Malware in the Future? Forecasting of Analyst Detection of Cyber Events

There have been extensive efforts in government, academia, and industry to anticipate, forecast, and mitigate cyber attacks. A common approach is time-series forecasting of cyber attacks based on data from network telescopes, honeypots, and automated intrusion detection/prevention systems. This research has uncovered key insights such as systematicity in cyber attacks. Here, we propose an alternate perspective of this problem by performing forecasting of attacks that are analyst-detected and -verified occurrences of malware. We call these instances of malware cyber event data. Specifically, our dataset was analyst-detected incidents from a large operational Computer Security Service Provider (CSSP) for the U.S. Department of Defense, which rarely relies only on automated systems. Our data set consists of weekly counts of cyber events over approximately seven years. Since all cyber events were validated by analysts, our dataset is unlikely to have false positives which are often endemic in other sources of data. Further, the higher-quality data could be used for a number for resource allocation, estimation of security resources, and the development of effective risk-management strategies. We used a Bayesian State Space Model for forecasting and found that events one week ahead could be predicted. To quantify bursts, we used a Markov model. Our findings of systematicity in analyst-detected cyber attacks are consistent with previous work using other sources. The advanced information provided by a forecast may help with threat awareness by providing a probable value and range for future cyber events one week ahead. Other potential applications for cyber event forecasting include proactive allocation of resources and capabilities for cyber defense (e.g., analyst staffing and sensor configuration) in CSSPs. Enhanced threat awareness may improve cybersecurity.Comment: Revised version resubmitted to journa

Patient-Specific Injury Metrics Predict Early Biomarker Response in Multiply Injured Patients

poster abstractIntroduction: It is important to identify multiply injured patients (MIPs) that can tolerate high-magnitude procedures and those at risk for complications. Determining how injury leads to immunologic dysfunction could identify MIPs at risk for complications. We explored a new precision medicine approach in which we determined how patientspecific injury metrics corresponded to changes in cytokines in a prospective cohort of MIPs. Methods: This was a prospective observational cohort of 40 MIPs, 18-55 yo, admitted to surgical ICU having had full axial CTs done at admission. Mechanical tissue damage was quantified by calculating volumetric measures of injuries from CT scans into the Tissue Damage Volume score (TDV). Ischemic tissue damage was calculated by calculation of all abnormal Shock Volumes (SV) (heart rate/systolic blood pressure > 0.9) in the first 24hr after injury. TIMS was calculated by combining mechanical and ischemic tissue damage: TIMS = TDV+5*SV. Linear regression was performed between TIMS and 21 cytokines including interleukin (IL)-6; IL-8; IL-10; IL-1RA; IL-2RA; MCP-1 drawn at 0hr, 8hr, and 24hr after injury. Linear regression was also performed between the cytokines, Injury Severity Score (ISS) and minimum pH (day 1). Results: Mean and median ISS was 29 (range 9 – 66). Minimum pH demonstrated best correspondence to cytokine levels measured 0hr and 8hr after injury. TIMS demonstrated the best correspondence to cytokine levels 24hr after injury. ISS demonstrated minimal predictive value of cytokines at any timepoint. Discussion: A precision medicine approach using a patient-specific quantity of injury predicted trauma-associated changes in circulating cytokines at 0hr, 8 hr, and 24 hr after surgery. This corresponds favorably with timing of orthopaedic surgical decisions regarding staged fracture interventions. While clinical significance of these findings is unknown, computational data analyses of temporal cytokine changes have been shown to be predictive of adverse outcomes after injury

SHERLOCK: Experimental evaluation of a conversational agent for mobile information tasks

Abstract—Controlled Natural Language (CNL) has great potential to support human-machine interaction (HMI) because it provides an information representation that is both human readable and machine processable.We investigated the effectiveness of a CNL-based conversational interface for HMI in a behavioural experiment called Simple Human Experiment Regarding Locally Observed Collective Knowledge (SHERLOCK). In SHERLOCK, individuals acted in groups to discover and report information to the machine using natural language (NL), which the machine then processed into CNL. The machine fused responses from different users to form a common operating picture, a dashboard showing the level of agreement for distinct information. To obtain information to add to this dashboard, users explored the real world in a simulated crowd-sourced sensing scenario. This scenario represented a simplified, controlled analogue for tactical intelligence (i.e., direct intelligence of the environment), which is key for rapidly planning military, law enforcement, and emergency operations. Overall, despite close to zero training, 74% of the users inputted NL that was machine interpretable and addressed the assigned tasks. An experimental manipulation aimed to increase user-machine interaction, however, did not improve performance as hypothesised. Nevertheless, results indicate the conversational interface may be effective in assisting humans with collection and fusion of information in a crowd-sourcing context

