Detecting Hardware-assisted Hypervisor Rootkits within Nested Virtualized Environments

Virtual machine introspection (VMI) is intended to provide a secure and trusted platform from which forensic information can be gathered about the true behavior of malware within a guest. However, it is possible for malware to escape a guest into the host and for hypervisor rootkits, such as BluePill, to stealthily transition a native OS into a virtualized environment. This research examines the effectiveness of selected detection mechanisms against hardware-assisted virtualization rootkits (HAV-R) within a nested virtualized environment. It presents the design, implementation, analysis, and evaluation of a hypervisor rootkit detection system which exploits both processor and translation lookaside buffer-based mechanisms to detect hypervisor rootkits within a variety of nested virtualized systems. It evaluates the effects of different types of virtualization on hypervisor rootkit detection and explores the effectiveness in-guest HAV-R obfuscation efforts. The results provide convincing evidence that the HAV-Rs are detectable in all SVMI scenarios examined, regardless of HAV-R or virtualization type. Also, that the selected detection techniques are effective at detection of HAV-R within nested virtualized environments, and that the type of virtualization implemented in a VMI system has minimal to no effect on HAV-R detection. Finally, it is determined that in-guest obfuscation does not successfully obfuscate the existence of HAV-R

Renal replacement therapy in acute kidney injury: controversy and consensus

Renal replacement therapies (RRTs) represent a cornerstone in the management of severe acute kidney injury. This area of intensive care and nephrology has undergone significant improvement and evolution in recent years. Continuous RRTs have been a major focus of new technological and treatment strategies. RRT is being used increasingly in the intensive care unit, not only for renal indications but also for other organ-supportive strategies. Several aspects related to RRT are now well established, but others remain controversial. In this review, we review the available RRT modalities, covering technical and clinical aspects. We discuss several controversial issues, provide some practical recommendations, and where possible suggest a research agenda for the future

Evaluating the Long-Term (Three Year) Durability of Brief Interventions Targeting Risk Factors For Psychopathology

Despite their brevity, prior work indicates that computer-based interventions can substantially impact risk factors for psychopathology including anxiety sensitivity (AS), thwarted belongingness (TB), and perceived burdensomeness (PB). However, very few studies have assessed the long-term (\u3e 1 year) effects of these interventions. The primary aim of the current study was to evaluate post-hoc, the long-term (3 year) durability of brief interventions targeting risk factors for anxiety and mood psychopathology using data from a pre-registered randomized clinical trial. Moreover, we were interested in evaluating whether mitigation in these risk factors mediated long-term symptom change. A sample determined to be at-risk for anxiety and mood pathology based on elevations on several risk factors (N = 303) was randomly assigned to one of four experimental conditions focused on: (1) reducing TB and PB; (2) reducing AS, (3) reducing TB,PB, and AS; or (4) a repeated contact control condition. Participants were assessed at post-intervention, one, three, six, 12, and 36 month follow-ups. Participants in the active treatment conditions showed sustained reductions in AS and PB through long-term follow-up. Mediation analyses suggested that reductions in AS mediated long-term reductions in anxiety and depression symptoms. These findings suggest that brief and scalable risk reduction protocols have long-term durability and efficacy both in terms of reducing risk factors for psychopathology

Cosmic evolution of radio-AGN feedback: confronting models with data

© 2022 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Radio-mode feedback is a key ingredient in galaxy formation and evolution models, required to reproduce the observed properties of massive galaxies in the local Universe. We study the cosmic evolution of radio-active galactic nuclei (AGN) feedback out to z ∼ 2.5 using a sample of 9485 radio-excess AGN. We combine the evolving radio luminosity functions with a radio luminosity scaling relationship to estimate AGN jet kinetic powers and derive the cosmic evolution of the kinetic luminosity density, Ωkin (i.e. the volume-averaged heating output). Compared to all radio-AGN, low-excitation radio galaxies dominate the feedback activity out to z ∼ 2.5, with both these populations showing a constant heating output of Ωkin≈(4−5)×1032WMpc−3Ωkin≈(4−5)×1032WMpc−3 across 0.5 < z < 2.5. We compare our observations to predictions from semi-analytical and hydrodynamical simulations, which broadly match the observed evolution in Ωkin, although their absolute normalization varies. Comparison to the Semi-Analytic Galaxy Evolution (SAGE) model suggests that radio-AGN may provide sufficient heating to offset radiative cooling losses, providing evidence for a self-regulated AGN feedback cycle. We integrate the kinetic luminosity density across cosmic time to obtain the kinetic energy density output from AGN jets throughout cosmic history to be ∼1050JMpc−3∼1050JMpc−3⁠. Compared to AGN winds, the kinetic energy density from AGN jets dominates the energy budget at z ≲ 2; this suggests that AGN jets play an important role in AGN feedback across most of cosmic history.Peer reviewe