Characterizing and Managing Intrusion Detection System (IDS) Alerts with Multi-Server/Multi-Priority Queuing Theory

The DoD sets forth an objective to employ an active cyber defense capability to prevent intrusions onto DoD networks and systems. Intrusion Detection Systems (IDS) are a critical part of network defense architectures, but their alerts can be difficult to manage. This research applies Queuing Theory to the management of IDS alerts, seeking to answer how analysts and priority schemes effect alert processing performance. To characterize the effect of these two variables on queue wait times, a MATLAB simulation was developed to allow parametric analysis under two scenarios. The first varies the number of analysts and the second varies the number of alert priority levels. Results indicate that two analysts bring about drastic improvements (a 41% decrease) in queue wait times (from 116.1 to 49.8 minutes) compared to a single analyst, due to the reduced potential for bottlenecks, with diminishing returns thereafter. In the second scenario, it was found that three priority levels are sufficient to realize the benefits of prioritization, and that a five level priority scheme did not result in shorter wait queue times for Priority 1 alerts. Queuing models offer an effective approach to make IDS resource decisions in keeping with DoD goals for Active Cyber Defense

A Heuristic Method for Task Selection in Persistent ISR Missions Using Autonomous Unmanned Aerial Vehicles

The Persistent Intelligence, Surveillance, and Reconnaissance (PISR) problem seeks to provide timely collection and delivery of data from prioritized ISR tasks using an autonomous Unmanned Aerial Vehicle (UAV). In the literature, PISR is classified as a type of Vehicle Routing Problem (VRP), often called by other names such as persistent monitoring, persistent surveillance, and patrolling. The objective of PISR is to minimize the weighted revisit time to each task (called weighted latency) using an optimal task selection algorithm. In this research, we utilize the average weighted latency as our performance metric and investigate a method for task selection called the Maximal Distance Discounted and Weighted Revisit Period (MD2WRP) utility function. The MD2WRP function is a heuristic method of task selection that uses n+1 parameters, where n is the number of PISR tasks. We develop a two-step optimization method for the MD2WRP parameters to deliver optimal latency performance for any given task configuration, which accommodates both single and multi-vehicle scenarios. To validate our optimization method, we compare the performance of MD2WRP to common Traveling Salesman Problem (TSP) methods for PISR using different task configurations. We find that the optimized MD2WRP function is competitive with the TSP methods, and that MD2WRP often results in steady-state task visit sequences that are equivalent to the TSP solution for a single vehicle. We also compare MD2WRP to other utility methods from the literature, finding thatMD2WRP performs on par with or better than these other methods even when optimizing only one of its n + 1 parameters. To address real-world operational factors, we test MD2WRP with Dubins constraints, no-y zones in the operational area, return-to-base requirements, and the addition and removal of vehicles and tasks mid-mission. For each operational factor, we demonstrate its effect on PISR task selections using MD2WRP and how MD2WRP needs to be modified, if at all, to compensate. Finally, we make practical suggestions about implementing MD2WRP for flight testing, outline potential areas for future study, and offer recommendations about the conduct of PISR missions in general

Polar ionospheric currents and high temporal resolution geomagnetic field models

Estimating high resolution models of the Earth's core magnetic field and its time variation in the polar regions requires that one can adequately account for magnetic signals produced by polar ionospheric currents, which vary on a wide range of time and length scales. Limitations of existing ionospheric field models in the challenging polar regions can adversely affect core field models, which in turn has important implications for studies of the core flow dynamics in those regions. Here we implement a new approach to co-estimate a climatological model of the ionospheric field together with a model of the internal and magnetospheric fields within the CHAOS geomagnetic field modelling framework. The parametrization of the ionospheric field exploits non-orthogonal magnetic coordinates and scales linearly with external driving parameters related to the solar wind and the interplanetary magnetic field. Using this approach we derive a new geomagnetic field model from measurements of the magnetic field collected by low Earth orbit satellites, which in addition to the internal field provides estimates of the typical current system in the polar ionosphere. We find that the time derivative of the estimated internal field is less contaminated by the polar currents, which is mostly visible in the zonal and near-zonal terms at high spherical harmonic degrees. Distinctive patches of strong secular variation at the core-mantle boundary, which have important implications for core dynamics, persist. Relaxing the temporal regularisation reveals annual oscillations, which could indicate remaining ionospheric field or related induced signals in the internal field model. Using principal component analysis we find that the annual oscillations mostly affect the zonal low-degree spherical harmonics of the internal field.Comment: 26 pages, 15 figures, 3 table

LCS-1: A High-Resolution Global Model of the Lithospheric Magnetic Field Derived from CHAMP and \u3cem\u3eSwarm\u3c/em\u3e Satellite Observations

