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Cyber physical systems are becoming ubiquitous devices in many fields thus creating the need for effective security measures. We propose to exploit their intrinsic dependency on the environment in which they are deployed to detect and mitigate anomalies. To do so, sensor measurements, network metrics, and contextual information are fused in a unified security architecture. In this paper, the model of the proposed framework is presented and a first proof of concept involving a telecommunication infrastructure case study is provided.

Before deployment and commissioning of new positioning products/applications, manufacturers need to perform long and often expensive field trials in targeted operational environments in order to assess and certify future behaviour. The community trust on GNSS (Global Navigation Satellite System) is so high that more and more safety critical applications based on satellite navigation are under development. With the increase of criticality level of GNSS applications, a relevant means to predict the performances and reliability of future applications is needed. Thus in this paper we introduce a new architecture based on Machine Learning that combines classical observables for local hazard detection, with the outcome of advanced RAIM in order to determine whether a given point of a railway is suitable for a safe and reliable use of GNSS for train positioning.

This work aims to a better understanding of augmentation network security. In more details, the objective is to simulate a spoofing attack aimed at introducing displacements in the positions computed by rovers that make use of an augmentation service. At first, we investigated the features of such an attack. Then, after introducing the Local Area Augmentation System presented in [1], we evaluated its vulnerabilities. At this aim we generalized the methodology introduced in [1] in order to evaluate the effects on the rovers of faults affecting the Reference Stations employed by the Augmentation Network to the case in which the errors affecting the pseudoranges, measured by different stations, are correlated, as in case of coordinated spoofing. The analytical evaluation is complemented by numerical results obtained by a GNSS simulator, fed with data recorded by a reference station network deployed in the Sardinia Island (Italy), in order to assess the feasibility of a train control system integrating GNSS technologies.

Deep learning models are now used in multiple contexts, including safety critical applications. However, it has been proven that small adversarial alterations to the input can undermine the performances of the model, leading to unreliable results, while being hardly visible to a human observer. Image watermarking share similarities with this field: a small information is embedded inside the media, aiming at being not perceivable but robust. Many attacks have been developed to remove watermarks. In this paper, we evaluate the effectiveness of multiple image transformations to remove adversarial perturbations from images. Our experiments on the MNIST dataset for a Projected Gradient Descent-based adversary demonstrate that many transformations can result in a significant gain in accuracy when classifying adversarial examples, while not degrading the quality of the images when the adversary is not present/non significant.

Industrial and Automation Control systems traditionally achieved security thanks to the use of proprietary protocols and isolation from the telecommunication networks. Nowadays, the advent of the Industrial Internet of Things poses new security challenges. In this paper, we first highlight the main security challenges that advocate for new risk assessment and security strategies. To this end, we propose a security framework and advanced tools to properly manage vulnerabilities, and to timely react to the threats. The proposed architecture fills the gap between computer science and control theoretic approaches. The physical layers connected to Industrial Control Systems are prone to disrupt when facing cyber-attacks. Considering the modules of the proposed architecture, we focus on the development of a practical framework to compare information about physical faults and cyber-attacks. This strategy is implemented in the ATENA architecture that has been designed as an innovative solution for the protection of critical assets.

International audience; Mission critical services are beginning to migrate to broadband from the trusted-but-limited existing systems. They need assured availability and confidentiality for communication in areas affected by a disaster, flash crowding or any catastrophic network failure. This paper describes a vision for an automotive virtual edge Communication scheme that helps healing stricken networks, utilizing any available resources for hosting network functions on vehicles. Emergency and essential service organizations who rush to the area would `bring their own network', i.e. computing capacity and connectivity tools, aboard their service vehicles. These vehicles form a dynamic community that shares resources, information and services, using the combined processing capacity via virtualized core functions. To realize such a scheme, innovative features are required, such as cooperative hosting, opportunistic vehicular resource virtualization, context-based edge SDN traffic prioritization, and ad-hoc vehicular community management, including multi-entity authentication

