Quantifying DNS namespace influence

Name resolution using the Domain Name System (DNS) is integral to today’s Internet. The resolution of a domain name is often dependent on namespace outside the control of the domain’s owner. In this article we review the DNS protocol and several DNS server implementations. Based on our examination, we propose a formal model for analyzing the name dependencies inherent in DNS. Using our name dependency model we derive metrics to quantify the extent to which domain names affect other domain names. It is found that under certain conditions, more than half of the queries for a domain name are influenced by namespaces not expressly configured by administrators. This result serves to quantify the degree of vulnerability of DNS due to dependencies that administrators are unaware of. When we apply metrics from our model to production DNS data, we show that the set of domains whose resolution affects a given domain name is much smaller than previously thought. However, behaviors such as using cached addresses for querying authoritative servers and chaining domain name aliases increase the number and diversity of influential domains, thereby making the DNS infrastructure more vulnerable.     

Influence of Amorphous Grain Boundary Phases on the Superplastic Behavior of 3-mol%-Yttria-Stabilized Tetragonal Zirconia Polycrystals (3Y-TZP)

Amorphous silicate grain boundary phases of varying chemistry and amounts were added to 3Y-TZP in order to determine their influence on the superplastic behavior between 1200° and 1300°C and on the room-temperature mechanical properties. Strain rate enhancement at high temperatures was observed in 3Y-TZP containing a glassy grain boundary phase, even with as little as 0.1 wt% glass. Strain rate enhancement was greatest in 3Y-TZP with 5 wt% glass, but the room-temperature hardness, elastic modulus, and fracture toughness were degraded. The addition of glassy grain boundary phases did not significantly affect the stress exponent of 3Y-TZP, but did lower the activation energy for superplastic flow. Strain rate enhancement was highest in samples containing the grain boundary phase with the highest solubility for Y₂O₃ and ZrO₂, but the strain rate did not scale inversely with the viscosity of the silicate phases. Grain boundary sliding accommodated by diffusional creep controlled by an interface reaction is proposed as the mechanism for superplastic deformation in 3Y-TZP with and without glassy grain boundary phases.     

An industrial study of applying input space partitioning to test financial calculation engines

This paper presents results from an industrial study that applied input space partitioning and semi-automated requirements modeling to large-scale industrial software, specifically financial calculation engines. Calculation engines are used in financial service applications such as banking, mortgage, insurance, and trading to compute complex, multi-conditional formulas to make high risk financial decisions. They form the heart of financial applications, and can cause severe economic harm if incorrect. Controllability and observability of these calculation engines are low, so robust and sophisticated test methods are needed to ensure the results are valid. However, the industry norm is to use pure human-based, requirements-driven test design, usually with very little automation. The Federal Home Loan Mortgage Corporation (FHLMC), commonly known as Freddie Mac, concerned that these test design techniques may lead to ineffective and inefficient testing, partnered with a university to use high quality, sophisticated test design on several ongoing projects. The goal was to determine if such test design can be cost-effective on this type of critical software. In this study, input space partitioning, along with automation, were applied with the help of several special-purpose tools to validate the effectiveness of input space partitioning. Results showed that these techniques were far more effective (finding more software faults) and more efficient (requiring fewer tests and less labor), and the managers reported that the testing cycle was reduced from five human days to 0.5. This study convinced upper management to begin infusing this approach into other software development projects.     

Comparison of two scaling approaches for the development of biomechanical multi-body human models

Dimensional scaling approaches are widely used to develop multi-body human models in injury biomechanics research. Given the limited experimental data for any particular anthropometry, a validated model can be scaled to different sizes to reflect the biological variance of population and used to characterize the human response. This paper compares two scaling approaches at the whole-body level: one is the conventional mass-based scaling approach which assumes geometric similarity; the other is the structure-based approach which assumes additional structural similarity by using idealized mechanical models to account for the specific anatomy and expected loading conditions. Given the use of exterior body dimensions and a uniform Young’s modulus, the two approaches showed close values of the scaling factors for most body regions, with 1.5 % difference on force scaling factors and 13.5 % difference on moment scaling factors, on average. One exception was on the thoracic modeling, with 19.3 % difference on the scaling factor of the deflection. Two 6-year-old child models were generated from a baseline adult model as application example and were evaluated using recent biomechanical data from cadaveric pediatric experiments. The scaled models predicted similar impact responses of the thorax and lower extremity, which were within the experimental corridors; and suggested further consideration of age-specific structural change of the pelvis. Towards improved scaling methods to develop biofidelic human models, this comparative analysis suggests further investigation on interior anatomical geometry and detailed biological material properties associated with the demographic range of the population.     

Testing Forecast Accuracy of Foreign Exchange Rates: Predictions from Feed Forward and Various Recurrent Neural Network Architectures

In this research, we work with data of futures contracts on foreign exchange rates for British pound (BP), Canadian dollar (CD), and Japanese yen (JY) that are traded at the Chicago Mercantile Exchange (CME) against US dollars. We model relationships between exchange rates in these currencies using linear models, feed forward artificial neural networks (ANN), and three versions of recurrent neural networks (RNN1, RNN2 and RNN3) for predicting exchange rates in these currencies against the US dollar. Our results on forecast evaluations based on AGS test the tests of forecast equivalence between any two competing models among the entire models employed for each of the series show that ANN and the three versions of RNN models offer superior forecasts for predicting BP, CD and JY exchange rates although the forecast evaluations based on MGN test are in sharp contrast. On the other hand forecast based on SIGN test shows that ANN and all the versions of RNN models offer superior forecasts for BP and CD in exception of JY exchange rates. The results for forecast evaluation for all the models for each of the series based on summary measures of forecast evaluations show that RNN3 model appears to offer the most accurate predictions of BP and RNN1 for JP exchange rates. However, none of the RNN models appear to be statistically superior to the benchmark (i.e., linear model) for predicting CD exchange rates.      

An Investigation of Cheating in Online Games

Cheating is rampant in current gameplay on the Internet. However, it isn't as well understood as we might expect. The authors summarize the various known methods of cheating and define a taxonomy of online game cheating with respect to the underlying vulnerability, consequence, and cheating principal. This taxonomy provides a systematic introduction to the characteristics of cheats in online games and how they can arise. Although cheating in online games is largely due to various security failures, the four traditional aspects of security—confidentiality, integrity, availability, and authenticity—are insufficient to explain it. Instead, fairness becomes a vital additional aspect, and its enforcement provides a convincing perspective for understanding security techniques' role in developing and operating online games.