A detailed description on unsupervised heterogeneous anomaly based intrusion detection framework

Observing network traffic flow for anomalies is a common method in Intrusion Detection. More effort has been taken in utilizing the data mining and machine learning algorithms to construct anomaly based intrusion detection systems, but the dependency on the learned models that were built based on earlier network behaviour still exists, which restricts those methods in detecting new or unknown intrusions. Consequently, this investigation proposes a structure to identify an extensive variety of abnormalities by analysing heterogeneous logs, without utilizing either a prepared model of system transactions or the attributes of anomalies. To accomplish this, a current segment (clustering) has been used and a few new parts (filtering, aggregating and feature analysis) have been presented. Several logs from multiple sources are used as input and this data are processed by all the modules of the framework. As each segment is instrumented for a particular undertaking towards a definitive objective, the commitment of each segment towards abnormality recognition is estimated with various execution measurements. Ultimately, the framework is able to detect a broad range of intrusions exist in the logs without using either the attack knowledge or the traffic behavioural models. The result achieved shows the direction or pathway to design anomaly detectors that can utilize raw traffic logs collected from heterogeneous sources on the network monitored and correlate the events across the logs to detect intrusions

Comparative outcomes of bariatric surgery in patients with impaired mobility and ambulatory population

Purpose: This study aims to characterize complications, metabolic improvement, and change in ambulation status for patients with impaired mobility undergoing bariatric surgery. Material and methods: Individuals undergoing primary sleeve gastrectomy (SG) or Roux-en-Y gastric bypass (RYGB) from February 2008 to December 2015 were included. Impaired mobility (WC) was defined as using a wheelchair or motorized scooter for at least part of a typical day. The WC group was propensity score matched to ambulatory patients (1:5 ratio). Comparisons were made for 30-day morbidity and mortality and 1-year improvement in weight-related comorbidities. Results: There were 93 patients in the WC group matched to 465 ambulatory controls. The median operative time (180 vs 159 min, p = 0.003) and postoperative length of stay (4 vs 3 days, p ≤ 0.001) was higher in the WC group. There were no differences in readmission or all-cause morbidity within 30 days. The median percent excess weight loss (%EWL) at 1 year was similar (WC group, 65% available, 53% EWL vs AMB group, 73% available, 54% EWL); however, patients with impaired mobility were less likely to experience improvement in diabetes (76 vs 90%, p = 0.046), hypertension (63 vs 82%, p < 0.005), and obstructive sleep apnea (53 vs 71%, p < 0.001). Within the WC group, 62% had improvement in their mobility status, eliminating dependence on wheelchair or scooter assistance. Conclusion: Patients with both obesity and impaired mobility experience similar rates of perioperative morbidity and weight loss at 1 year compared to ambulatory controls. However, improvement in weight-related comorbidities may be less likely with impaired mobility