Developing and Securing the Cloud

529

Chapter 31

Integrity Management,

Data Provenance, and

Cloud Services

31.1 Overview

In this chapter, we will discuss integrity management for cloud services. Integrity

includes several aspects. In the database world, integrity includes concurrency con-

trol and recovery as well as enforcing integrity constraints. For example, when mul-

tiple transactions are executed at the same time, the consistency of the data has to

be ensured. When a transaction aborts, it has to be ensured that the database is

recovered from the failure into a consistent state. Integrity constraints are rules that

have to be satisfied by the data. e rules include “salary value has to be positive”

and “age of an employee cannot decrease over time.” More recently, integrity has

included data quality, data provenance, data currency, real-time processing, and

fault tolerance.

In this chapter, we discuss the aspects of integrity for cloud services as well as

implementing integrity management as cloud services. For example, how do we

ensure the integrity of the data and the processes? How do we ensure that data

quality is maintained? e organization of this chapter is as follows. In Section

31.2, we discuss the aspects of integrity, data quality, and provenance. In particular,

integrity aspects will be discussed in Section 31.2.1. Data quality and provenance

will be discussed in Section 31.2.2. Detecting security threats and misuse with

data provenance will be discussed in Section 31.2.3. Cloud services and integrity

530  ◾  Developing and Securing the Cloud

management are discussed in Section 31.3. In particular, data integrity and prov-

enance as cloud services will be discussed in Section 31.3.1. Data integrity for cloud

services will be discussed in Section 31.3.2. is chapter concludes with Section

31.4. e aspects of integrity are illustrated in Figure 31.1.

31.2 Integrity, Data Quality, and Provenance

31.2.1 Aspects of Integrity

ere are many aspects of integrity. For example, concurrency control, recovery,

data accuracy, meeting real-time constraints, data accuracy, data quality, data

provenance, fault tolerance, and integrity constraint enforcement are all aspects

of integrity management. is is illustrated in Figure 31.1. In this section, we will

examine each aspect of integrity.

Concurrency control: In data management, concurrency control is about trans-

actions that are executed at the same time and ensuring the consistency of the data.

erefore, transactions have to obtain locks or utilize time stamps to ensure that

the data are left in a consistent state when multiple transactions attempt to access

the data at the same time. Extensive research has been carried out on concurrency-

control techniques for transaction management both in centralized and in distrib-

uted environments [BERN87].

Data recovery: When transactions abort before they complete execution, the

database should be recovered to a consistent state such as its state before the trans-

action started execution. Several recovery techniques have been proposed to ensure

the consistency of the data.

Data authenticity: When the data are delivered to the user, their authenticity has

to be ensured. at is, the user should get the accurate data and the data should not

be tampered with. We have conducted research on ensuring authenticity of XML

data during third-party publishing [BERT04].

Data quality

and

provenance

Concurrency

control

and

recovery

Integrity

of the

agents

Integrity

of the

websites

Aspects

of

integrity

Figure 31.1 Aspects of integrity.