International audience; Nowadays, Internet of Things (IoT) coupled with cloud computing begins to take an important place in economic systems and in society daily life. It has got a large success in several application areas, ranging from smart city applications to smart grids. Despite the apparent success, one major challenge that should be addressed is the huge amount of data generated by the sensing devices. The transmission of these huge amount of data to the network may affect the energy consumption of sensing devices, and can also cause network congestion issues. To face this challenge, we present a Bayesian Inference Approach (BIA), which allows avoiding the transmission of high spatio-temporal correlated data. In this paper, BIA is based on a hierarchical architecture with smart nodes, smart gateways and data centers. Belief Propagation algorithm has been chosen for performing an approximate inference on our model in order to reconstruct the missing sensing data. BIA is evaluated based on the data collected from the M3 sensors deployed in the FIT IoT-LAB platform and according to different scenarios. The results show that our proposed approach reduces drastically the number of transmitted data and the energy consumption, while maintaining an acceptable level of data prediction accuracy.

International audience; To meet the food demand of the future, farmers are turning to the Internet of Things (IoT) for advanced analytics. In this case, data generated by sensor nodes and collected by farmers on the field provide a wealth of information about soil, seeds, crops, plant diseases, etc. Therefore, the use of high tech farming techniques and IoT technology offer insights on how to optimize and increase yield. However, one major challenge that should be addressed is the huge amount of data generated by the sensing devices, which make the control of sending useless data very important.To face this challenge, we present a Bayesian Inference Approach (BIA), which allows avoiding the transmission of high spatio-temporal correlateddata. In this paper, BIA is based on the PEACH project, which aims to predict frost events in peach orchards by means of dense monitoringusing low-power wireless mesh networking technology. Belief Propagation algorithm has been chosen for performing an approximate inferenceon our model in order to reconstruct the missing sensing data. According to different scenarios, BIA is evaluated based on the data collected from real sensors deployed on the peach orchard. The results show that our proposed approach reduces drastically the number of transmitted data and the energy consumption, while maintaining an acceptable level of data prediction accuracy.

International audience; Nowadays, Internet of Things (IoT) coupled with cloud computing begins to take an important place in economic systems and in society daily life. It has got a large success in several application areas, ranging from smart city applications to smart grids. One major challenge that should be addressed is the huge amount of data generated by the sensing devices, which make the control of sending useless data very important.To face this challenge, we present a Bayesian Inference Approach (BIA), which allows avoiding the transmission of high spatio-temporal correlated data. In this paper, BIA is based on a hierarchical architecture with simple nodes, smart gateways and data centers. Belief Propagation algorithm has been chosen for performing an approximate inference on our model in order to reconstruct the missing sensing data. BIA is evaluated based on the data collected from real sensors and according to different scenarios. The results show that our proposed approach reduces drastically the number of transmitted data and the energy consumption, while maintaining an acceptable level of data prediction accuracy.

The need for effective and reliable surveillance techniques is getting nowadays more and more of primary importance, especially in the actual scenario in which safety and security have become a priority. While classical techniques rely on video-based surveillance systems, such as Close-Circuit television, many studies show that also the audio signal can be effectively used for these purposes. There are many characteristics that make the audio signal particularly suited for this task and, above all, the fact that the analysis of the audio signal can greatly improve thanks to the introduction of automatic classification. Recently, a large focus has been on the use of Deep Neural Networks for classifying audio data and, in this work, we aim to test their performance in the audio surveillance field. In this contribution we propose an algorithm for audio events detection in noisy environments based on the use of deep recurrent neural network. The achieved results show satisfactory and improved performances with respect to state-of-the-art techniques.

