Data and Applications Security and Privacy XXIX: 29th Annual by Pierangela Samarati

By Pierangela Samarati

This publication constitutes the refereed lawsuits of the twenty ninth Annual IFIP WG 11.3 foreign operating convention on facts and purposes safeguard and privateness, DBSec 2015, held in Fairfax, VA, united states, in July 2015. The 18 revised complete papers and six brief papers offered have been rigorously reviewed and chosen from forty five submissions. The papers are geared up within the following topical sections: info anonymization and computation; entry keep an eye on and authorization; person privateness; authentication and knowledge integration; privateness and belief; entry regulate and utilization regulations; community and net safety; and knowledge circulation and inference.

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Extra resources for Data and Applications Security and Privacy XXIX: 29th Annual IFIP WG 11.3 Working Conference, DBSec 2015, Fairfax, VA, USA, July 13-15, 2015, Proceedings

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This supports the hypothesis raised in O3. We will further discuss the implication of this observation in Sect. 5. Next, we examine the impact of different information sharing parameters. We record the relative cost of CQP under different data authorization sharing probabilities (ρDA ) and query information sharing probabilities (ρQ ) for 10,000 simulated queries, and show the result in Fig. 6d3 . We see that (O7) although increasing ρDA alone can reduce the cost of query plans (through local planning), the cost reduction is faster if coalition parties share both data authorization information and query information, and utilize CQP.

We assume that each party has a planning server, which plans its owner’s queries and offers planning service to other parties. We also assume that before executing any query, all parties have created information sharing policies according to its needs. The CQP service is similar to previous decentralized query planning frameworks [11–13] that attempt to address the problem of missing query planning information in a distributed database setting. However, the cause of insufficient information in previous scenarios was the difficulty in obtaining planning information, rather than information sharing policies.

RS , Example. E and S now plan the sub queries delegated to them. For RE E has found a semi-join based query plan QPE in Fig. 4a. For RE RS RN , S has found the plan QPS shown in Fig. 4b. We calculate the cost of these two query plans as follows: cost(QPE ) = 1000 × 3 + 500 × 3 + 2000 × 10 = 24, 500 and cost(QPS ) = 1000 × 3 + 1000 × 3 + 5000 × 3 + 3000 × 10 = 51, 000. Both plans are filtered based on authorization sharing policies in Table 2. Towards Collaborative Query Planning in Multi-party Database Networks 27 Algorithm 2: Query plan filtering.

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