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How are data in process different from data at rest or in storage?

Data can exist in different states – at rest, in transit, and in process. Understanding the differences between these data states is crucial for implementing proper security measures. This article will examine how data in process differs from data at rest or data in storage.

With the rapid digitization of information, organizations are generating and storing more data than ever before. This data powers key business functions and contains sensitive information like customer details, financial records, intellectual property, and more. Securing and protecting this data is a top priority.

To do so effectively, organizations must understand the different states that data can exist in. Broadly speaking, data states fall into three categories:

  • Data at rest – Data that is persisted and stored on disk or other media.
  • Data in transit – Data that is being transmitted across networks.
  • Data in process – Data that is being acted upon and processed.

Each data state presents different security considerations. This article will focus on how data in process differs from data at rest or data in storage.

Defining Data at Rest and Data in Storage

Before examining data in process, let’s clearly define data at rest and data in storage:

  • Data at rest refers to all data that is persisted and stored on any form of physical media. This includes data stored on hard drives, external disks, networked drives, SSDs, optical media, tape backups, and more. Data at rest is idle and passive – it is not moving and not being processed.
  • Data in storage is essentially synonymous with data at rest. It refers to inactive data that resides in persistent storage media. This encompasses databases, data warehouses, file shares, archives, backups, and any other repositories where data is stored.

In summary, data at rest and data in storage imply the same meaning – data that is not transiting a network or being processed, but is persistently stored and idle.

Defining Data in Process

Data in process refers to data that is actively being processed and acted upon within a computing system. More specifically:

  • Data becomes “in process” when an application or service retrieves it from storage into memory for performing computations and operations.
  • “In process” data resides in temporary memory like RAM while being used by a CPU, GPU, or other processing unit.
  • Once processing finishes, data may be discarded from memory or persisted back to storage, returning to a “rest” state.

In essence, data in process is active data that is being accessed, manipulated, transformed, and computed on by applications and services.

Key Differences Between Data in Process and Data at Rest

There are several key differences between data in process compared to data at rest or in storage:

Location

The most fundamental difference is location. Data at rest resides in persistent storage media like hard drives, databases, and data warehouses. Data in process temporarily resides in volatile memory like RAM while being computed on.

Lifetime

Data at rest persists indefinitely – it continues existing in storage until deleted or overwritten. Data in process is transient – it only temporarily exists in memory during processing before being discarded or persisted back to storage.

Accessibility

Data at rest must be read from storage before use. Data in process is already loaded into memory and immediately accessible by processing units.

State

Data at rest is idle/inactive. Data in process is active and being operated on.

Security

Data at rest can leverage certain security mechanisms like file system permissions, database access controls, and encryption. These mechanisms are not applicable to data in process residing in memory.

Security Risks and Challenges

The different characteristics of data in process present unique security challenges:

  • No inherent access controls – Processing units can directly access in-memory data without any file system or database access controls.
  • Vulnerable to exploits – Software vulnerabilities may allow attackers to read or manipulate in-memory data.
  • Unencrypted – Data in process often resides in memory unencrypted even if stored encrypted on disk.
  • Memory scraping – Malware or malicious insiders may scrape sensitive data from memory.
  • Data remanence – Data in volatile memory can persist for seconds to minutes after power loss.

These risks necessitate additional security measures for data in process which we will discuss next.

Securing Data in Process

Protecting data in process brings unique challenges compared to securing data at rest. Some key measures include:

Access controls

Use memory access control mechanisms provided by CPUs and operating systems to prevent unauthorized access to process memory space.

Encryption

Leverage in-memory encryption technologies to encrypt data within RAM. This mitigates memory scraping risks.

Memory wiping

Overwrite freed memory locations to prevent data remanence in volatile memory.

Code integrity

Employ code signing to validate software integrity and prevent execution of malicious code.

Process isolation

Isolate compute processes into separate protected memory regions to limit access.

Trusted execution

Utilize trusted execution environments provided by CPUs to secure sensitive processing.

Intrusion detection

Monitor for signs of memory tampering and unexpected memory access patterns.

Data in Process vs. Data in Transit

Data in process should not be confused with data in transit. Data in transit refers to data being transmitted over networks. Some key differences:

Factor Data in Process Data in Transit
Location Temporary memory (RAM) Network cables/wireless
State Active – being processed Active – being transmitted
Security Access controls, encryption Encryption, tunneling
Lifetime Transient – temporary Temporary during transmission

As shown, both data in process and in transit are active/temporary states unlike data at rest. However, data in process resides locally in memory while data in transit is physically moving across networks.

Recommendations

Based on our analysis, here are some key recommendations for securing data in process:

  • Classify which data absolutely requires protection when in memory to guide security measures.
  • Assess risk levels – threat models, impact of exposure, types of processing performed.
  • Evaluate hardware-based security technologies like secure enclaves offered by AMD and Intel.
  • Implement least privilege – only expose data to processes and users that need access.
  • Train developers on secure coding practices to avoid vulnerabilities.
  • Continuously monitor controls and emerging threats to data in process.

Conclusion

Data in process presents unique security challenges compared to data at rest:

  • Resides unencrypted in volatile memory while active.
  • Bypasses access controls that apply to data on disk.
  • Directly accessible by processors once in memory.
  • Susceptible to exploits, memory scraping, data remanence.

Specific measures must be taken to protect data actively being processed beyond traditional data at rest protections. Going forward, securing data in process will become an increasingly critical aspect of defense as threats evolve.