We derive a new model, named LCS-1, of Earth’s lithospheric field based on four years (2006 September–2010 September) of magnetic observations taken by the CHAMP satellite at altitudes lower than 350 km, as well as almost three years (2014 April–2016 December) of measurements taken by the two lower Swarm satellites Alpha and Charlie. The model is determined entirely from magnetic ‘gradient’ data (approximated by finite differences): the north–south gradient is approximated by first differences of 15 s along-track data (for CHAMP and each of the two Swarm satellites), while the east–west gradient is approximated by the difference between observations taken by Swarm Alpha and Charlie. In total, we used 6.2 mio data points. The model is parametrized by 35 000 equivalent point sources located on an almost equal-area grid at a depth of 100 km below the surface (WGS84 ellipsoid). The amplitudes of these point sources are determined by minimizing the misfit to the magnetic satellite ‘gradient’ data together with the global average of |Br| at the ellipsoid surface (i.e. applying an L1 model regularization of Br). In a final step, we transform the point-source representation to a spherical harmonic expansion. The model shows very good agreement with previous satellite-derived lithospheric field models at low degree (degree correlation above 0.8 for degrees n ≤ 133). Comparison with independent near-surface aeromagnetic data from Australia yields good agreement (coherence \u3e 0.55) at horizontal wavelengths down to at least 250 km, corresponding to spherical harmonic degree n ≈ 160. The LCS-1 vertical component and field intensity anomaly maps at Earth’s surface show similar features to those exhibited by the WDMAM2 and EMM2015 lithospheric field models truncated at degree 185 in regions where they include near-surface data and provide unprecedented detail where they do not. Example regions of improvement include the Bangui anomaly region in central Africa, the west African cratons, the East African Rift region, the Bay of Bengal, the southern 90°E ridge, the Cretaceous quiet zone south of the Walvis Ridge and the younger parts of the South Atlantic

Serologic Evidence of H1 Swine Influenza Virus Infection in Swine Farm Residents and Employees

We evaluated seropositivity to swine and human H1 influenza viruses in 74 swine farm owners, employees, their family members, and veterinarians in rural south-central Wisconsin, compared with 114 urban Milwaukee, Wisconsin, residents. The number of swine farm participants with positive serum hemagglutination-inhibition (HI) antibody titers >40 to swine influenza viruses (17/74) was significantly higher (p<0.001) than the number of seropositive urban control samples (1/114). The geometric mean serum HI antibody titers to swine influenza viruses were also significantly higher (p<0.001) among the farm participants. Swine virus seropositivity was significantly (p<0.05) associated with being a farm owner or a farm family member, living on a farm, or entering the swine barn >4 days/week. Because pigs can play a role in generating genetically novel influenza viruses, swine farmers may represent an important sentinel population to evaluate the emergence of new pandemic influenza viruses

An Improved Methodology for Multidimensional High- Throughput Preformulation Characterization of Protein Conformational Stability

The Empirical Phase Diagram (EPD) technique is a vector-based multidimensional analysis method for summarizing large data sets from a variety of biophysical techniques. It can be used to provide comprehensive preformulation characterization of a macromolecule’s higher-order structural integrity and conformational stability. In its most common mode, it represents a type of stimulus-response diagram using environmental variables such as temperature, pH, and ionic strength as the stimulus, with alterations in macromolecular structure being the response. Until now EPD analysis has not been available in a high throughput mode because of the large number of experimental techniques and environmental stressor/stabilizer variables typically employed. A new instrument has been developed that combines circular dichroism, UV-absorbance, fluorescence spectroscopy and light scattering in a single unit with a 6-position temperature controlled cuvette turret. Using this multifunctional instrument and a new software system we have generated EPDs for four model proteins. Results confirm the reproducibility of the apparent phase boundaries and protein behavior within the boundaries. This new approach permits two EPDs to be generated per day using only 0.5 mg of protein per EPD. Thus, the new methodology generates reproducible EPDs in high-throughput mode, and represents the next step in making such determinations more routine

Direct measurements of CO2 flux in the Greenland Sea

During summer 2006 eddy correlation CO2 fluxes were measured in the Greenland Sea using a novel system set-up with two shrouded LICOR-7500 detectors. One detector was used exclusively to determine, and allow the removal of, the bias on CO2 fluxes due to sensor motion. A recently published correction method for the CO2-H2O cross-correlation was applied to the data set. We show that even with shrouded sensors the data require significant correction due to this cross-correlation. This correction adjusts the average CO2 flux by an order of magnitude from -6.7 x 10⁻² mol m⁻² day⁻¹ to -0.61 x 10⁻² mol m⁻² day⁻¹, making the corrected fluxes comparable to those calculated using established parameterizations for transfer velocity

Attachment, Social Support, and Perceived Mental Health of Adult Dog Walkers: What Does Age Have to Do With It?

In part of a larger pilot study of dog walking as a physical activity intervention we assessed levels of attachment, social supports, and perceived mental health of 75 dog owners, identified through a tertiary- care veterinary hospital. Owners completed the Medical Outcomes Study (MOS) Social Support Survey, mental health component of the Short-Form-12 (SF-12) Health Survey, and the Lexington Attachment to Pets Scale (LAPS). Of particular interest was that younger owners had stronger attachments to their dogs (r = -.488;p \u3c.001) and less social support (r = .269;p =.021). Our study suggests the importance of companion animals for social support, particularly for those without close friends/relatives. For younger owners, our study reveals vulnerabilities in support networks that may warrant referrals to human helping professionals. We suggest the use of Carstensen\u27s Socioemotional Selectivity Theory as an interpretive framework to underscore the importance of including companion animals as part of the human social convoy, especially in terms of providing affectionate and interactional social support