| 1. Security Types |
2. Scenario |
3. Challenges |
4. Description |
5. Threats |
6. Current Mitigations |
| Infrastructure Security |
Application Computation Infrastructure |
Secure computations in distributed programming frameworks |
Distributed programming frameworks utilize parallelism in computation and storage to process massive amounts of data. |
Malfunctioning compute worker nodes |
Trust establishment: initiation, periodic trust update |
| Access to sensitive data |
Mandatory access control |
||||
| Privacy of output information |
Privacy preserving transformations |
||||
| Data from Diverse Appliances and Sensors |
Security best practices for non-relational stores |
Non-relational data stores popularized by NoSQL databases are still evolving with respect to security infrastructure. |
Lack of stringent authentication and authorization mechanisms |
Enforcement through middleware layer |
|
| Passwords should never be held in clear |
|||||
| Encrypted data at rest |
|||||
| Lack of secure communication between compute nodes |
Protect communication using SSL/TLS |
||||
| Data Management |
Consumer Data Archive |
Secure data storage and transactions logs |
The exponential increasing of data set requires auto-tiering for big data storage management. |
Data Confidentiality and Integrity |
Encryption and signatures |
| Availability |
Proof of data possession |
||||
| Consistency |
Periodic audit and hash chains |
||||
| Collusion |
Policy based encryption |
||||
| Data Management |
Audit of usage, pricing, billing |
Granular audits |
In order to be notified at the attack takes place, we need audit information. |
Completeness of audit information |
Infrastructure solutions as discussed before. Scaling of SIEM tools. |
| Timely access to audit information |
|||||
| Integrity of audit information |
|||||
| Authorized access to audit information |
|||||
| Keeping track of ownership of data pricing, audit |
Data provenance |
Analysis of large provenance graphs to detect metadata dependencies for security/confidentiality applications is computationally intensive. |
Secure collection of data |
Authentication techniques |
|
| Consistency of data and metadata |
Message digests |
||||
| Insider threats |
Access Control through systems and cryptography |