Abstract
Purpose – The purpose of this paper is to examine how the introduction of new communication channels facilitates interactive information sharing and collaboration between various actors over social networking services and how social networking fits in the existing European legal framework on data protection. The paper also aims to discuss some specific data protection issues, focusing on the role of the relevant actors, using the example of photo tagging. Design/methodology/approach – Privacy in social networks is one of the main concerns for providers and users. This paper examines the role of the main actors in social networking, i.e. the providers and the users, scrutinised under the light of the European data protection legislation. Specifically, how social networking service providers deal with users' privacy and how users handle their personal information, if this manipulation is complied with the respective legislation and how “tagging”, one of the most familiar services provided by the social networking providers, may cause privacy risks. Findings – Social networking is one of the most remarkable cultural phenomena that has blossomed in the Web 2.0 era. They enable the connection of users and they facilitate the exchange of information among them. However, the users reveal vast amounts of personal information over social networking services, without realising the privacy and security risks arising from their actions. The European data protection legislation could be used as a means for protecting the users against the unlawful processing of their personal information, although a number of problems arise regarding its applicability. Originality/value – The paper discusses some privacy concerns involved in social networks and examines how social networking service providers and users deal with personal information with regard to the European data protection legislation.

Abstract
This paper addresses the controversy between employees right to privacy and employers need to safeguard organizational resources by employing monitoring tools. It shows how organizations can formulate use policies, by applying basic principles for fair and lawful monitoring. A list of key points is presented, which organizations should take into account, for developing such policies. Finally, the paper explores how, widely accepted information security standards, such as the ISO 17799, can aid the attempt to address this controversy.

Abstract
Purpose – This paper seeks to provide an overview of the major technical, organizational and legal issues pertaining to the outsourcing of IS/IT security services. Design/methodology/approach – The paper uses a combined socio-technical approach to explore the different aspects of IS/IT security outsourcing and suggests a framework for accommodating security and privacy requirements that arise in outsourcing arrangements. Findings – Data protection requirements are a decisive factor for IS/IT security outsourcing, not only because they pose restrictions to management, but also because security and privacy concerns are commonly cited among the most important concerns prohibiting organizations from IS/IT outsourcing. New emerging trends such as outsourcing in third countries, pose significant new issues, with regard to meeting data protection requirements. Originality/value – The paper illustrates the reasons for which the outsourcing of IS/IT security needs to be examined under a different perspective from traditional IS/IT outsourcing. It focuses on the specific issue of personal data protection requirements that must be accommodated, according to the European Union directive.

Abstract
Purpose – The objective of this paper is to investigate the legal and technical reasons why a declaration of will, denoted by a digital signature, can be cancelled and how this cancellation can be technically achieved. Design/methodology/approach – Proposes a technical framework for establishing a signature revocation mechanism based on special data structures, the signature revocation tokens (SRT), and investigates the alternatives for disseminating the signature status information (SSI) to the relying parties. Findings – A relying party has to take into consideration the possible existence of a signature revocation, in order to decide on the validity of a digital signature. A scheme based on a central public repository for the archival and distribution of signature revocation tokens exhibits significant advantages against other alternatives. Originality/value – Identifies various intrinsic problems of the digital signature creation process that raise several questions on whether the signer performs a conscious and wilful act, although he/she is held liable for this action. The law faces the eventual right of the signer to claim a revocation of a previously made declaration of will, especially in cases of an error, fraud

Abstract
Traditionally public decision-makers have been given discretion in many of the decisions they have to make in how to comply with legislation and policies. In this way, the context and specific circumstances can be taken into account when making decisions. This enables more acceptable solutions, but at the same time, discretion might result in treating individuals differently. With the advance of AI-based decisions, the role of the decision-makers is changing. The automation might result in fully automated decisions, humans in-the-loop or AI might only be used as recommender systems in which humans have the discretion to deviate from the suggested decision. The predictability of and the accountability of the decisions might vary in these circumstances, although humans always remain accountable. Hence, there is a need for human-control and the decision-makers should be given sufficient authority to control the system and deal with undesired outcomes. In this direction this paper analyzes the degree of discretion and human control needed in AI-driven decision-making in government. Our analysis is based on the legal requirements set/posed to the administration, by the extensive legal frameworks that have been created for its operation, concerning the rule of law, the fairness – non-discrimination, the justifiability and accountability, and the certainty/ predictability.