Face processing techniques for automatic recognition in broadcast video attract the research interest because of its value in applications, such as video indexing, retrieval, and summarization. In multimedia press review, the automatic annotation of broadcasting news programs is a challenging task because people can appear with large appearance variations such as hair styles, illumination conditions and poses that make the comparison between similar faces more difficult. In this paper a technique for automatic face identification in TV broadcasting programs based on a gallery of faces downloaded from Web is proposed. The approach is based on a joint use of Scale Invariant Feature Transform descriptor and Eigenfaces-based algorithms and it has been tested on video sequences using a database of images acquired starting from a web search. Experimental results show that the joint use of these two approaches improves the recognition rate in case of use Standard Definition (SD) and High Definition (HD) standards.

In this contribution the design of a bi-technological enhanced terminal for secure mobile communication is presented. It is based on the TETRA and TETRAPOL communication networks, that are currently used by public and private bodies as network infrastructures and are particularly exploited in case of emergency. The proposed system allows the use of both, TETRA and TETRAPOL, low level communications layers. Furthermore, the proposed terminal introduces high level capabilities that enhance the basic functionalities of these communication systems, while preserving the intrinsics security of the standards. The implementation of the proposed terminal architecture is the basis for the development of an integrated European network where emergency services and first responders share communications, processes, and a legal framework, to be used in case of natural disasters and security threats. In this contribution, the terminal architecture and the security analysis are introduced and discussed.

This paper presents a novel method to blindly estimate the quality of a multimedia communication link by means of an unconventional use of digital fragile watermarking. Data hiding by digital watermarking is usually employed for multimedia copyright protection, authenticity verification, or similar purposes. However, watermarking is here adopted as a technique to provide a blind measure of the quality of service in multimedia communications. Specifically, a fragile watermark is hidden in an MPEG-like host data video transport stream using a spread-spectrum approach. Like a tracing signal, the watermark tracks the data, where it is embedded, since both the watermark and the host data follow the same communication link. The estimation of the tracing watermark allows dynamically evaluating the effective quality of the provided video services. This depends on the whole physical layer, including the employed video co/decoder. The performed method is based on the evaluation of the mean-square-error between the estimated and the actual watermarks. The proposed technique has been designed for application to wireless multimedia communication systems. According to the results obtained, the sensitivity of the detected tracing watermark on the quality of service (QoS) indices provides for some useful capabilities for analyzing future mobile Universal Mobile Telecommunications System (UMTS) services.

Internet of Things (IoT) refers to the capability to connect, communicate and remotely manage a large number of networked, automated devices via the Internet. IoT is becoming as part of daily life and aims to extend pervasive communication and networking anytime, anywhere with any device. In this context security requirements and architectures must be properly formulated, implemented in order to enforce the security policies during their life-cycle. This paper provides a survey and analysis of security in the area of IoT introducing an approach addressed to overcome the conventional security solutions and deploy a federated architecture for dynamic prevention, detection, diagnosis, isolation, and countermeasures against cyber attacks. Based on the analysis of the most common web services, the paper defines the security needs proposing a federated model to design an architecture for secure exchange of services in IoT paradigm.

In this paper, we focus on Smart Cities, particularly revolution at the edges of the fabric, examining the objectives for developing a Smart City and the direct link between the business/requirements model and its delivery through services, applications, sensors and edge networks. We will provide an overview of how cities are developed and a view of how a Smart City is characterised. Whilst intelligent fabrics create the potential for a Smart City, it is the market that determines how the technology is exploited. We will consider what that market looks like and, in particular, who the stakeholders are, from both market research and academic perspectives. Our assessment of the Smart City's enabling fabrics will cover early applications and the current evolution of implementation in the UK and Italy.

Nowadays, the increase of interdependencies among different Critical Infrastructures (CI) makes it more and more difficult to protect without using a systemic approach that considers a single infrastructure as part of a complex system of infrastructures. A strong collaboration among CI owners is required to avoid, or at least to limit the propagation of failures from one infrastructure to another and to put CI in safety mode. The key element enabling this required cooperation is the possibility for them to exchange relevant information related to the status of their infrastructures and to the services provided. In this paper, we present a middleware solution that allows CIs sharing real-time information, enabling the design and implementation of fault mitigation strategies and mechanisms to prevent the cascading phenomena generated by the failure propagation from one infrastructure to another.

