Data mining for network intrusion detection

This paper gives an overview of our research in building rare class prediction models for identifying known intrusions and their variations and anomaly/outlier detection schemes for detecting novel attacks whose nature is unknown. Experimental results on the KDDCup’99 data set have demonstrated that our rare class predictive models are much more efficient in the detection of intrusive behavior than standard classification techniques. Experimental results on the DARPA 1998 data set, as well as on live network traffic at the University of Minnesota, show that the new techniques show great promise in detecting novel intrusions. In particular, during the past few months our techniques have been successful in automatically identifying several novel intrusions that could not be detected using state-of-the-art tools such as SNORT. In fact, many of these have been on the CERT/CC list of recent advisories and incident notes. 1

Textbook outcome following oesophagectomy for cancer: international cohort study

Background: Textbook outcome has been proposed as a tool for the assessment of oncological surgical care. However, an international assessment in patients undergoing oesophagectomy for oesophageal cancer has not been reported. This study aimed to assess textbook outcome in an international setting. Methods: Patients undergoing curative resection for oesophageal cancer were identified from the international Oesophagogastric Anastomosis Audit (OGAA) from April 2018 to December 2018. Textbook outcome was defined as the percentage of patients who underwent a complete tumour resection with at least 15 lymph nodes in the resected specimen and an uneventful postoperative course, without hospital readmission. A multivariable binary logistic regression model was used to identify factors independently associated with textbook outcome, and results are presented as odds ratio (OR) and 95 per cent confidence intervals (95 per cent c.i.). Results: Of 2159 patients with oesophageal cancer, 39.7 per cent achieved a textbook outcome. The outcome parameter 'no major postoperative complication' had the greatest negative impact on a textbook outcome for patients with oesophageal cancer, compared to other textbook outcome parameters. Multivariable analysis identified male gender and increasing Charlson comorbidity index with a significantly lower likelihood of textbook outcome. Presence of 24-hour on-call rota for oesophageal surgeons (OR 2.05, 95 per cent c.i. 1.30 to 3.22; P = 0.002) and radiology (OR 1.54, 95 per cent c.i. 1.05 to 2.24; P = 0.027), total minimally invasive oesophagectomies (OR 1.63, 95 per cent c.i. 1.27 to 2.08; P < 0.001), and chest anastomosis above azygous (OR 2.17, 95 per cent c.i. 1.58 to 2.98; P < 0.001) were independently associated with a significantly increased likelihood of textbook outcome. Conclusion: Textbook outcome is achieved in less than 40 per cent of patients having oesophagectomy for cancer. Improvements in centralization, hospital resources, access to minimal access surgery, and adoption of newer techniques for improving lymph node yield could improve textbook outcome