Supply chain attacks,exemplified by the SUNBURST attack utilizing SolarWinds Orion updates,pose a growing cybersecurity threat to entities worldwide.However,the need for suitable datasets for detecting and anticipatin...Supply chain attacks,exemplified by the SUNBURST attack utilizing SolarWinds Orion updates,pose a growing cybersecurity threat to entities worldwide.However,the need for suitable datasets for detecting and anticipating SUNBURST attacks is a significant challenge.We present a novel dataset collected using a unique network traffic data collection methodology to address this gap.Our study aims to enhance intrusion detection and prevention systems by understanding SUNBURST attack features.We construct realistic attack scenarios by combining relevant data and attack indicators.The dataset is validated with the J48 machine learning algorithm,achieving an average F-Measure of 87.7%.Our significant contribution is the practical SUNBURST attack dataset,enabling better prevention and mitigation strategies.It is a valuable resource for researchers and practitioners to enhance supply chain attack defenses.In conclusion,our research provides a concise and focused SUNBURST attack dataset,facilitating improved intrusion detection and prevention systems.展开更多
This paper mainly studies big data-related position portrait construction based on recruitment data crawled from the 51job website.We first use text mining technique to classify job information and accurately obtain t...This paper mainly studies big data-related position portrait construction based on recruitment data crawled from the 51job website.We first use text mining technique to classify job information and accurately obtain the texts of two important aspects:work content and job requirements.We then apply the information extraction technique to extract labels describing different aspects of positions from structured and unstructured text data,and also adopt the Kano model to obtain more labels.Finally,we construct a multi-aspect and multi-dimensional position portrait through the sunburst chart.The position portrait constructed in this paper provides multi-dimensional analysis of the requirements of big data-related jobs and can help job seekers,enterprises,universities,and even third-party training institutions know the demand for talents and quickly determine the pertinence of a candidate's resume.展开更多
文摘Supply chain attacks,exemplified by the SUNBURST attack utilizing SolarWinds Orion updates,pose a growing cybersecurity threat to entities worldwide.However,the need for suitable datasets for detecting and anticipating SUNBURST attacks is a significant challenge.We present a novel dataset collected using a unique network traffic data collection methodology to address this gap.Our study aims to enhance intrusion detection and prevention systems by understanding SUNBURST attack features.We construct realistic attack scenarios by combining relevant data and attack indicators.The dataset is validated with the J48 machine learning algorithm,achieving an average F-Measure of 87.7%.Our significant contribution is the practical SUNBURST attack dataset,enabling better prevention and mitigation strategies.It is a valuable resource for researchers and practitioners to enhance supply chain attack defenses.In conclusion,our research provides a concise and focused SUNBURST attack dataset,facilitating improved intrusion detection and prevention systems.
文摘This paper mainly studies big data-related position portrait construction based on recruitment data crawled from the 51job website.We first use text mining technique to classify job information and accurately obtain the texts of two important aspects:work content and job requirements.We then apply the information extraction technique to extract labels describing different aspects of positions from structured and unstructured text data,and also adopt the Kano model to obtain more labels.Finally,we construct a multi-aspect and multi-dimensional position portrait through the sunburst chart.The position portrait constructed in this paper provides multi-dimensional analysis of the requirements of big data-related jobs and can help job seekers,enterprises,universities,and even third-party training institutions know the demand for talents and quickly determine the pertinence of a candidate's resume.
