PACE: Pattern Accurate Computationally Efficient Bootstrapping for Timely Discovery of Cyber-security Concepts

McNeil, Nikki; Bridges, Robert A.; Iannacone, Michael D.; Czejdo, Bogdan D.; Perez, Nicolas; Goodall, John R.

doi:10.1109/icmla.2013.106

Cited by 36 publications

(16 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Mulwad et al [10] proposed a method to extract vulnerabilities and attacks using Wikitology. McNeil et al [11] proposed a method to extract software names, vulnerability categories, vulnerability effects, and exploit effects. Joshi et al [12] proposed a method to generate a Resource Description Framework (RDF) data, which is automatically processed, from unc 2019 Information Processing Society of Japan structured data.…”

Section: Related Workmentioning

confidence: 99%

Understanding Attack Trends from Security Blog Posts Using Guided-topic Model

Nagai

Takita

Furumoto

et al. 2019

Journal of Information Processing

View full text Add to dashboard Cite

Organizations are plagued by sophisticated and diversified cyber attacks. In order to prevent such attacks, it is necessary to understand threat trends and to take measures to protect their assets. Security vendors publish reports which contain threat trends or analysis of malware. These reports are useful for help in responding to a cyber security incident. However, it is difficult to collect threat information from multiple sources such as security blog posts. In this paper, we propose a method to efficiently collect information from the relationship between words using SeededLDA. In our case studies, we visualize the relationship between the words from security blog posts which were published in 2017 by eight security vendors, and demonstrate how our method helps to understand threat trends in the IoT industry and financial institutions.

show abstract

Section: Related Workmentioning

confidence: 99%

Understanding Attack Trends from Security Blog Posts Using Guided-topic Model

Nagai

Takita

Furumoto

et al. 2019

Journal of Information Processing

View full text Add to dashboard Cite

show abstract

“…There is also ongoing work to incorporate data from unstructured text sources, through a similar process [5,15,10]. This text processing also relies directly on the ontology to define the entities, relations, and properties that must be extracted from these texts.…”

Section: Data Sourcesmentioning

confidence: 99%

Developing an Ontology for Cyber Security Knowledge Graphs

Iannacone

Bohn

Nakamura

et al. 2015

Proceedings of the 10th Annual Cyber and Information Security Research Conference

111

View full text Add to dashboard Cite

In this paper we describe an ontology developed for a cyber security knowledge graph database. This is intended to provide an organized schema that incorporates information from a large variety of structured and unstructured data sources, and includes all relevant concepts within the domain. We compare the resulting ontology with previous efforts, discuss its strengths and limitations, and describe areas for future work.

show abstract

“…There is some research work providing evidence that relevant and timely cybersecurity data is available on Twitter [32,41,44], specifically that some vulnerabilities were published on Twitter before their inclusion on vulnerability databases. However, these are case studies concerning a single vulnerability, and compare the tweets referring them solely with the NVD.…”

Section: Cybersecurity-related Osint Studiesmentioning

confidence: 99%

Follow the Blue Bird: A Study on Threat Data Published on Twitter

Alves

Andongabo

Gashi

et al. 2020

Computer Security – ESORICS 2020

View full text Add to dashboard Cite

Open Source Intelligence (OSINT) has taken the interest of cybersecurity practitioners due to its completeness and timeliness. In particular, Twitter has proven to be a discussion hub regarding the latest vulnerabilities and exploits. In this paper, we present a study comparing vulnerability databases between themselves and against Twitter. Although there is evidence of OSINT advantages, no methodological studies have addressed the quality and benefits of the sources available. We compare the publishing dates of more than nine-thousand vulnerabilities in the sources considered. We show that NVD is not the most timely or the most complete vulnerability database, that Twitter provides timely and impactful security alerts, that using diverse OSINT sources provides better completeness and timeliness of vulnerabilities, and provide insights on how to capture cybersecurity-relevant tweets.

show abstract

PACE: Pattern Accurate Computationally Efficient Bootstrapping for Timely Discovery of Cyber-security Concepts

Cited by 36 publications

References 7 publications

Understanding Attack Trends from Security Blog Posts Using Guided-topic Model

Understanding Attack Trends from Security Blog Posts Using Guided-topic Model

Developing an Ontology for Cyber Security Knowledge Graphs

Follow the Blue Bird: A Study on Threat Data Published on Twitter

Contact Info

Product

Resources

About