Abstract
The rapid growth of Information and Communication Technologies emerges deep concerns on how data mining techniques and intelligent systems parse, analyze and manage enormous amount of data. Due to sensitive information contained within, data can be exploited by potential aggressors. Previous research has shown the most accurate approach to acquire knowledge from data while simultaneously preserving privacy is the exploitation of cryptography. In this paper we introduce an extension of a privacy preserving data mining algorithm designed and developed for both horizontally and vertically partitioned databases. The proposed algorithm exploits the multi-candidate election schema and its capabilities to build a privacy preserving Tree Augmented Naive Bayesian classifier. Security analysis and experimental results ensure the preservation of private data throughout mining processes.

Abstract
Cloud Computing (CC) is a promising next-generation computing paradigm providing network and computing resources on demand via the web. The cloud market is still in its infancy and all major issues, ranging from interoperability and standardization, to legislation and SLA contracts are still wide open. However, the main obstacle for a more catholic acceptance of the cloud model is security. In the CC model, the client has limited control over her data and computations as she outsources everything to the cloud provider. This basic CC feature influences several security related areas.

Abstract
Privacy preserving analysis of a social network aims at a better understanding of the network and its behavior, while at the same time protecting the privacy of its individuals. We propose an anonymization method for weighted graphs, i.e., for social networks where the strengths of links are important. This is in contrast with many previous studies which only consider unweighted graphs. Weights can be essential for social network analysis, but they pose new challenges to privacy preserving network analysis. In this paper, we mainly consider prevention of identity disclosure, but we also touch on edge and edge weight disclosure in weighted graphs. We propose a method that provides k-anonymity of nodes against attacks where the adversary has information about the structure of the network, including its edge weights. The method is efficient, and it has been evaluated in terms of privacy and utility on real word datasets.

Abstract
Technological and social phenomena like cloud computing, behavioural advertising, online social networks as well as globalisation (of data flows) have profoundly transformed the way in which personal data are processed and used. This paper discusses the efficiency of the legislation in force and the impact of PETs and the concept of privacy by design on the enforcement of data protection rules. By recognizing the need to update the data protection regulation as a result of current technological trends that threaten to erode core principles of data protection, the paper addresses the question if the Draft-Regulation presents an adequate and efficient response to the challenges that technological changes pose to regulators. In this context the paper focuses on the right to be forgotten as a comprehensive set of existing and new rules to better cope with privacy risks online in the age of “perfect remembering” and we how persistency and high availability of information limit the right of individuals to be forgotten. The paper deals with both the normative and the technical instruments and requirements so as to ensure that personal information will not be permanently retained.

Abstract
The evolution of new technologies and the spread of the Internet have led to the exchange and elaboration of massive amounts of data. Simultaneously, intelligent systems that parse and analyze patterns within data are gaining popularity. Many of these data contain sensitive information, a fact that leads to serious concerns on how such data should be managed and used from data mining techniques. Extracting knowledge from statistical databases is an essential step towards deploying intelligent systems that assist in making decisions, but also must preserve the privacy of parties involved. In this paper, we present a novel privacy preserving data mining algorithm from statistical databases that are horizontally partitioned. The novelty lies to the multi-candidate election schema and its capabilities of being a basic foundation for a privacy preserving Tree Augmented Naïve Bayesian (TAN) classifier, in order to obviate disclosure of personal information.

Abstract
It is widely accepted that electronic Government environments have caused a complete transformation of the way individuals, businesses and governmental agencies interact with central government. However, the acceptance and success of e-Government services largely depend on the level of trust and confidence developed by the users to the provided services and the overall system security. Thus the employment of the appropriate authentication framework is a crucial factor. This paper focuses on the way to determine the appropriate trust level of an electronic service. Specifically, it provides guidelines according to the data required for a transaction, as well as to the available authentication and registration mechanisms. Moreover, a Single Sign-On architecture is proposed, supporting a uniform authentication procedure that depends on the level of trust required by the service. In the aforementioned research work specific requirements and limitations for Greece have been taken into account.

Abstract
This paper provides a combined approach on the major issues pertaining to the investigation of cyber crimes and the deployment of Internet forensics techniques. It discusses major issues from a technical and legal perspective and provides general directions on how these issues can be tackled. The paper also discusses the implications of data mining techniques and the issue of privacy protection with regard to the use of forensics methods.