Harnessing RNA sequencing for global, unbiased evaluation of two new adjuvants for dendritic-cell immunotherapy

Effective stimulation of immune cells is crucial for the success of cancer immunotherapies. Current approaches to evaluate the efficiency of stimuli are mainly defined by known flow cytometry-based cell activation or cell maturation markers. This method however does not give a complete overview of the achieved activation state and may leave important side effects unnoticed. Here, we used an unbiased RNA sequencing (RNA-seq)-based approach to compare the capacity of four clinical-grade dendritic cell (DC) activation stimuli used to prepare DC-vaccines composed of various types of DC subsets; the already clinically applied GM-CSF and Frühsommer meningoencephalitis (FSME) prophylactic vaccine and the novel clinical grade adjuvants protamine-RNA complexes (pRNA) and CpG-P. We found that GM-CSF and pRNA had similar effects on their target cells, whereas pRNA and CpG-P induced stronger type I interferon (IFN) expression than FSME. In general, the pathways most affected by all stimuli were related to immune activity and cell migration. GM-CSF stimulation, however, also induced a significant increase of genes related to nonsense-mediated decay, indicating a possible deleterious effect of this stimulus. Taken together, the two novel stimuli appear to be promising alternatives. Our study demonstrates how RNA-seq based investigation of changes in a large number of genes and gene groups can be exploited for fast and unbiased, global evaluation of clinical-grade stimuli, as opposed to the general limited evaluation of a pre-specified set of genes, by which one might miss important biological effects that are detrimental for vaccine efficacy

Harnessing RNA sequencing for global, unbiased evaluation of two new adjuvants for dendritic-cell immunotherapy

Effective stimulation of immune cells is crucial for the success of cancer immunotherapies. Current approaches to evaluate the efficiency of stimuli are mainly defined by known flow cytometry-based cell activation or cell maturation markers. This method however does not give a complete overview of the achieved activation state and may leave important side effects unnoticed. Here, we used an unbiased RNA sequencing (RNA-seq)-based approach to compare the capacity of four clinical-grade dendritic cell (DC) activation stimuli used to prepare DC-vaccines composed of various types of DC subsets; the already clinically applied GM-CSF and Frühsommer meningoencephalitis (FSME) prophylactic vaccine and the novel clinical grade adjuvants protamine-RNA complexes (pRNA) and CpG-P. We found that GM-CSF and pRNA had similar effects on their target cells, whereas pRNA and CpG-P induced stronger type I interferon (IFN) expression than FSME. In general, the pathways most affected by all stimuli were related to immune activity and cell migration. GMCSF stimulation, however, also induced a significant increase of genes related to nonsense-mediated decay, indicating a possible deleterious effect of this stimulus. Taken together, the two novel stimuli appear to be promising alternatives. Our study demonstrates how RNA-seq based investigation of changes in a large number of genes and gene groups can be exploited for fast and unbiased, global evaluation of clinicalgrade stimuli, as opposed to the general limited evaluation of a pre-specified set of genes, by which one might miss important biological effects that are detrimental for vaccine efficacy

The tumour microenvironment shapes dendritic cell plasticity in a human organotypic melanoma culture

Contains fulltext : 220729.pdf (publisher's version ) (Open Access)The tumour microenvironment (TME) forms a major obstacle in effective cancer treatment and for clinical success of immunotherapy. Conventional co-cultures have shed light onto multiple aspects of cancer immunobiology, but they are limited by the lack of physiological complexity. We develop a human organotypic skin melanoma culture (OMC) that allows real-time study of host-malignant cell interactions within a multicellular tissue architecture. By co-culturing decellularized dermis with keratinocytes, fibroblasts and immune cells in the presence of melanoma cells, we generate a reconstructed TME that closely resembles tumour growth as observed in human lesions and supports cell survival and function. We demonstrate that the OMC is suitable and outperforms conventional 2D co-cultures for the study of TME-imprinting mechanisms. Within the OMC, we observe the tumour-driven conversion of cDC2s into CD14(+) DCs, characterized by an immunosuppressive phenotype. The OMC provides a valuable approach to study how a TME affects the immune system

