Collecting Indicators of Compromise from Unstructured Text of Cybersecurity Articles using Neural-Based Sequence Labelling

no code implementations • 4 Jul 2019 • Zi Long, Lianzhi Tan, Shengping Zhou, Chaoyang He, Xin Liu

Indicators of Compromise (IOCs) are artifacts observed on a network or in an operating system that can be utilized to indicate a computer intrusion and detect cyber-attacks in an early stage.

Stochastic Distributed Optimization for Machine Learning from Decentralized Features

no code implementations • 16 Dec 2018 • Yaochen Hu, Di Niu, Jianming Yang, Shengping Zhou

Distributed machine learning has been widely studied in the literature to scale up machine learning model training in the presence of an ever-increasing amount of data.

BIG-bench Machine Learning Distributed Optimization

Automatic Identification of Indicators of Compromise using Neural-Based Sequence Labelling

no code implementations • PACLIC 2018 • Shengping Zhou, Zi Long, Lianzhi Tan, Hao Guo

In this paper, we propose using a neural-based sequence labelling model to identify IOCs automatically from reports on cybersecurity without expert knowledge of cybersecurity.