Homomorphic Encryption Market Size

Homomorphic Encryption Market Size

Homomorphic Encryption Market size was valued at USD 178.4 million in 2023 and is projected to grow at a CAGR of over 8% from 2024 to 2032, owing to the increase in cyber-attacks, including data breaches and ransomware. According to the Federal Bureau of Investigation, Internet Crime Report, in 2023, ransomware incidents noted over 2,285 complaints representing an increase of over 18% from 2022 with losses rising 74% from USD 34.3 million to USD 59.6 million.

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Also, the report highlights the emerging ransomware trends including the deployment of multiple ransomware variants against the same victim and the use of data-destruction tactics to increase pressure on victims to negotiate. This evolving cyber threat requires advanced encryption techniques that protect data during processing, not just when it is stored or transmitted. Homomorphic encryption provides a way to perform computations on encrypted data, minimizing the risk of exposure even if data is intercepted. This is expected to drive the growth of the market during the forecast period.

As organizations increasingly move their data and applications to the cloud, they face the challenge of securing sensitive information during processing. Traditional encryption protects data at rest and in transit. However, once data is decrypted for processing or analysis, it becomes vulnerable to unauthorized access and cyberattacks. This vulnerability is a significant security risk, particularly in cloud environments where multiple users and services share the same infrastructure. Homomorphic encryption solves this problem by allowing data to be processed while still encrypted, eliminating the need for decryption. This innovation changes how data can be securely managed in the cloud.

Homomorphic encryption requires a lot of computing power. Operations on encrypted data require significantly more processing power and time compared to operations on unencrypted data. This can cause delays and slow performance, particularly for complex computations or large datasets. Additionally, the need for powerful processors and large amounts of memory can make homomorphic encryption impractical for some applications, particularly those requiring real-time processing or where resources are limited.