Cyber security research frameworks for coevolutionary network defense

Cyber security is increasingly a challenge for organizations everywhere. Defense systems that require less expert knowledge and can adapt quickly to threats are strongly needed to combat the rise of cyber attacks. Computational intelligence techniques can be used to rapidly explore potential solutions while searching in a way that is unaffected by human bias. Several architectures have been created for developing and testing systems used in network security, but most are meant to provide a platform for running cyber security experiments as opposed to automating experiment processes. In the first paper, we propose a framework termed Distributed Cyber Security Automation Framework for Experiments (DCAFE) that enables experiment automation and control in a distributed environment. Predictive analysis of adversaries is another thorny issue in cyber security. Game theory can be used to mathematically analyze adversary models, but its scalability limitations restrict its use. Computational game theory allows us to scale classical game theory to larger, more complex systems. In the second paper, we propose a framework termed Coevolutionary Agent-based Network Defense Lightweight Event System (CANDLES) that can coevolve attacker and defender agent strategies and capabilities and evaluate potential solutions with a custom network defense simulation. The third paper is a continuation of the CANDLES project in which we rewrote key parts of the framework. Attackers and defenders have been redesigned to evolve pure strategy, and a new network security simulation is devised which specifies network architecture and adds a temporal aspect. We also add a hill climber algorithm to evaluate the search space and justify the use of a coevolutionary algorithm --Abstract, page iv

Anhedonia and reward-circuit connectivity distinguish nonresponders from responders to dorsomedial prefrontal rTMS in major depression

Background Depression is a heterogeneous mental illness. Neurostimulation treatments, by targeting specific nodes within the brain’s emotion-regulation network, may be useful both as therapies and as probes for identifying clinically relevant depression subtypes. Methods Here, we applied 20 sessions of magnetic resonance imaging-guided repetitive transcranial magnetic stimulation (rTMS) to the dorsomedial prefrontal cortex in 47 unipolar or bipolar patients with a medication-resistant major depressive episode. Results Treatment response was strongly bimodal, with individual patients showing either minimal or marked improvement. Compared with responders, nonresponders showed markedly higher baseline anhedonia symptomatology (including pessimism, loss of pleasure, and loss of interest in previously enjoyed activities) on item-by-item examination of Beck Depression Inventory-II and Quick Inventory of Depressive Symptomatology ratings. Congruently, on baseline functional magnetic resonance imaging, nonresponders showed significantly lower connectivity through a classical reward pathway comprising ventral tegmental area, striatum, and a region in ventromedial prefrontal cortex. Responders and nonresponders also showed opposite patterns of hemispheric lateralization in the connectivity of dorsomedial and dorsolateral regions to this same ventromedial region. Conclusions The results suggest distinct depression subtypes, one with preserved hedonic function and responsive to dorsomedial rTMS and another with disrupted hedonic function, abnormally lateralized connectivity through ventromedial prefrontal cortex, and unresponsive to dorsomedial rTMS. Future research directly comparing the effects of rTMS at different targets, guided by neuroimaging and clinical presentation, may clarify whether hedonia/reward circuit integrity is a reliable marker for optimizing rTMS target selection

Association of Accelerometry-Measured Physical Activity and Cardiovascular Events in Mobility-Limited Older Adults: The LIFE (Lifestyle Interventions and Independence for Elders) Study.

BACKGROUND:Data are sparse regarding the value of physical activity (PA) surveillance among older adults-particularly among those with mobility limitations. The objective of this study was to examine longitudinal associations between objectively measured daily PA and the incidence of cardiovascular events among older adults in the LIFE (Lifestyle Interventions and Independence for Elders) study. METHODS AND RESULTS:Cardiovascular events were adjudicated based on medical records review, and cardiovascular risk factors were controlled for in the analysis. Home-based activity data were collected by hip-worn accelerometers at baseline and at 6, 12, and 24 months postrandomization to either a physical activity or health education intervention. LIFE study participants (n=1590; age 78.9±5.2 [SD] years; 67.2% women) at baseline had an 11% lower incidence of experiencing a subsequent cardiovascular event per 500 steps taken per day based on activity data (hazard ratio, 0.89; 95% confidence interval, 0.84-0.96; P=0.001). At baseline, every 30 minutes spent performing activities ≥500 counts per minute (hazard ratio, 0.75; confidence interval, 0.65-0.89 [P=0.001]) were also associated with a lower incidence of cardiovascular events. Throughout follow-up (6, 12, and 24 months), both the number of steps per day (per 500 steps; hazard ratio, 0.90, confidence interval, 0.85-0.96 [P=0.001]) and duration of activity ≥500 counts per minute (per 30 minutes; hazard ratio, 0.76; confidence interval, 0.63-0.90 [P=0.002]) were significantly associated with lower cardiovascular event rates. CONCLUSIONS:Objective measurements of physical activity via accelerometry were associated with cardiovascular events among older adults with limited mobility (summary score >10 on the Short Physical Performance Battery) both using baseline and longitudinal data. CLINICAL TRIAL REGISTRATION:URL: http://www.clinicaltrials.gov. Unique identifier: NCT01072500

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Coevolutionary Agent-Based Network Defense Lightweight Event System (CANDLES)

Predicting an adversary\u27s capabilities, intentions, and probable vectors of attack is in general a complex and arduous task. Cyber space is particularly vulnerable to unforeseen attacks, as most computer networks have a large, complex, opaque attack surface area and are therefore extremely difficult to analyze. Abstract adversarial models which capture the pertinent features needed for analysis, can reduce the complexity sufficiently to make analysis feasible. Game theory allows for mathematical analysis of adversarial models; however, its scalability limitations restrict its use to simple, abstract models. Computational game theory is focused on scaling classical game theory to large, complex systems capable of modeling real-world environments; one promising approach is coevolution where each player\u27s \u27fitness is dependent on its adversaries. In this paper, we propose the Coevolutionary Agent-based Network Defense Lightweight Event System (CANDLES), a framework designed to coevolve attacker and defender agent strategies and evaluate potential solutions with a custom, abstract computer network defense simulation. By performing a qualitative analysis of the result data, we provide a proof of concept for the applicability of coevolution in planning for, and defending against, novel attacker strategies in computer network security