In this paper the reliability of a real-time service for multicast transmission over lossy Mobile Ad-hoc NETwork (MANET) is addressed. The proposed system combines application layer channel coding based on Luby Transform (LT) code with multicast delivery in a wireless network exploiting PUMA (Protocol for Unified Multicasting through Announcements). The main goal is to achieve a real-time service with an high quality level in a lossy environment. The rateless property, the ability of adapt the code on the fly, makes fountain codes an attractive solution for data broadcast/multicast applications in a MANET scenario characterized by dynamic channel conditions and packets losses. The proposed novel approach leads to an improvement on arrival times of packets towards destination nodes.1

Recently, significant efforts have being dedicated to the design of algorithms and architectures able to protect biometric characteristics, in order to guarantee the necessary security and privacy to their owners. In this paper we discuss a protected on-line signature-based biometric authentication system, where the considered biometrics are secured by means of non-invertible transformations, able to generate templates from which retrieving the original information is computationally as hard as random guessing it. The advantages of using a protection method based on non-invertible transforms are exploited by presenting three different matching strategies in the transformed domain, and by proposing a multi-biometrics approach based on score-level fusion to improve the performances of the considered system. The reported experimental results, evaluated on the public MCYT signature database, show that the achievable recognition rates are only slightly affected by the proposed protection scheme, which is able to provide security and renewability for the considered biometrics.

In this paper we discuss the feasibility of employing keystroke dynamics to perform user verification on mobile phones. Specifically, after having introduced a new statistical classifier, we analyze the discriminative capabilities of the features extracted from the acquired patterns, in order to determine which ones guarantee the best authentication performances. The effectiveness of using template selection techniques for keystroke verification is also investigated. The obtained experimental results indicate that the proposed method can be effectively employed to authenticate mobile phones users, even in operational contexts where the number of enrollment acquisition is kept low.

The use of digital media for improving the effectiveness of teaching methodologies in Universities is increasing. In this contribution the experience performed at University of Roma TRE is presented. Since 2005 an online contest is used in the Multimedia class for improving both knowledge and human interaction. This paper shows the competitive-collaborative learning scheme adopted and it reports the feedback received by the students that has been collected by means of a questionnaire. The obtained comments show the effectiveness of the proposed learning scheme.

The increasing use of digital image-based applications is resulting in huge databases that are often difficult to use and prone to misuse and privacy concerns. These issues are especially crucial in medical applications. The most commonly adopted solution is the encryption of both the image and the patient data in separate files that are then linked. This practice results to be inefficient since, in order to retrieve patient data or analysis details, it is necessary to decrypt both files. In this contribution, an alternative solution for secure medical image annotation is presented. The proposed framework is based on the joint use of a key-dependent wavelet transform, the Integer Fibonacci-Haar transform, of a secure cryptographic scheme, and of a reversible watermarking scheme. The system allows: i) the insertion of the patient data into the encrypted image without requiring the knowledge of the original image, ii) the encryption of annotated images without causing loss in the embedded information, and iii) due to the complete reversibility of the process, it allows recovering the original image after the mark removal. Experimental results show the effectiveness of the proposed scheme.

"Low-cost personal computers, wireless access technologies, the Internet, and computer-equipped classrooms allow the design of novel and complementary methodologies for teaching digital information security in electrical engineering curricula. The challenges of the current digital information era require experts who are effectively able to counteract piracy, forgery, copyright infringement, and so on. Digital watermarking is one possible technique for fighting piracy, which consists of the insertion of invisible but robust information to protect the data. In this paper, a new teaching approach, designed for testing student skills and progressing in multimedia data protection, is presented. This consists of a distributed security game where students compete by first using the developed watermarking techniques and then attacking each other's methods, thus verifying their robustness. Groups of students from different universities and countries play against each other, trying to compromise other teams' hiding systems while protecting their own data from attacks. The proposed methodology can be considered as an appealing approach for stimulating learning, cooperation, and team competition. The effectiveness of the teaching method is verified by a student survey and their academic results."

