Fight against counterfeiting of goods related to IP infringing: Technical report of DG JRC.G.06 on analysis of Due Diligence for fight against counterfeiting of goods related to IP infringing

This report analyses how Due Diligence concepts, which includes Corporate Social Responsibility (CSR) and Supply Chain Management Responsibility (SCMR) can be applied to the fight against counterfeit related to IP infringing. We intentionally decided to limit the study in this report to the market portion of counterfeit products related to IP infringing. Counterfeit products can be a wider set than just IP infringing products.JRC.G.6-Digital Citizen Securit

Privacy and Biometric Passports

This work deals with privacy implications and threats that can emerge with the large-scale use of electronic biometric documents, such the recently introduced electronic passport (e-Passport). A brief introduction to privacy and personal data protection is followed by a presentation of the technical characteristics of the e-Passport. The description includes the digital data structure, and the communication and reading mechanisms of the e-Passport, indicating the possible points and methods of attack

Electronic Passports

The article discusses the fetures of the electronic passports. The content of the machine readeable zone, RFID (contactless smartcard) technology, the data groups, and the Czech and German implementations are discussed in more details.JRC.G.6-Sensors, radar technologies and cybersecurit

The Architecture of an Information Tool for De-mining: Mine Identification Core Module (MICM).

Abstract not availableJRC.(ISIS)-Institute For Systems, Informatics And Safet

Use of ePassport for Identity Management in Network-Centric Citizen Life Processes

Digital identity management (IdM) for citizen life processes requires trusted relationship among the service providers and users. Current IdM systems tend to lack the trust component in particular for online transactions. We propose the use of ePassport as a globally interoperable trust token to bridge the gap between offline and online environments. The paper analyses trust attributes of the ePassport and recognizes the extensions required to its deployment in an online IdM for high-value transactions. An architecture is proposed for a network-centric IdM system to support three categories of life processes: eGovernment services, high value private services, and eCommerce. The solution is compatible with privacy enhancing technologies while at the same time creating trusted digital identities and offering users convenience.JRC.G.6-Security technology assessmen

Utilizing CPU, Memory and other features signals to control processes and related data in computing devices with potential to identify user. An Application Risk Assessment Approach

In the Internet era users' fundamental privacy and anonymity rights have received significant research and regulatory attention. This is not only a result of the exponential growth of data that users generate when accomplishing their daily task by means of computing devices with advanced capabilities, but also because of inherent data properties that allow them to be linked with a real or soft identity. Service providers exploit these facts for user monitoring and identification, albeit impacting users' anonymity, based mainly on personal identifiable information or on sensors that generate unique data to provide personalized services. In this paper, we report on the feasibility of user identification using instead general system features like memory, CPU and network data, as provided by the underlying operating system. We provide a general framework based on supervised machine learning algorithms both for distinguishing users, and informing them about their anonymity exposure. We conduct a series of experiments to collect trial datasets for users' engagement on a shared computing platform. We evaluate various well-known classifiers in terms of their effectiveness in distinguishing users, and we perform a sensitivity analysis of their configuration setup to discover optimal settings under diverse conditions. Furthermore, we examine the bounds of sampling data to eliminate the chances of user identification and thus promote anonymity. Overall results show that under certain configurations users' anonymity can be preserved, while in other cases users' identification can be inferred with high accuracy, without relying on personal identifiable information.JRC.G.6-Digital Citizen Securit

On the Efficiency of User Identification: A System based Approach

In the Internet era users’ fundamental privacy and anonymity rights have received significant research and regulatory attention. This is not only a result of the exponential growth of data that users generate when accomplishing their daily task by means of computing devices with advanced capabilities, but also because of inherent data properties that allow them to be linked with a real or soft identity. Service providers exploit these facts for user monitoring and identification, albeit impacting users’ anonymity, based mainly on personal identifiable information or on sensors that generate unique data to provide personalized services. In this paper, we report on the feasibility of user identification using instead general system features like memory, CPU and network data, as provided by the underlying operating system. We provide a general framework based on supervised machine learning algorithms both for distinguishing users, and informing them about their anonymity exposure. We conduct a series of experiments to collect trial datasets for users’ engagement on a shared computing platform. We evaluate various well-known classifiers in terms of their effectiveness in distinguishing users, and we perform a sensitivity analysis of their configuration setup to discover optimal settings under diverse conditions. Furthermore, we examine the bounds of sampling data to eliminate the chances of user identification and thus promote anonymity. Overall results show that under certain configurations users’ anonymity can be preserved, while in other cases users’ identification can be inferred with high accuracy, without relying on personal identifiable information.JRC.E.3-Cyber and Digital Citizens' Securit

On the ontology of Digital Identification

Abstract. Existing technical and legal definitions of identification and closely related privacy concepts show a confused and often circular semantics, in particular when applied to a digital environment. We examine the ontology of digital identification in the wider context of privacy. We begin with a formal definition of the ´identical ´ relation between 2 nyms and from this we derive a quantifiable notion of identification based on linkability and its opposite, anonymity. We base our logical model on a 3 layered semantic model theory. The results of this modeling show the context dependence of identification. Identification has meaning only in relation to a set of individuals known as the anonymity set, and an existing knowledge base of facts about these individuals. 1 Introduction and Survey of Current Models of Identity Digital identities are fast becoming the most important and coveted assets in the information society. For example, the US Federal Trade Commission estimates that complaints about identity theft doubled in 2002. However, a survey of regulatory descriptions of identity reveals a lot of confusion. The US patriot act, 2001 [1], mention

Hydrothermal Carbonization of Dry Anaerobic Digestion Residues Derived from Food and Agro Wastes in Lesvos Island

Biowaste management is at the center of attention in recent years due to the increased focus on Circular Economy practices. Lesvos has numerous food processing facilities and olive mills, and therefore Olive Mill Wastewater (OMWW) is a wastewater stream that requires attention. In this study, a holistic experimental set-up that combines aerobic and anaerobic treatment strategies was developed taking into consideration the hydrothermal carbonization of AD digestate along with locally available OMWW. The study focuses on the hydrothermal carbonization (HTC) of anaerobic residues from biogas production, and food waste was co-utilized with spent coffee grounds (SCG). The reduced volatile solids of SCG have some effects on the final products. AD produced methane yields of 54.7% for the food waste and 52.4%. for the feedstock with added SCG. At the same time, the feedstock that contained SCG produced more hydrochar that reached up to 50% of the yield. Hydrothermal carbonization in a water medium produced liquids with basic pH values around 8 and conductivities of 4–5 mS/cm, while the samples that were treated in OMWW medium had pH values close to 5.5 and conductivities of around 12 mS/cm. The produced hydrochars have significant calorific values that exceeded 20 MJ/kg for almost all the samples. Overall, HTC with OMWW as a medium was able significantly reduce the COD of OMWW while resulting in hydrochars with increased heating values