Traffic Analysis Resistant Infrastructure

Network traffic analysis is using metadata to infer information from traffic flows. Network traffic flows are the tuple of source IP, source port, destination IP, and destination port. Additional information is derived from packet length, flow size, interpacket delay, Ja3 signature, and IP header options. Even connections using TLS leak site name and cipher suite to observers. This metadata can profile groups of users or individual behaviors. Statistical properties yield even more information. The hidden Markov model can track the state of protocols where each state transition results in an observation. Format Transforming Encryption (FTE) encodes data as the payload of another protocol. The emulated protocol is called the host protocol. Observation-based FTE is a particular case of FTE that uses real observations from the host protocol for the transformation. By communicating using a shared dictionary according to the predefined protocol, it can difficult to detect anomalous traffic. Combining observation-based FTEs with hidden Markov models (HMMs) emulates every aspect of a host protocol. Ideal host protocols would cause significant collateral damage if blocked (protected) and do not contain dynamic handshakes or states (static). We use protected static protocols with the Protocol Proxy--a proxy that defines the syntax of a protocol using an observation-based FTE and transforms data to payloads with actual field values. The Protocol Proxy massages the outgoing packet\u27s interpacket delay to match the host protocol using an HMM. The HMM ensure the outgoing traffic is statistically equivalent to the host protocol. The Protocol Proxy is a covert channel, a method of communication with a low probability of detection (LPD). These covert channels trade-off throughput for LPD. The multipath TCP (mpTCP) Linux kernel module splits a TCP streams across multiple interfaces. Two potential architectures involve splitting a covert channel across several interfaces (multipath) or splitting a single TCP stream across multiple covert channels (multisession). Splitting a covert channel across multiple interfaces leads to higher throughput but is classified as mpTCP traffic. Splitting a TCP flow across multiple covert channels is not as performant as the previous case, but it provides added obfuscation and resiliency. Each covert channel is independent of the others, and a channel failure is recoverable. The multipath and multisession frameworks provide independently address the issues associated with covert channels. Each tool addresses a challenge. The Protocol Proxy provides anonymity in a setting were detection could have critical consequences. The mpTCP kernel module offers an architecture that increases throughput despite the channel\u27s low-bandwidth restrictions. Fusing these architectures improves the goodput of the Protocol Proxy without sacrificing the low probability of detection

First principles predictions of thermophysical properties of refrigerant mixtures

We present pair potentials for fluorinated methanes and their dimers with CO2 based on ab initio potential energy surfaces. These potentials reproduce the experimental second virial coefficients of the pure fluorinated methanes and their mixtures with CO2 without adjustment. Ab initio calculations on trimers are used to model the effects of nonadditive dispersion and induction. Simulations using these potentials reproduce the experimental phase-coexistence properties of CH3F within 10% over a wide range of temperatures. The phase coexistence curve of the mixture of CH2F2 and CO2 is reproduced with an error in the mole fractions of both phases of less than 0.1. The potentials described here are based entirely on ab initio calculations, with no empirical fits to improve the agreement with experiment

Utilization of deep learning to quantify fluid volume of neovascular age-related macular degeneration patients based on swept-source OCT imaging: The ONTARIO study.