A Comparative Study of the T Cell Stimulatory and Polarizing Capacity of Human Primary Blood Dendritic Cell Subsets

Dendritic cells (DCs) are central players of immune responses; they become activated upon infection or inflammation and migrate to lymph nodes, where they can initiate an antigen-specific immune response by activating naive T cells. Two major types of naturally occurring DCs circulate in peripheral blood, namely, myeloid and plasmacytoid DCs (pDCs). Myeloid DCs (mDCs) can be subdivided based on the expression of either CD1c or CD141. These human DC subsets differ in surface marker expression, Toll-like receptor (TLR) repertoire, and transcriptional profile, suggesting functional differences between them. Here, we directly compared the capacity of human blood mDCs and pDCs to activate and polarize CD4 + T cells. CD141 + mDCs show an overall more mature phenotype over CD1c + mDC and pDCs; they produce less IL-10 and more IL-12 than CD1c + mDCs. Despite these differences, all subsets can induce the production of IFN-in naive CD4 + T cells. CD1c + and CD141 + mDCs especially induce a strong T helper 1 profile. Importantly, naive CD4 + T cells are not polarized towards regulatory T cells by any subset. These findings further establish all three human blood DCs-despite their differences-as promising candidates for immunostimulatory effectors in cancer immunotherapy

Atrasentan and renal events in patients with type 2 diabetes and chronic kidney disease (SONAR): a double-blind, randomised, placebo-controlled trial

Background: Short-term treatment for people with type 2 diabetes using a low dose of the selective endothelin A receptor antagonist atrasentan reduces albuminuria without causing significant sodium retention. We report the long-term effects of treatment with atrasentan on major renal outcomes. Methods: We did this double-blind, randomised, placebo-controlled trial at 689 sites in 41 countries. We enrolled adults aged 18–85 years with type 2 diabetes, estimated glomerular filtration rate (eGFR)25–75 mL/min per 1·73 m 2 of body surface area, and a urine albumin-to-creatinine ratio (UACR)of 300–5000 mg/g who had received maximum labelled or tolerated renin–angiotensin system inhibition for at least 4 weeks. Participants were given atrasentan 0·75 mg orally daily during an enrichment period before random group assignment. Those with a UACR decrease of at least 30% with no substantial fluid retention during the enrichment period (responders)were included in the double-blind treatment period. Responders were randomly assigned to receive either atrasentan 0·75 mg orally daily or placebo. All patients and investigators were masked to treatment assignment. The primary endpoint was a composite of doubling of serum creatinine (sustained for ≥30 days)or end-stage kidney disease (eGFR <15 mL/min per 1·73 m 2 sustained for ≥90 days, chronic dialysis for ≥90 days, kidney transplantation, or death from kidney failure)in the intention-to-treat population of all responders. Safety was assessed in all patients who received at least one dose of their assigned study treatment. The study is registered with ClinicalTrials.gov, number NCT01858532. Findings: Between May 17, 2013, and July 13, 2017, 11 087 patients were screened; 5117 entered the enrichment period, and 4711 completed the enrichment period. Of these, 2648 patients were responders and were randomly assigned to the atrasentan group (n=1325)or placebo group (n=1323). Median follow-up was 2·2 years (IQR 1·4–2·9). 79 (6·0%)of 1325 patients in the atrasentan group and 105 (7·9%)of 1323 in the placebo group had a primary composite renal endpoint event (hazard ratio [HR]0·65 [95% CI 0·49–0·88]; p=0·0047). Fluid retention and anaemia adverse events, which have been previously attributed to endothelin receptor antagonists, were more frequent in the atrasentan group than in the placebo group. Hospital admission for heart failure occurred in 47 (3·5%)of 1325 patients in the atrasentan group and 34 (2·6%)of 1323 patients in the placebo group (HR 1·33 [95% CI 0·85–2·07]; p=0·208). 58 (4·4%)patients in the atrasentan group and 52 (3·9%)in the placebo group died (HR 1·09 [95% CI 0·75–1·59]; p=0·65). Interpretation: Atrasentan reduced the risk of renal events in patients with diabetes and chronic kidney disease who were selected to optimise efficacy and safety. These data support a potential role for selective endothelin receptor antagonists in protecting renal function in patients with type 2 diabetes at high risk of developing end-stage kidney disease. Funding: AbbVie