HiddenLayer is an Austin, Texas-based developer of a cybersecurity platform to protect artificial intelligence and machine learning models.
HiddenLayer is an Austin, Texas-based developeddeveloper of a cybersecurity platform to protect artificial intelligence and machine learning models.
HiddenLayer is a developer of a cybersecurity product designed to protect machine learning and artificial intelligence algorithms, models, and underlying data. The company's platform uses machine learning to analyze model interactions and to identify malicious activity without requiring access to the machine learning model or sensitive training data. HiddenLayer's turnkey artificial intelligence and machine learning security models are developeddesigned to not add unnecessary complexity to models and doesdo not require access to raw data and algorithms. The company was founded in 2022 by CEO Christopher Sestito, Tanner Burns, and James Ballard and is headquartered in Austin, Texas.
HiddenLayer's platform is a machine learning security (MLSec) platfromplatform whichthat works to provide security against attacks on artificial intelligence and machine learning models. These tend to include ML attacks, such as inference, data poisoning, extraction, and evasion. Inference attacks are the process of using the input and ouputoutput of a model to learn how the model makes its decision and then allow attackers to tamper with the model. Data poisoning is the process of interfering with the data used for learning to corrupt the way the model works. Extraction is an advanced inference attack wherein which private data is stolen from the model if notor a full copy of the model is stolen. And evasion is a form of inference attack wherein which the attacker learns how to bypass the intended use of a model.
The MLSec platform includes the HiddenLayer MLDR, ModelScanner, and Security Audit Reporting, with a machine learning-based approach to analyze events in real-time and identify malicious activity without requiring access to sensitive training data. The HiddenLayer MLDR offers the real-time defense with flexible response operations whichthat include alerting, isolation, profiling, and misleading, and offers users configurable settingsettings to allow company'scompanies to fine-tune their company's needs. The ModelScanner scans a machine learning model to identify vulnerabilities to ensure the model has not been compromised and detects malicious code injections. And the Security Audit Reporting works to offer a comprehensive view of AiAI and ML assets security and validate the ML model security across an enterprise. This includes an on-demand dashboard and distributed reporting with priotizationprioritization for vulnerabilities.
October 25, 2022
HiddenLayer helps enterprises safeguard their machine learning models
HiddenLayer is an Austin, Texas-based developed of a cybersecurity platform to protect artificial intelligence and machine learning models.
HiddenLayer is a developer of cybersecurity product designed to protect machine learning and artificial intelligence algorithms, models, and underlying data. The company's platform uses machine learning to analyze model interactions and to identify malicious activity without requiring access to the machine learning model or sensitive training data. HiddenLayer's turnkey artificial intelligence and machine learning security models are developed to not add unnecessary complexity to models and does not require access to raw data and algorithms. The company was founded in 2022 by CEO Christopher Sestito, Tanner Burns, and James Ballard and is headquartered in Austin, Texas.
HiddenLayer's platform is a machine learning security (MLSec) platfrom which works to provide security against attacks on artificial intelligence and machine learning models. These tend to include ML attacks such as inference, data poisoning, extraction, and evasion. Inference attacks are the process of using the input and ouput of a model to learn how the model makes its decision and then allow attackers to tamper with the model. Data poisoning is the process of interfering with the data used for learning to corrupt the way the model works. Extraction is an advanced inference attack where private data is stolen from the model if not a copy of the model is stolen. And evasion is a form of inference attack where the attacker learns how to bypass the intended use of a model.
The MLSec platform includes the HiddenLayer MLDR, ModelScanner, and Security Audit Reporting, with a machine learning-based approach to analyze events in real-time and identify malicious activity without requiring access to sensitive training data. The HiddenLayer MLDR offers the real-time defense with flexible response operations which include alerting, isolation, profiling, and misleading, and offers users configurable setting to allow company's to fine-tune their company's needs. The ModelScanner scans a machine learning model to identify vulnerabilities to ensure the model has not been compromised and detects malicious code injections. And the Security Audit Reporting works to offer a comprehensive view of Ai and ML assets security and validate the ML model security across an enterprise. This includes an on-demand dashboard and distributed reporting with priotization for vulnerabilities.
October 25, 2022
August 23, 2022
July 19, 2022
HiddenLayer helps enterprises safeguard their machine learning models
HiddenLayer is an Austin, Texas-based developer of a cybersecurity platform to protect artificial intelligence and machine learning models.