Privacy and Integrity Preserving in Distributed Systems Presented for Ph.D. Qualifying Examination Fei Chen Michigan State University August 25 th, 2009

Introduction  Data collection and publishing is a core operation in many distributed systems  Outsourced database systems Organizations outsource their databases to service providers Organizations can focus on their core tasks without considering the management of their database  Two-tiered wireless sensor networks Storage nodes gather data from nearby sensors and process queries from the sink Power and storage saving for sensors as well as the efficiency of query processing

Outsourced database systems  Outsourcing databases offers many advantages  Significantly reduce the management cost of organizations  Service Providers have higher bandwidths and lower latencies  Having multiple service providers helps to avoid the organizations being a single point of failure Database Outsourced Database Organizations Service Provider Customer Query Result Query Result Query Result Database  An outsourced database system

Two-tired sensor networks  A two-tired sensor network  Benefits  Power saving for sensors  Memory saving for sensors  Query processing becomes more efficient Data Storage Node Sensor Query Result Sensor Sink Sensor

Comparison between two distributed systems  Similarity  Three common parties Data owners, i.e., organizations and sensors Data publishers, i.e., service providers and storage nodes Users, i.e., customers and the sink  The two distributed systems can be modeled as There may be multiple publishers For outsourced database systems, there may be multiple users For two-tiered sensor networks, there are multiple data owners  Difference  For outsourced database systems, users may not be fully trusted by data owners  For two-tiered sensor networks, the sink is fully trusted by sensors Data Outsourced Data Data Owner Data Publisher User Query Result

Security Challenges  Due to the important role of data publishers, there are two security challenges  Preserve privacy of the data stored in a data publisher Data Outsourced Data Data Owner Data Publisher User Query Result Untrusted Data Encrypted How can a data publisher search the query result over the encrypted data?

Security Challenges  Preserve integrity of a query result from a data publisher Data Outsourced Data Data Owner Data Publisher User Query Result Database Untrusted manipulate results (1)Forge data (2)Return portion of the result How can we prevent the misbehavior of data publishers?

Problem Statement  Design the storage scheme and query protocol in a privacy and integrity preserving manner  Data and query privacy Publishers cannot figure out the original data Publishers cannot figure out queries  Queries over data Data publishers can search query results over the encrypted data, e.g., range queries.  Query result integrity Users can detect whether a query result contains forged data or misses some legitimate data.  Efficiency e.g. communication and computation cost

The Proposed Approaches  To preserve the privacy of the data, the data owner encrypts the data  To enable the searching operation for data publishers, the data owner encodes the private data in a format which supports the searching operation  To preserve the integrity of query results, the data owner computes verification objects (VOs) for all possible queries Let {t 1, t 2, …, t m } denote the data of a data owner, the basic idea is illustrated Data Publisher User search(query ) encrypt(t i1 ), …, encrypt(t ig ) Data Owner {encrypt(t 1 ), …, encrypt(t m )} {t 1, …, t m } search(t 1, …, t m ) query VOs(t 1, …, t m ) VO(t i1, …, t ig )

Previous Work  Outsourced database systems  Preserving Privacy Bucket Partition [Hacigumus et al., SIGMOD 2002] A Public-key system [Boneh and Waters, TCC 2007]  Preserving Integrity Merkle hash trees [Devanbu et al., Journal of Computer Security 2003] Signature aggregation and chaining techniques [Narasimha and Tsudik, DASFAA 2006] Spatial data structures [Chen et al., ESORICS 2008]  Two-tiered sensor networks S&L scheme [Infocom 2008] The optimized version of S&L scheme [Infocom 2009, Mobihoc 2009]

Privacy in outsourced database systems  Bucket Partition [Hacigumus et al., SIGMOD 2002] Data Publisher Result: Data owner (Key K i ) User (Key K i ) {2,5,9,15,20,23,34,40} {2,5,9} Ki {15,20,23} Ki {34,40} Ki Bucket ids : [35,45] 3, 4 {34,40} Ki Return more data Outsourced Database

Privacy in outsourced database systems  Bucket Partition  Drawbacks  A query result may have false positive errors  It allows data publishers to obtain a reasonable estimation on the actual value of data items and queries