In this demonstration we present the MICIE platform for on-line risk assessment in scenarios with heterogeneous interdependent Critical Infrastructures (CIs) such as power distribution networks, power plants, refineries, water distribution networks, transportation systems and telecommunication networks. These CIs are highly exposed to a large number of threats, including natural hazards, component failures and intentional attacks. Moreover, the increasing interdependence between CIs amplifies the effects of such threats and adds novel challenges to risk assessment tools. In this context, MICIE is the first systematic approach to integrate CI interdependence factors in on-line risk assessment, addressing both the development of on-line risk assessment models and the development of an information sharing platform for continuous exchange of relevant risk information between interdependent CIs.

The wide diffusion of biometric based authentication systems, which has been witnessed in the last few years, has raised the need to protect both the security and the privacy of the employed biometric templates. In fact, unlike passwords or tokens, biometric traits cannot be revoked or reissued and, if compromised, they can disclose unique information about the user’s identity. Moreover, since biometrics represent personal information, they can be used to acquire data which can be used to discriminate people because of religion, health, sex, gender, personal attitudes, and so forth. In this chapter, the privacy requirements, the major threats to privacy, and the best practices to employ in order to deploy privacy sympathetic systems, are discussed within the biometric framework. An overview of state of the art on privacy enhancing technologies, applied to biometric based authentication systems, is presented.

In this paper, we propose a protected on-line signature based biometric authentication system. The original signature templates are protected by transforming them in a non-invertible way. Recovering the original biometrics from the stored data is thus computationally as hard as random guessing. The transformed templates are compared employing a Dynamic Time Warping (DTW) matching strategy. The reported experimental results, evaluated on the public MCYT signature database, show that the recognition rates are only slightly affected by the proposed protection scheme, which is able to guarantee the desired security for the employed biometrics. © 2009 IEEE.

This chapter contains sections titled: Introduction Signature-Based User-Adaptive Fuzzy Commitment Security-Scalable Signature-Based Authentication System Using Data Hiding Summary References ]]>

In this paper an overview of the challenges to long term preservation of digital objects is given. We highlight threats, which can be posed by humans, hardware/software, environment and institutions to long term digital preservation systems, with specific emphasis to security threats. Some technological solutions are described, and the Italian experience on long term digital preservation is briefly described. © 2009 IEEE.

The representation of a biometric trait through a set of parametric features is commonly employed in many biometric authentication systems. In order to avoid any loss of useful information, large sets of features have been defined for biometric characteristics such as signature, gait or face. However, the proposed sets often contain features which are irrelevant, correlated with other features, or even unreliable. In this paper we propose two different approaches for the selection of those features which guarantee the best recognition performances. Moreover, we also face the problem of the binary representation of the selected features. Specifically, an algorithm which selects the minimum number of bits which should be assigned to a given feature, in order to not affect the recognition performances, is here proposed. The effectiveness of the proposed approaches is tested considering a watermarking based on-line signature authentication system, and employing the public MCYT online signature corpus as experimental database. © Springer-Verlag Berlin Heidelberg 2009.

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. E. Maiorana, P. Campisi, M. Martínez-Díaz, J. Ortega-García, A. Neri, "Template protection for HMM-based on-line signature authentication" in IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops CVPRW, Anchorage, AK (USA), 2008, pp. 1-6., The security of biometric data is a very important issue in the deployment of biometric-based recognition systems. In this paper, we propose a signature-based biometric authentication system, where signal processing techniques are applied to the acquired on-line signature in order to generate protected templates, from which retrieving the original data is computationally as hard as randomly guessing them. A hidden Markov model (HMM)-based matching strategy is employed to compare the transformed signatures. The proposed protected authentication system generates a score as the result of the matching process, thus allowing to implement protected multibiometric recognition systems, through the application of score-fusion techniques. The experimental results show that, at the cost of only a slight performance reduction, the desired protection for the employed biometric templates can be properly achieved.

