse range of biological considerations. We discuss these possible extensions and applications to real data

Blockchain for Power Grids

Sharing information is an important part of regulating and maintaining efficient and safe power grids. This project’s goal is to develop a way of using blockchain technology to share transaction information among different power grids in a secure, controlled, monitored, and efficient manner. The biggest concern regarding the data is integrity. By leveraging blockchain technology, the data will be reliable and resilient to attacks, such as man-in-the-middle and data spoofing attacks. The Hyperledger Fabric implementation provides a permissioned network in which power grids will act as nodes that maintain ledger information. By using a distributed ledger to validate transactions through the process of consensus, the system can share information in a manner that is more secure and transparent than traditional information sharing systems in which data is less secure and takes longer to validate. The additional layers of security and speed that Hyperledger technology provides help to prevent issues, such as power grid failures, that could stem from the latency or integrity issues involved with traditional methods of validating, processing, and reacting to shared data