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Network Detection and Response

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CORELIGHT LABS

MISSION + TEAM

corelight-labs-mission-main

 

MISSION

To provide cutting-edge content that enables complete, detailed monitoring of enterprise network activity for threat hunting, analysis, and response.

Team


  • Management Team

Scientific roots

Julien Piet, Aashish Sharma, Vern Paxson, and David Wagner.
Network Detection of Interactive SSH Impostors Using Deep Learning
Proc. USENIX Security, August 2023.

Julien Piet, Dubem Nwoji, and Vern Paxson.
GGFAST: Automating Generation of Flexible Network Traffic Classifiers
Proc. ACM SIGCOMM, September 2023.

Grant Ho, Mayank Dhiman, Devdatta Akhawe, Vern Paxson, Stefan Savage, Geoffrey M. Voelker, David Wagner.
Hopper: Modeling and Detecting Lateral Movement.
Proc. USENIX Security Symposium, August 2021.

Keith J. Jones, Yong Wang.
Malgazer: An Automated Malware Classifier With Running Window Entropy and Machine Learning 
Sixth International Conference on Mobile And Secure Services (MobiSecServ), 2020.

Ignacio Arnaldo, Kalyan Veeramachaneni.
The Holy Grail of "Systems for Machine Learning": Teaming humans and machine learning for detecting cyber threats.
ACM SIGKDD Explorations Newsletter 21 (2), 39-47, 2019.

Grant Ho, Asaf Cidon, Lior Gavish, Marco Schweighauser, Vern Paxson, Stefan Savage, Geoffrey M. Voelker, David Wagner.
Detecting and Characterizing Lateral Phishing at Scale.
Proc. USENIX Security Symposium, August 2019.

Ankit Arun, Ignacio Arnaldo.
Shooting the Moving Target: Machine Learning in Cybersecurity.
USENIX Conference on Operational Machine Learning (OpML 19), 13-14, 2019.

Ignacio Arnaldo, Kalyan Veeramachaneni, Mei Lam.
eX2: A Framework for Interactive Anomaly Detection.
Intelligent User Interfaces Workshops, 2019.

Ignacio Arnaldo, Ankit Arun, Sumeeth Kyathanahalli, Kalyan Veeramachaneni.
Acquire, Adapt, and Anticipate: Continuous Learning to Block Malicious Domains.
IEEE International Conference on Big Data (Big Data), 1891-1898, 2018.

Grant Ho, Aashish Sharma, Mobin Javed, Vern Paxson, David Wagner.
Detecting Credential Spearphishing Attacks in Enterprise Settings.
Proc. USENIX Security Symposium, August 2017.

Ignacio Arnaldo, Alfredo Cuesta-Infante, Ankit Arun, Mei Lam, Costas Bassias, Kalyan Veeramachaneni.
Learning Representations for Log Data in Cybersecurity.
International Conference on Cyber Security Cryptography and Machine Learning, 2017.

Yizheng Chen, Yacin Nadji, Athanasios Kountouras, Fabian Monrose, Roberto Perdisci, Manos Antonakakis, Nikolaos Vasiloglou.
Practical Attacks Against Graph-based Clustering.
Proceedings of the 24th ACM Conference on Computer and Communications Security (CCS), 2017.

Charles Lever, Robert Walls, Yacin Nadji, David Dagon, Patrick McDaniel, Manos Antonakakis.
Domain-Z: 28 Registrations Later - Measuring the Exploitation of Residual Trust in Domains.
IEEE Symposium on Security and Privacy (Oakland), 2016.

Kalyan Veeramachaneni, Ignacio Arnaldo, Vamsi Korrapati, Constantinos Bassias, Ke Li.
AI^2: Training a Big Data Machine to Defend.
IEEE 2nd International Conference on Big Data Security on Cloud, 2016.

To learn more about joining Corelight Labs, visit our Careers page.

Scientific roots


Grant Ho, Mayank Dhiman, Devdatta Akhawe, Vern Paxson, Stefan Savage, Geoffrey M. Voelker, David Wagner.
Hopper: Modeling and Detecting Lateral Movement.
Proc. USENIX Security Symposium, August 2021.

Keith J. Jones, Yong Wang.
Malgazer: An Automated Malware Classifier With Running Window Entropy and Machine Learning 
Sixth International Conference on Mobile And Secure Services (MobiSecServ), 2020.

Ignacio Arnaldo, Kalyan Veeramachaneni.
The Holy Grail of "Systems for Machine Learning": Teaming humans and machine learning for detecting cyber threats.
ACM SIGKDD Explorations Newsletter 21 (2), 39-47, 2019.

Grant Ho, Asaf Cidon, Lior Gavish, Marco Schweighauser, Vern Paxson, Stefan Savage, Geoffrey M. Voelker, David Wagner.
Detecting and Characterizing Lateral Phishing at Scale.
Proc. USENIX Security Symposium, August 2019.

Ankit Arun, Ignacio Arnaldo.
Shooting the Moving Target: Machine Learning in Cybersecurity.
USENIX Conference on Operational Machine Learning (OpML 19), 13-14, 2019.

Ignacio Arnaldo, Kalyan Veeramachaneni, Mei Lam.
eX2: A Framework for Interactive Anomaly Detection.
Intelligent User Interfaces Workshops, 2019.

Ignacio Arnaldo, Ankit Arun, Sumeeth Kyathanahalli, Kalyan Veeramachaneni.
Acquire, Adapt, and Anticipate: Continuous Learning to Block Malicious Domains.
IEEE International Conference on Big Data (Big Data), 1891-1898, 2018.

Grant Ho, Aashish Sharma, Mobin Javed, Vern Paxson, David Wagner.
Detecting Credential Spearphishing Attacks in Enterprise Settings.
Proc. USENIX Security Symposium, August 2017.

Ignacio Arnaldo, Alfredo Cuesta-Infante, Ankit Arun, Mei Lam, Costas Bassias, Kalyan Veeramachaneni.
Learning Representations for Log Data in Cybersecurity.
International Conference on Cyber Security Cryptography and Machine Learning, 2017.

Yizheng Chen, Yacin Nadji, Athanasios Kountouras, Fabian Monrose, Roberto Perdisci, Manos Antonakakis, Nikolaos Vasiloglou.
Practical Attacks Against Graph-based Clustering.
Proceedings of the 24th ACM Conference on Computer and Communications Security (CCS), 2017.

Charles Lever, Robert Walls, Yacin Nadji, David Dagon, Patrick McDaniel, Manos Antonakakis.
Domain-Z: 28 Registrations Later - Measuring the Exploitation of Residual Trust in Domains.
IEEE Symposium on Security and Privacy (Oakland), 2016.

Kalyan Veeramachaneni, Ignacio Arnaldo, Vamsi Korrapati, Constantinos Bassias, Ke Li.
AI^2: Training a Big Data Machine to Defend.
IEEE 2nd International Conference on Big Data Security on Cloud, 2016.


To learn more about joining Corelight Labs, visit our Careers page.

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