In this paper an adaptive feature-based approach to on-line signature verification is presented. Cryptographic techniques are employed to protect the extracted templates thus making impossible to derive the original biometric data from the stored information, as well as to generate multiple templates from the same original biometrics. Our approach allows to obtain, together with protection, also template cancelability thus guaranteeing user's privacy. The proposed authentication scheme is able to automatically adjust its parameters to the variability of each user's signature, thus obtaining a user adaptive system with enhanced performances with respect to a nonadaptive one. Experimental results show the effectiveness of our approach. Also the effects on the recognition performances when using the pen inclination features are investigated.

Along with the wide diffusion of biometric-based authentication systems, the need to provide security and privacy to the employed biometric templates has become an issue of paramount importance in the design of user-friendly applications. Unlike password or tokens, if a biometrics is compromised, usually it cannot be revoked or reissued. In this paper we propose an on-line signature-based biometric authentication system, where non invertible transformations are applied to the acquired signature functions, making impossible to derive the original biometrics from the stored templates, while maintaining the same recognition performances of an unprotected system Specifically, the possibility of generating cancelable templates from the same original data, thus providing a proper solution to privacy concerns and security issues, is deeply investigated. © 2008 IEEE.

Security and privacy issues are considered as two of the major concerns related to the use of biometric data for authentication purposes. In this paper we propose two different approaches for the protection of on-line signature biometric templates. In the first one, cryptographic techniques are employed to protect signature features, making impossible to derive the original biometrics from the stored templates. In the second one, data hiding techniques are used to design a security scalable authentication system, embedding some dynamic signature features into a static representation of the signature itself. Extensive experimental results are provided to show the effectiveness of the presented protection methods. © 2008 Springer Berlin Heidelberg.

Biometrics is rapidly becoming the principal technology for automatic people authentication. The main advantage in using biometrics over traditional recognition approaches relies in the diffi- culty of losing, stealing, or copying individual behavioral or physical traits. The major weakness of biometrics-based systems relies in their security: in order to avoid data stealing or corruption, storing raw biometric data is not advised. The same problem occurs when biometric templates are employed, since they can be used to re- cover the original biometric data. We employ cryptographic tech- niques to protect dynamic signature features, making it impossible to derive the original biometrics from the stored templates, while maintaining good recognition performances. Together with protec- tion, we also guarantee template cancellability and renewability. Moreover, the proposed authentication scheme is tailored to the sig- nature variability of each user, thus obtaining a user adaptive sys- tem with enhanced performances with respect to a nonadaptive one. Experimental results show the effectiveness of our approach when compared to both traditional nonsecure classifiers and other, already proposed protection schemes. © 2008 SPIE and IS&T.

This paper presents a novel spatial data hiding scheme based on the Least Significant Bit insertion. The bitplane decomposition is obtained by using the (p, r) Fibonacci sequences. This decomposition depends on two parameters, p and r. Those values increase the security of the whole system; without their knowledge it is not possible to perform the same decomposition used in the embedding process and to extract the embedded information. Experimental results show the effectiveness of the proposed method.

In this paper a joint watermarking and ciphering scheme for digital images is presented. Both operations are performed on a key-dependent transform domain. The commutative property of the proposed method allows to cipher a watermarked image without interfering with the embedded signal or to watermark an encrypted image still allowing a perfect deciphering. Furthermore, the key dependence of the transform domain increases the security of the overall system. Experimental results show the effectiveness of the proposed scheme.

In this paper we propose a signature-based biometric authentication system, where watermarking techniques are used to embed some dynamic signature features in a static representation of the signature itself. User authentication can be performed either by means of the only signature static image, or by using it together with the dynamic features embedded in the enrollment stage, by using a fusion approach. A multilevel authentication system, which is capable to provide two different levels of security, is then obtained. The proposed watermarking techniques are based on the properties of the Radon transform which well fits to the signature images. A robust embedding is obtained while keeping unaltered the original structure of the host signal. ©2007 IEEE.

