Efficient Proactive Security for Sensitive Data Storage Arun Subbiah Douglas M. Blough School of ECE, Georgia Tech {arun, dblough}@ece.gatech.edu

Efficient Proactive Security for Sensitive Data Storage

Arun Subbiah

Douglas M. Blough

School of ECE, Georgia Tech{arun, dblough}@ece.gatech.edu

Efficient Proactive Security for Sensitive Data StorageArun Subbiah, Douglas M. Blough {arun, dblough}@ece.gatech.edu

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Autonomic Proactive

Detect failures Repair

Distributed Data Storage System

Autonomic

Periodic refresh

Proactive

Autonomic / self-healing / adaptive– Detect storage node failure / compromise, then repair

Proactive security and fault-tolerance– Refresh and renew, don’t rely on failure detector


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Failure Detector for Byzantine Quorum Systems

Integrated into a distributed filesystem prototype L. Kong, A. Subbiah, M. Ahamad, and D. M. Blough, "A Reconfigurable Byzantine Quorum

Approach for the Agile Store," SRDS 2003 L. Kong, D. J. Manohar, A. Subbiah, M. Sun, M. Ahamad, and D. M. Blough, "Agile Store:

Experience with Quorum-Based Data Replication Techniques for Adaptive Byzantine Fault Tolerance," SRDS 2005

FD

FD

FD

FD

FD

Diagnosis Server

Byzantine Quorum System

Users


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Failure Detector Performance in Byzantine Quorum Systems

Probability of detection

badp


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Proactive Security – Integrity and Confidentiality Protection

p

SVR1 SVR2 SVR3

Time Interval 1

Time Interval 2

Time Interval 3

Time Interval 4


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Proactive Security – Confidentiality Protection

Data storage using perfect secret sharing

Problem: Perfect secret sharing schemes have high computation overhead; do not scale with large amounts of data

Solution: The GridSharing Framework: Use XOR and replication

A. Subbiah and D. M. Blough, "An Approach for Fault Tolerant and Secure Data Storage in Collaborative Work Environments," Workshop on Storage Security and

Survivability, ACM CCS, 2005


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Computation Overheads for Perfect Secret Sharing

Verifiable secret sharing: Feldman’s scheme with Shamir’s scheme– Computation times during encoding and decoding over 700 ms

• For any 3 out of 5 shares scheme

Compare with AES (Rijndael) symmetric key encryption– Encryption and decryption times approx. 205 μs

Perfect secret sharing is over 3000 times slower than symmetric-key encryption

The GridSharing framework: < 1 ms

Computation times for an 8 KB data block on a Pentium 4 3GHz computer.


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Proactive Security – Integrity Protection

Each server periodically checks the integrity of its stored data with other servers.

Repair if any corruptions are detected.

Assume metadata is replicated at all servers

Users


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A Proactively-Secure Document Store

Users upload / download encrypted documents. Documents stored at all the servers. Experiments run on the Emulab cluster (http://www.emulab.net).

Users

100 Mbps LAN 1 Gbps

LAN

Time Interval Marker

Diagnosis Server

All machines: 3 GHz, 64-bit Xeon, 2 GB RAM, 146 GB hard disk


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Throughput Measurement


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Storage Repair Rate


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PhD Work

Byzantine-fault detection algorithms– Integrated with Reconfigurable Quorums to give Agile Store.

Coding techniques for distributed storage– First secret sharing technique that scales with large amounts of data.

Protocol design for integrity and confidentiality protection Prototype implementation and performance evaluation

– First practical proactively-secure data store.

– Scales to 100s GB of data.

More info: http://www.arunsubbiah.com