The reason why data anonymization really matters
AI industry is losing opportunities
Massive amounts of data are key assets for the AI industry. However, from selfies to medical records, most data include private information. Two greatest challenges when utilizing personal data are strict regulations and the enormous expense.
While data is essential to unleash the power of AI, protecting privacy is equally important. This conundrum has created a strong demand for a tool that delivers both.
Protecting Confidentiality
Some images, videos, texts or audio files contain critical information of an organization, which should not be revealed to the public.
When using or sharing data with confidential information, preventing all the possibilities of data leakage is a must.
Protecting Data Ownership
From uploading to labeling, validation and purchase, many people are involved in the data transaction process.
All the data need to be protected from unlawful data usages, such as illegal copy or reselling.
How secure is your data?
Infringement of ownership is the major ongoing issue that occurs in the process of data transaction. Security holes existing in the current data sharing environment are the major causes of the data breach incidents. In the entire flow of data, various participants are involved, such as providers, labelers, validators and consumers.
Two types of security holes
Data security holes appear in two different cases. First, data could be snatched in the processing phase, by some labelers and validators using them for own purposes without permission. Second, some purchasers may yield unfair profit by reselling data while seriously damaging the owner's copyright.
Jammer
Safeguard your data assets from illegal ML training
How Jammer protects data ownership
Train with your data
exclusively
Jammer disables data to be used for training AI models, ensuring that the data will be protected from misuses by untrusted labelers and validators.
Jammer makes data untrainable for preview, labeling, validation, etc. A significant accuracy drop appears when training with jammed data. As a result, Jammer makes it useless to train an AI model with illegally copied ones.
Watermarker
Protect your data ownership from illegal resales
How Watermarker protects data ownership
Display your ownership
through data
Watermarker embeds watermarks displaying the ownership into data that is to be purchased by consumers, therefore making it worthless for illegal uses, such as reselling.
Watermarks are visible to human, but data can be used for ML models without causing any accuracy drop. Since the marks are hard-to-remove, data processed with Watermarker are protected from thefts while still usable for AI trainings.