In this paper we propose an Orthogonal Frequency Division Multiplexing Ultra Wide Band (OFDM-UWB) system that introduces encryption, mutual authentication, and data integrity functions, at the physical layer, without impairing spectral efficiency. Encryption is performed by rotating the constellation employed in each band by means of a pseudorandom phase-hopping sequence. Authentication and data integrity, based on encrypted-hash, are directly coupled with Forward Error Correction (FEC). Dependence of the phase hopping sequence on the transmitted message deny the use of the phase hopping obtained by means of known and chosen plaintext attacks for decryption of further messages. Moreover, since phase hopping generation keys change very rapidly they are also difficultly detectable from a hypothetic man in the middle . Computer simulations confirm the superior performance, even in terms of BER, to a standard PSKOFDM system, due to the FEC capabilities of encrypted hash.

In this paper the use of Internet Protocol ver.6 packets to convey hidden information is exploited. The possibility to hide information in commonly used data transport mechanisms allows one to send extra information in a transparent way. The hidden message does not affect the routing mechanism neither interferes with the security mechanisms implemented on IP based networks, as firewalls, intrusion detection systems, authentication tools.

In the last decade a lot of efforts have been devoted to the development of biometrics-based authentication systems. In this paper we propose a signature-based biometric authentication system, where watermarking techniques are used to embed some dynamic signature features in a static representation of the signature itself, stored either in a centralized database or in a smartcard. The user authentication can be performed either by using some static features extracted from the acquired signature or by using both the aforementioned static features together with the dynamic features embedded in the enrollment stage. A multi-level authentication system, which is capable to provide various degree of security, is thus obtained. The proposed watermarking techniques are tailored to images with sharp edges, like a signature picture, in order to obtain a robust embedding method while keeping intact the original structure of the host signal. Experimental results show the two different levels of security which can be reached when either static features or both static and dynamic features are employed in the authentication process.

This paper proposes a business model founded on Bayes decision test for video-call billing. This model is based on the end-to-end Quality of Service (QoS) obtained exploiting the tracing watermarking procedure recently introduced in literature. In particular, we employ the watermark embedded in each transmitted video-sequence to monitor the QoS of the communication link and then to adequately fare the user depending on the real received video-quality. We need to know only the MSE of the received watermark to estimate the end-to-end QoS of the communication link. Numerical results are conducted to characterize the effectiveness of the proposed method, using two different business scenarios, and confirm the validity of such approach. Therefore, the network operator is able to implement an adaptive billing strategy, depending on the effective received quality and maximizing the profit.

This work presents a collaborative network-aware processing of multimedia content for dynamic quality of service (QoS) management using tracing watermarking. Tracing watemarking has been recently proposed as a technique to provide a blind measure of the QoS of the communication link, focusing on multimedia communication scenarios. In this work, we use the transmitted video-sequences to monitor the QoS in a videoconference call. The video-sequence of every active user travels on the communication link, one time as video (transparent mode), one lime as watermark (hidden mode) describing a boomerang trajectory. The results obtained through our simulation trials confirm the validity of such approach. In fact, the advantages of distributing the management process are (i) an easier and more precise localization of the cause of QoS problems, (ii) a better knowledge of local situations, (iii) a lower complexity for a single QoS agent and (iv) an increase in possible actions.

Biometrics is the most emerging technology for automatic people authentication, nevertheless severe concerns raised about security of such systems and users' privacy. In case of malicious attacks toward one or more components of the authentication system, stolen biometric features cannot be replaced. This paper focuses on securing the enrollment database and the communication channel between such database and the matcher. In particular, a method is developed to protect the stored biometric templates, adapting the fuzzy commitment scheme to iris biometrics by exploiting error correction codes tailored on template discriminability. The aforementioned method allows template renewability applied to iris based authentication and guarantees high security performing the match in the encrypted domain.

