Every day, we create 2.5 quintillion bytes of data.
Security and privacy issues are magnified by velocity, volume, and variety of
big data. Therefore, traditional security mechanisms are inadequate.
Big Data Security and Privacy is our topic of the month. Read an executive summary
of our monthly technical
Ten Big Data Security and Privacy Challenges
Introduction
The term big data refers to the massive amounts of digital information companies and governments collect about us and our surroundings. Every day, we create 2.5 quintillion bytes of data—so much that 90% of the data in the world today has been created in the last two years alone. Security and privacy issues are magnified by velocity, volume, and variety of big data, such as large-scale cloud infrastructures, diversity of data sources and formats, streaming nature of data acquisition and high volume inter-cloud migration. The use of large scale cloud infrastructures, with a diversity of software platforms, spread across large networks of computers, also increases the attack surface of the entire system.
Therefore, traditional security mechanisms, which are tailored to securing small-scale static (as opposed to streaming) data, are inadequate. In this paper, we highlight top ten big data-specific security and privacy challenges.
- Secure computations in distributed programming frameworks
- Security best practices for non-relational data stores
- Secure data storage and transactions logs
- End-point input validation/filtering
- Real-time security/compliance monitoring
- Scalable and composable privacy-preserving data mining and analytics
- Cryptographically enforced access control and secure communication
- Granular access control
- Granular audits
- Data provenance