Pietro Colombo

Secure Wireless Multimedia Sensor Networks: A Survey

Wireless Multimedia Sensor Networks (WMSNs) are used in many application domains, such as surveillance systems, telemedicine and so on. In order to ensure a broad deployment of such innovative services, strict requirements on security, privacy, and distributed processing of multimedia contents should be satisfied, taking also into account the limited technological resources (in term of energy, computation, bandwidth, and storage) of sensor nodes. Thus, with respect to classic Wireless Sensor Networks, the achievement of these goals is more challenging due to the presence of multimedia data, which usually requires complex compression and aggregation algorithms. In order to provide a unifying synthesis on the last achievements, this survey summarizes the main findings on secure WMSNs proposed in the literature and forecasts future perspectives of such a technology.

Privacy Aware Access Control for Big Data

Big Data is an emerging phenomenon that is rapidly changing business models and work styles 1. Big Data platforms allow the storage and analysis of high volumes of data with heterogeneous format from different sources. This integrated analysis allows the derivation of properties and correlations among data that can then be used for a variety of purposes, such as making predictions that can profitably affect decision processes. As a matter of fact, nowadays Big Data analytics are generally considered an asset for making business decisions. Big Data platforms have been specifically designed to support advanced form of analytics satisfying strict performance and scalability requirements. However, no proper consideration has been devoted so far to data protection. Indeed, although the analyzed data often include personal and sensitive information, with relevant threats to privacy implied by the analysis, so far Big Data platforms integrate quite basic form of access control, and no support for privacy policies. Although the potential benefits of data analysis are manifold, the lack of proper data protection mechanisms may prevent the adoption of Big Data analytics by several companies. This motivates the fundamental need to integrate privacy and security awareness into Big Data platforms. In this paper, we do a first step to achieve this ambitious goal, discussing research issues related to the definition of a framework that supports the integration of privacy aware access control features into existing Big Data platforms.

Enforcement of Purpose Based Access Control within Relational Database Management Systems

Privacy is becoming a key requirement for ICT applications that handle personal data. However, Database Management Systems (DBMSs), which are devoted to data collection and processing by definition, still do not provide the proper support for privacy policies. Policies are enforced by ad-hoc programmed software modules that complement DBMS access control services. This practice is time consuming, error prone, and neither general nor scalable. This work does a first step to overcome these limits. We propose a systematic approach to the automatic development of a monitor that regulates the execution of SQL queries based on purpose based privacy policies. The proposed solution does not require programming, it is general, platform independent and usable with most of the existing relational DBMSs.

GuardMR: Fine-grained Security Policy Enforcement for MapReduce Systems

Executing data analytics tasks in MapReduce systems introduces new security and privacy concerns as the processed unstructured datasets may contain sensitive information (e.g., social security numbers, business sensitive information) at the level of individual records, and the existing file-level access control mechanisms provide all or nothing access to the entire dataset. To address these concerns, we propose GUARDMR which is a novel, modular framework that can enforce fine-grained security policies at the key-value level in MapReduce systems. The presented security policies can dynamically create authorized views of data resources based on the organizational roles of the MapReduce users. GUARDMR further simplifies the specification of authorized views via automatically generating the bytecode of the functions necessary for creating the views, from the high level specification language (i.e., OCL). It facilitates enforcement of a broad, flexible set of policies that can handle the complexity demanded by high volume, high variety, unstructured datasets and general MapReduce computation without any modification to the underlying MapReduce system and operating system. Our evaluation results indicate that GUARDMR provides fine-grained access control for Apache Hadoop system with easy maintainability and very low overhead

A Methodological Framework for SysML: a Problem Frames-based Approach

Recently, SysML has been adopted by the object management group as a modelling language for systems engineering. SysML is a UML profile that represents a subset of UML 2 with extensions. A wide adoption of the language could be hindered by the lack of a methodology that drives the modelling activities. Problem frames (PFs) are a rigorous approach to requirements modelling that has the potential to improve the software development process. Unfortunately, PFs are not supported by an intuitive notation and easy to use tools. As a consequence, their adoption in industry is limited. This paper explores the possibility of exploiting the PFs ideas in the context of SysML models. The goal is to provide model-based development processes using SysML with a set of concepts and guidelines that are sound and have already been used and validated.

Towards a Modeling and Analysis Framework for Privacy-Aware Systems

Nowadays, almost any software application deals with private information. However, effective tools that support the specification and implementation of privacy-aware systems are still missing. This work makes a step to address this issue. In this paper we present MAPaS, a model based framework for the modeling and analysis of privacy-aware systems. MAPaS provides a modeling language for the privacy domain and a rich set of functionalities that allow users to easily analyze privacy-preserving characteristics of a system at the early stages of its development. In this paper, besides presenting the main modules of MaPaS, we show how it can effectively help in the development of privacy-aware systems.

A model driven approach for AMF configuration generation

High availability of services is an important requirement for mission critical systems. The Service Availability Forum defines standards like the Availability Management Framework (AMF) to support the realization of high available systems. AMF is a middleware service that coordinates redundant application components to ensure the high availability of the provided services. In order to provide and protect services, AMF requires a configuration that captures the organization of logical entities and their relations. It describes the service providers, the provided services, their types, and the deployment infrastructure. The process of generating an AMF configuration requires the description of the software characteristics as well as the configuration requirements that specify the services to be provided. Due to the large number of parameters to be taken into account, the generation of an AMF configuration can be a difficult and error prone task. This paper proposes a new approach for the automatic generation of AMF configurations. The proposed solution is model driven and is based on UML profiles which capture the concepts related to configuration requirements, software description, and AMF configurations. AMF configurations are generated using ATL based transformations defined between these different profiles.

A UML-Based Domain Specific Modeling Language for the Availability Management Framework

The Service Availability Forum (SA Forum) is a consortium of several telecommunications and computing companies that defines standard solutions for high availability platforms. One of the most important SA Forum services is the Availability Management Framework (AMF) which is responsible for managing the availability of an application running under its control. To achieve this, AMF requires a complete configuration, which consists of several entities organized according to AMF rules and constraints. In this paper, we argue that AMF concepts form a domain for which a domain-specific modeling language can greatly facilitate the generation, analysis and the management of AMF configurations. We define such a language by extending UML through its profiling mechanism and we implement it. More important, we discuss the challenges and the lessons learned in the course of this project.

Dealing with anonymity in wireless sensor networks

Nowadays Wireless Sensor Networks (WSN) are used in many application contexts. Data handled by WSN are required to be protected for privacy reasons since they can be directly or indirectly related to individuals. The problem of preventing the identification of individuals starting from their data, known as anonymity, is a fundamental requirement for privacy aware systems. This paper proposes a solution to guarantee anonymity for a wide spread type of WSN by means of privacy policies. The solution is based on a UML model that introduces the conceptual elements and guidelines that are needed to build privacy policies for WSN.

Enhancing MongoDB with Purpose-Based Access Control

Privacy has become a key requirement for data management systems. Nevertheless, NoSQL datastores, namely highly scalable non relational database management systems, which often support data management of Internet scale applications,still do not provide support for privacy policies enforcement. With this work, we begin to address this issue, by proposing an approach for the integration of purpose based policy enforcement capabilities into MongoDB, a popular NoSQL datastore. Our contribution consists of the enhancement of the MongoDB role based access control model with privacy concepts and related enforcement monitor. The proposed monitor is easily integrable into any MongoDB deployment through simple configurations. Experimental results show that our monitor enforces purpose-based access control with low overhead.