Privacy in outsourced database systems  A Public key system [Boneh and Waters, TCC 2007]  Hidden Vector Encryption Using bilinear groups to produce tokens for searching conjunctive, subset, and range queries on an encrypted database.  Drawback  Computationally expensive Public key cryptography Require a database owner to perform O(zD) encryption for each tuple, where z is the number of dimensions and D is the domain size

Integrity in outsourced database systems  Merkle hash trees [Devanbu et al., Journal of Computer Security 2003] H 18 H 1 =h((d 1 ) k i ) H 12 =h(H 1 |H 2 ) H 14 =h(H 12 |H 34 ) H 18 =h (H 14 |H 58 ) H4H4 H3H3 H 34 H 14 H2H2 H1H1 H 12 H8H8 H7H7 H 78 H 58 H6H6 H5H5 H 56 (d1)ki(d1)ki (d2)ki(d2)ki (d3)ki(d3)ki (d4)ki(d4)ki (d5)ki(d5)ki (d6)ki(d6)ki (d7)ki(d7)ki (d8)ki(d8)ki

Integrity in outsourced database systems  Merkle hash trees H 18 Query [10, 30] Query result Verification object H 14 H 58 H 34 H 12 H 56 H1H1 H 78 H2H2 H3H3 H4H4 H5H5 H6H6 H7H7 H8H8 (2) k i (5) k i (9) k i (15) k i (20) k i (23) k i (34) k i (40) k i

Integrity in outsourced database systems  Drawbacks  A query result has false positive errors  It is hard to extend Merkle hash trees to verify the integrity for multi- dimensional data H 18 Query [10, 14] Query result H 14 H 58 H 34 H 12 H 56 H1H1 H 78 H2H2 H3H3 H4H4 H5H5 H6H6 H7H7 H8H8 (2) k i (5) k i (9) k i (15) k i (20) k i (23) k i (34) k i (40) k i Verification object

Integrity in outsourced database systems  Signature Aggregation and Chaining  It aggregates multiple individual signatures into one unified signature Verifying the unified signature is equivalent to verifying all individual signatures  It presents a signature chain that links a signature of a data item with the signatures of the data item’s neighbors  Drawbacks  A query result has false positive errors  It is computationally expensive to verify the integrity of multi- dimensional data

Integrity in outsourced database systems  Spatial Data Structures [Chen et al., ESORICS 2008]

Integrity in outsourced database systems  Chen et al. proposed a Canonical Range Tree (CRT) to count the number of data items in access control areas and query spaces.  Advantages  No false positive errors. Do not need to provide the boundary data items.  It can be used to perform access control  Drawbacks  Only can be applied for range queries, while SQL includes other types of queries

Privacy and Integrity in Two-tiered sensor networks  S&L scheme [Infocom 2008]  Two major drawbacks  Fairly accurate estimating data items and quires  Power and space consumption grows exponentionally with the number of dimensions. Data Storage Node Query Sensor S i (Key K i ) Sink (Key K i ) {1, 4, 5, 7, 9} {1,4} Ki {5} Ki h(i||4||t||K i ) {7, 9} Ki Bucket IDs: [9,10] 3, 4 h(i||4||t||K i ) 7 is out of the range Prove empty bucket {7, 9} Ki Result:

Privacy and Integrity in Two-tiered sensor networks  Optimized version of S&L scheme  For one-dimensional data [Infocom 2009] Embed relationships among data collected by each sensor Define a vector where each bit indicates whether the node has data in the corresponding bucket or not Storage Node Sensor 3 Sensor 2 Sensor 1 2,5,915,20,23 34,40 Bucket Vector V 1 : V1V1 V1V1 318 {3, 1110} Ki {18, 1110} Ki

Privacy and Integrity in Two-tiered sensor networks Storage Node Sensor 3 Sensor 2 Sensor 1 V1V1 V1V (12,5) ki (15,6) ki (23,4) ki (45,3) ki  For Multi-dimensional data [Mobihoc 2009]  These two schemes are less secure than S&L’s scheme  They inherit the same weakness of allowing storage nodes to estimate the original data and queries  The optimization technique allows a compromised sensor to easily compromise the integrity verification functionality of the network Send falsified bit maps to sensors and storage nodes V 1 =

Future Research Directions  For outsourced database systems  No complete solutions of preserving privacy and integrity for outsourced database systems  Preserving privacy and integrity for multi-dimensional data is not well studied  For two-tiered sensor networks  Prevent a storage node from estimating data and queries  Multi-dimensional data  Efficiency

Questions Thank you!