Device Hash

What is a Device Hash?

Device hash is a cryptographic identifier created by combining multiple attributes of a device, such as its operating system, browser type, IP address, screen resolution, and other hardware or software details. This process ensures the creation of a unique but anonymous identifier for each device, allowing businesses to track device behavior over time.

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Unlike device fingerprinting, which provides a detailed profile of the device, a device hash focuses on creating a single, anonymized identifier that protects user privacy while enabling businesses to monitor suspicious patterns, such as devices linked to multiple fraudulent accounts or transactions.

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How Does Device Hash Work?

Data Collection

The system collects a set of non-sensitive device attributes during user interactions, such as:

• Browser type and version.

• Operating system and version.

• Screen resolution.

• Device model and manufacturer.

• IP address or geolocation.

These attributes are not used to uniquely identify an individual but to create a unique identifier for the device itself.

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Hash Generation

• These attributes are combined into a single cryptographic hash using hashing algorithms
  • like SHA-256.

• The result is a unique identifier for the device that is consistent across sessions but cannot be reverse-engineered to expose sensitive information.

Usage in Fraud Detection

The device hash is stored and tracked over time, enabling fraud detection systems to:

• Identify repeated use of the same device across multiple accounts (e.g., account farming).

• Monitor high-risk behaviors, such as frequent transaction attempts from a single device.

• Block devices flagged for previous fraudulent activities.

Device hashes are integral in identifying and preventing fraud in real-time, as they provide consistent and reliable device identification, even without cookies.

Use Cases

Legitimate Applications

• E-Commerce Platforms: Detecting and preventing promo abuse by tracking devices used to create multiple fake accounts.

• Financial Institutions: Monitoring login attempts or transactions from devices flagged as high-risk.

• Gaming Platforms: Preventing players from bypassing bans by identifying and blocking flagged devices.

Fraudulent Scenarios

• Device Spoofing: Fraudsters manipulate or randomize device attributes to generate different hashes, evading detection.

• Account Takeover: Attackers use a previously flagged device to access compromised accounts.

• Synthetic Identity Fraud: Fraudsters link multiple synthetic accounts to a single device for coordinated fraud attempts.

Can Device Hashes Be Spoofed?

Advanced fraudsters may attempt to manipulate device attributes to generate different hashes. However, a well-implemented hash system that incorporates multiple hardware and software elements makes spoofing significantly more difficult and detectable through anomaly patterns.

How Does Device Hash Detect and Prevent Fraud

Device hashes play a critical role in fraud detection, especially when combined with other data points. Here’s how they work:

Identifying Fraudulent Behavior

For example, when cybercriminals test stolen credentials or card details, they often make multiple attempts from the same device. Despite using techniques like clearing browser cache, spoofing tools, or device emulators to disguise their activities, device hashes can link these separate actions back to the same device.

How Device Hashes Work in Fraud Detection

• Building a Suspicious Profile: Combining device hashes with cookie hashes, and browser hashes creates comprehensive profiles of suspicious activity.
• Monitoring High-Risk Behavior: Track repeated patterns, such as multiple failed login attempts or the use of stolen credentials.
• Flagging Fraudulent Activity: Flag high-risk behavior before a breach occurs.
• Identifying Spoofing and Emulation Attempts: Detect attempts to fake device identities or emulate devices to disguise the true origin of actions.‍
• Blocking Fraudulent Requests: Once fraudulent activity is detected, systems can block requests that originate from the same device, even if the fraudster tries to mask it.

Impacts on Businesses

Positive Impacts

• Enhanced Fraud Detection: Device hashes allow businesses to recognize high-risk devices across sessions, blocking repeat offenders.

• Privacy Compliance: Hashes anonymize device data, reducing privacy concerns while maintaining tracking capabilities.

• Reduced Operational Costs: Early detection of suspicious devices reduces the need for manual fraud investigations.

Negative Impacts

• False Positives: Legitimate users sharing devices (e.g., family members) may be flagged incorrectly.

• Fraud Adaptation: Fraudsters may employ device spoofing techniques to evade detection by altering or randomizing device attributes.

• Scalability Challenges: Generating and managing device hashes across large-scale operations may require robust infrastructure and resources.

Is Device Hash Collection Compliant with Privacy Regulations?

When implemented with proper anonymization and data minimization, device hash technology complies with privacy regulations. The key requirements are ensuring the hash cannot be reversed to identify individuals and providing transparent information about data collection practices.

Although device hashes provide significant advantages, businesses must continuously adapt their detection mechanisms to stay ahead of evolving fraud tactics and scale effectively.

Learn more about device hash technology and how it complements other security solutions with TrustDecision's Device Fingerprint and Fraud Management solutions.