Crossfire attack is a recently proposed threat designed to disconnect whole geographical areas, such as cities or states, from the Internet. Orchestrated in multiple phases, the attack uses a massively distributed botnet to generate low-rate benign traffic aiming to congest selected network links, so-called target links. The adoption of benign traffic, while simultaneously targeting multiple network links, makes the detection of the Crossfire attack a serious challenge.In this paper, we propose a framework for early detection of Crossfire attack, i.e., detection in the warm-up period of the attack. We propose to monitor traffic at the potential decoy servers and discuss the advantages comparing with other monitoring approaches. Since the low-rate attack traffic is very difficult to distinguish from the background traffic, we investigate several deep learning methods to mine the spatiotemporal features for attack detection. We investigate Autoencoder, Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) Network to detect the Crossfire attack during its warm-up period. We report encouraging experiment results.
A 63-year-old male presented to us with upper abdominal pain and odynophagia for 3 months. Contrast-enhanced computed tomography of the abdomen revealed hiatus hernia with ulceroproliferative growth involving the gastro-oesophageal (GE) junction and cardia of the stomach with no obvious transserosal extension. Upper gastrointestinal (GI) endoscopy was suggestive of a tumour of size 3 cm × 3 cm near the GE junction and sliding hiatus hernia. Although there are various ways described in the literature for managing GI stromal tumour (GIST), we opted for laparo-endoscopic transgastric resection with hiatus hernia repair due to obvious advantages in terms of safety and efficacy. Just a handful of cases have been described in the literature being treated in this fashion. The procedure was successfully performed as evidenced by an uneventful recovery of the patient. His histopathology report was suggestive of GIST of size 3.5 cm × 3.0 cm × 2.0 cm. The resected margins were free of the tumour.
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