Data Protection in Collaborative Business Applications

Data Protection in Collaborative Business Applications

Florian Kerschbaum (SAP Research CEC Karlsruhe, Germany)
Copyright: © 2010 |Pages: 30
DOI: 10.4018/978-1-60566-414-9.ch005
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Abstract

Collaborative business applications are an active field of research and an emerging practice in industry. This chapter will focus on data protection in b2b applications which offer a wide range of business models and architecture, since often equal partners are involved in the transactions. It will present three distinct applications, their business models, security requirements and the newest solutions for solving these problems. The three applications are collaborative benchmarking, fraud detection and supply chain management. Many of these applications will not be realized if no appropriate measure for protecting the collaborating parties’ data are taken. This chapter focuses on the strongest form of data protection. The business secrets are kept entirely secret from other parties (or at least to the degree possible). This also corresponds to the strongest form of privacy protection in many instances. The private information does not leave the producing system, (i.e., data protection), such that the information producer remains its sole owner. In case of B2B application, the sensitive data are usually business secrets, and not personally identifiable data as in privacy protection.
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Introduction

Collaborative business applications are an active field of research and an emerging practice in industry. Collaborative business applications can be classified into business-to-consumer (B2C) and business-to-business (B2B) applications. Electronic B2C applications are of great interest with the advent of the Internet as an additional sales channel, but are usually restricted in their business model and architecture to classical client-server matching the buyer-seller relationship. B2B applications offer a much wider range of business models and architecture, since often equal partners are involved in the transactions. The security requirements resulting from these architectures therefore also span a much broader variety than in the B2C area.

This chapter will focus on data protection in B2B applications. It will present three distinct applications, their business models, security requirements and the newest solutions for solving these problems. The three applications are collaborative benchmarking, fraud detection and supply chain management. Each application has its own business model and architecture.

In each of these applications data protection is of the utmost importance. Many of these applications will not be realized if not appropriate measure for protecting the collaborating parties’ data are taken. The involved data usually consists of business secrets whose revelation would impact the position of the company, e.g. its negotiation position or external recognition. This data is therefore associated with a risk of revelation, and the effect of data protection can be financially measured with risk analysis.

This chapter focuses on the strongest form of data protection. The business secrets are kept entirely secret from other parties (or at least to the degree possible). Each party is seen as an entity that is either entirely compromised or intact and can perform computations without being inspected. Then there is a protocol that relies on cryptographic protection run between the parties. One can show that (under certain assumptions) nothing can be inferred from the protocol except the result.

This also corresponds to the strongest form of privacy protection in many instances. The private information does not leave the producing system, i.e. data protection, such that the information producer remains its sole owner. In case of B2B application, the sensitive data are usually business secrets, and not personally identifiable data as in privacy protection. The value of business secrets can often be higher than that often irrationally low value of personal information as many studies suggest (Acquisti 2004, Cvrcek et al. 2006). Therefore the protection of data in collaborative business applications can be much better economically motivated than its counterpart privacy.

The motivation for collaboration in these business applications stems from an economic benefit that cannot be achieved by a party by itself, i.e. the motivational factor is not enhanced security, but economics. Nevertheless as mentioned before many of these applications will not be realized, if not appropriate security measures are in place. In particular this chapter is concerned with the information gain, such applications can provide and that can be an effective obstacle to the realization of the application. The economic benefit is therefore tied to the security requirements which usually stem from the business model and so data protection enables an economic benefit.

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