PURPOSE: To evaluate the predictive ability of a deep learning-based algorithm to determine long-term best-corrected distance visual acuity (BCVA) outcomes in neovascular age-related macular degeneration (nARMD) patients using baseline swept-source optical coherence tomography (SS-OCT) and OCT-angiography (OCT-A) data. METHODS: In this phase IV, retrospective, proof of concept, single center study, SS-OCT data from 17 previously treated nARMD eyes was used to assess retinal layer thicknesses, as well as quantify intraretinal fluid (IRF), subretinal fluid (SRF), and serous pigment epithelium detachments (PEDs) using a novel deep learning-based, macular fluid segmentation algorithm. Baseline OCT and OCT-A morphological features and fluid measurements were correlated using the Pearson correlation coefficient (PCC) to changes in BCVA from baseline to week 52. RESULTS: Total retinal fluid (IRF, SRF and PED) volume at baseline had the strongest correlation to improvement in BCVA at month 12 (PCC = 0.652, p = 0.005). Fluid was subsequently sub-categorized into IRF, SRF and PED, with PED volume having the next highest correlation (PCC = 0.648, p = 0.005) to BCVA improvement. Average total retinal thickness in isolation demonstrated poor correlation (PCC = 0.334, p = 0.189). When two features, mean choroidal neovascular membranes (CNVM) size and total fluid volume, were combined and correlated with visual outcomes, the highest correlation increased to PCC = 0.695 (p = 0.002). CONCLUSIONS: In isolation, total fluid volume most closely correlates with change in BCVA values between baseline and week 52. In combination with complimentary information from OCT-A, an improvement in the linear correlation score was observed. Average total retinal thickness provided a lower correlation, and thus provides a lower predictive outcome than alternative metrics assessed. Clinically, a machine-learning approach to analyzing fluid metrics in combination with lesion size may provide an advantage in personalizing therapy and predicting BCVA outcomes at week 52

Fungal diversity regulates plant-soil feedbacks in temperate grassland

Feedbacks between plants and soil microbial communities play an important role in vegetation dynamics, but the underlying mechanisms remain unresolved. Here, we show that the diversity of putative pathogenic, mycorrhizal, and saprotrophic fungi is a primary regulator of plant-soil feedbacks across a broad range of temperate grassland plant species. We show that plant species with resource-acquisitive traits, such as high shoot nitrogen concentrations and thin roots, attract diverse communities of putative fungal pathogens and specialist saprotrophs, and a lower diversity of mycorrhizal fungi, resulting in strong plant growth suppression on soil occupied by the same species. Moreover, soil properties modulate feedbacks with fertile soils, promoting antagonistic relationships between soil fungi and plants. This study advances our capacity to predict plant-soil feedbacks and vegetation dynamics by revealing fundamental links between soil properties, plant resource acquisition strategies, and the diversity of fungal guilds in soil

Ultra-endurance athletic performance suggests that energetics drive human morphological thermal adaptation

Both extinct and extant hominin populations display morphological features consistent with Bergmann's and Allen's Rules. However, the functional implications of the morphologies described by these ecological laws are poorly understood. We examined this through the lens of endurance running. Previous research concerning endurance running has focused on locomotor energetic economy. We considered a less-studied dimension of functionality, thermoregulation. The performance of male ultra-marathon runners (n = 88) competing in hot and cold environments was analysed with reference to expected thermoregulatory energy costs and the optimal morphologies predicted by Bergmann's and Allen's Rules. Ecogeographical patterning supporting both principles was observed in thermally challenging environments. Finishers of hot-condition events had significantly longer legs than finishers of cold-condition events. Furthermore, hot-condition finishers had significantly longer legs than those failing to complete hot-condition events. A degree of niche-picking was evident; athletes may have tailored their event entry choices in accordance with their previous race experiences. We propose that the interaction between prolonged physical exertion and hot or cold climates may induce powerful selective pressures driving morphological adaptation. The resulting phenotypes reduce thermoregulatory energetic expenditure, allowing diversion of energy to other functional outcomes such as faster running

Applying systematic review methods to studies of people’s views: an example from public health research

Methods for systematic reviews are well developed for trials, but not for non-experimental or qualitative research. This paper describes the methods developed for reviewing research on people’s perspectives and experiences (‘‘views’’ studies) alongside trials within a series of reviews on young people’s mental health, physical activity, and healthy eating. Reports of views studies were difficult to locate; could not easily be classified as ‘‘qualitative’’ or ‘‘quantitative’’; and often failed to meet seven basic methodological reporting standards used in a newly developed quality assessment tool. Synthesising views studies required the adaptation of qualitative analysis techniques. The benefits of bringing together views studies in a systematic way included gaining a greater breadth of perspectives and a deeper understanding of public health issues from the point of view of those targeted by interventions. A systematic approach also aided reflection on study methods that may distort, misrepresent, or fail to pick up people’s views. This methodology is likely to create greater opportunities for people’s own perspectives and experiences to inform policies to promote their health