In this paper, a novel authentications system combining biometric cryptosystems with digital watermarking is presented. One of the main vulnerabilities of the existing data hiding systems is the public knowledge of the embedding domain. We propose the use of biometric data, minutiae fingerprint set, for generating the encryption key needed to decompose an image in the Tree structured Haar transform. The uniqueness of the biometrics key together with other, embedded, biometric information guarantee the authentication of the user. Experimental tests show the effectiveness of the proposed system.

In the last decade, there has been an explosive growth in mobile computing technology and obviously an increase demand for platforms with multimedia application support. The desire to be connected “any-time, any-where and any-way” has led to an increasing array of heterogeneous systems, multimedia applications, devices, and service providers. In response to this issue, quality of service (QoS) is designed to hide low-level application variation and provide necessary service guarantees. In this contribution, motivation and operating guidelines for QoS assessment in real-time interactive multimedia communications are discussed and investigated. In particular, we consider the end-to-end service quality methodologies proposing a QoS evaluation technique by means of an unconventional use of fragile watermarking. Thus, by knowing the end-to-end QoS, it is possible to adopt optimal pricing strategies in terms of the QoS profiling for all the active users involved in the communication.

Broadband multimedia communications will be a key element in the 3rd generation of wireless services. A primary challenge is the support of interactive services requiring synchronous playout of multimedia content with a maximum acceptable delay in a multi-user scenario. Subjective tests show that the subjects prefer a lower quality reproduction than a “hopping” video: the pause needed to re-buffer severely affects the overall quality. To maximize the number of active users that can be served with a predefined Quality of Service (QoS) level by a packet-oriented radio access, we propose the use of a multimedia proxy. This component may transcode the original video stream to match a predefined quality level based on the quality of each user’s channel.

Many studies have shown that color representation is very relevant in image processing and communications techniques. In this contribution, we propose a new color space, based on the "skin" component, in order to minimize the perceptual distortions introduced by digital watermarking. We have therefore defined a new color space, called YST, in which the brightness component is the same of YUV. Conversely, the S (skin) component has been obtained estimating the average values corresponding to a set of different colors of human faces. The criterion for this selection was to achieve a reasonable degree of generalization. The third component, T, is automatically identified by the Gram-Schmidt procedure in order to have an orthogonal color space. Analytical results are used to show the benefits obtained in digital watermarking by the new representation as well as in terms of peak signal-to-noise ratio and video quality metrics.

Protein secondary structures are regular structural elements which are formed by hydrogen bonds between relatively small segments of the protein sequence. In this paper a fast learning neural network approach to protein secondary structure identification is presented. The identification is obtained by using an ad hoc neural network. Experimental results show the effectiveness of the proposed approach.

This paper considers the use of data hiding strategies for improved color image compression. Specifically, color information is piggybacked on the luminance component of the image in order to reduce the overall signal storage requirements. A practical wavelet-based data hiding scheme is proposed in which selected perceptually irrelevant luminance bands are replaced with perceptually salient chrominance components. Simulation results demonstrate the improvement in compression quality of the proposed scheme to SPIHT and JPEG at low bit rates. The novel technique also has the advantage that it can be used to further reduce the storage requirements of algorithms such as SPIHT which is optimized for grayscale image compression.

Traditionally, data hiding and compression have had contradictory goals. The former problem adds perceptually irrelevant information in order to embed data, while the latter removes this irrelevancy and redundancy to reduce storage requirements. In this paper, we use data hiding to help improve signal compression. We take an unconventional approach and consider "piggy-backing" the color information on the luminance component of an image for improved color image coding. Our new technique essentially transforms a given color image into the YIQ color space where the chrominance information is subsampled and embedded in the wavelet domain of the luminance component. Our technique can be used as preprocessing to improve the performance of popular image compression schemes such as SPIHT that are optimized for grayscale image compression. Simulation results demonstrate the superior performance of the proposed technique in comparison to JPEG and straightforward SPIHT.