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Ca' Foscari University of Venice, Italy

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13 Papers

A Fast and Cost-effective Design for FPGA-based Fuzzy Rainbow Tradeoffs

Topics: Security Frameworks, Architectures and Protocols; Cryptographic Algorithms; Vulnerability Analysis and Countermeasures; Security Architecture and Design Analysis

Authors: Leonardo Veronese ^{1

;

2} , Francesco Palmarini ^{1

;

2} , Riccardo Focardi ^{1

;

2} and Flaminia Luccio ^{1

;

2}

Affiliations: ¹ 10Sec S.r.l., via delle Industrie 13, Venice, Italy , ² DAIS, Ca’ Foscari University, via Torino 155, Venice, Italy

Digital Object Identifier: 10.5220/0010904300003120

Proceedings of ICISSP 2022, ISBN: 978-989-758-553-1

Quick Abstract

Time/memory tradeoffs are general techniques used in cryptanalysis that aim at reducing the computational effort in exchange for a higher memory usage. Among these techniques, one of the most modern algorithms is the fuzzy-rainbow tradeoff, which has notably been used in 2010 to attack the GSM A5/1 cipher. Most of the existing analyses of tradeoff algorithms only take into account the main-memory model, which does not reflect the hierarchical (external) storage model of real world systems. Moreover, to the best of our knowledge, there are no publicly available implementations or designs that show the performance level that can be achieved with modern off-the-shelf hardware. In this paper, we propose a reference hardware and software design for the cryptanalysis of ciphers and one-way functions based on FPGAs, SSDs and the fuzzy rainbow tradeoff algorithm. We evaluate the performance of our design by extending an existing analytical model to account for the actual storage hierarchy, and we estimate an attack time for DES and A5/1 ciphers of less than one second, demonstrating that these ciphers can be cracked in real-time with a budget under 6000e.

Evaluating Security, Privacy and Usability Features of QR Code Readers

Topics: Cryptographic Algorithms; Content Protection and Digital Rights Management; Privacy Enhancing Technologies; Authentication, Privacy and Security Models; Security Awareness and Education

Authors: Heider Wahsheh and Flaminia Luccio

Affiliation: University Ca’ Foscari, Venice and Italy

Digital Object Identifier: 10.5220/0007346202660273

Proceedings of ICISSP 2019, ISBN: 978-989-758-359-9

Quick Abstract

The widespread of smartphones with advanced capabilities has motivated developers to design new mobile applications that are used as barcode scanners. Although several barcode readers are available, they still have security and privacy limitations. In this paper, we first present a comprehensive and systematic review of barcode reader applications by analyzing their security, privacy and usability features. We categorize these apps into four groups depending on their properties: URLs security, Crypto-based security, Popular applications, and Save-privacy. We also highlight their weaknesses and present design recommendations for usable, secure and privacy-guaranteed scanner applications. Based on our recommendations, we have developed BarSec Driod a proof-of-concept secure barcode reader Android app that exploits some features of other applications and at the same time overcomes their limitations. We have performed a user usability and security survey, on BarSec Driod and two other popular QR code readers, KasperSky and QR Droid Private. The results show that BarSec Driod is easy to use, satisfies the expectations of the users and is secure. Moreover, we have observed that following the design tips, user’s security awareness and usability increase.

Related Ontology Subjects/Areas/Topics (2)

Information and Systems Security

Privacy Enhancing Technologies

Stochastic Phase Estimation and Unwrapping

Topics: Signal Processing; Industry Related Applications; Image and Video Analysis and Understanding

Authors: Mara Pistellato , Filippo Bergamasco , Andrea Albarelli , Luca Cosmo , Andrea Gasparetto and Andrea Torsello

Affiliation: DAIS, Ca’Foscari University of Venice, Via Torino 155, Venice and Italy

Digital Object Identifier: 10.5220/0007389402000209

Proceedings of ICPRAM 2019, ISBN: 978-989-758-351-3

Quick Abstract

Phase-shift is one of the most effective techniques in 3D structured-light scanning for its accuracy and noise resilience. However, the periodic nature of the signal causes a spatial ambiguity when the fringe periods are shorter than the projector resolution. To solve this, many techniques exploit multiple combined signals to unwrap the phases and thus recovering a unique consistent code. In this paper, we study the phase estimation and unwrapping problem in a stochastic context. Assuming the acquired fringe signal to be affected by additive white Gaussian noise, we start by modelling each estimated phase as a zero-mean Wrapped Normal distribution with variance σ̄2. Then, our contributions are twofolds. First, we show how to recover the best projector code given multiple phase observations by means of a ML estimation over the combined fringe distributions. Second, we exploit the Cramér-Rao bounds to relate the phase variance σ̄2 to the variance of the observed signal, that can be easily estimated online during the fringe acquisition. An extensive set of experiments demonstrate that our approach outperforms other methods in terms of code recovery accuracy and ratio of faulty unwrappings.

Related Ontology Subjects/Areas/Topics (7)

Applications	Health Engineering and Technology Applications	Signal Processing
Cardiovascular Imaging and Cardiography	Pattern Recognition	Software Engineering
Cardiovascular Technologies

A Non-parametric Spectral Model for Graph Classification

Topics: Graphical and Graph-Based Models; Spectral Methods

Authors: Andrea Gasparetto , Giorgia Minello and Andrea Torsello

Affiliation: Università Ca' Foscari Venezia, Italy

Digital Object Identifier: 10.5220/0005220303120319

Proceedings of ICPRAM 2015, ISBN: 978-989-758-076-5

Quick Abstract

Graph-based representations have been used with considerable success in computer vision in the abstraction and recognition of object shape and scene structure. Despite this, the methodology available for learning structural representations from sets of training examples is relatively limited. In this paper we take a simple yet effective spectral approach to graph learning. In particular, we define a novel model of structural representation based on the spectral decomposition of graph Laplacian of a set of graphs, but which make away with the need of one-to-one node-correspondences at the base of several previous approaches, and handles directly a set of other invariants of the representation which are often neglected. An experimental evaluation shows that the approach significantly improves over the state of the art.

Related Ontology Subjects/Areas/Topics (4)

Graphical and Graph-Based Models		Spectral Methods		Theory and Methods
Pattern Recognition

Objective and Subjective Metrics for 3D Display Perception Evaluation

Topics: Perception; Virtual Environments

Authors: Andrea Albarelli , Luca Cosmo , Filippo Bergamasco and Andrea Gasparetto

Affiliation: Università Ca' Foscari, Italy

Digital Object Identifier: 10.5220/0005280603090317

Proceedings of ICPRAM 2015, ISBN: 978-989-758-077-2

Quick Abstract

Many modern professional 3D display systems adopt stereo vision and viewer-dependent rendering in order to offer an immersive experience and to enable complex interaction models. Within these scenarios, the ability of the user to effectively perform a task depends both on the correct rendering of the scene and on his ability to perceive it. These factors, in turn, are affected by several error sources, such as accuracy of the user position estimation or lags between tracking and rendering. With this paper, we introduce a practical and sound method to quantitatively assess the accuracy of any view-dependent display approach and the effects of the different error sources. This is obtained by defining a number of metrics that can be used to analyze the results of a set of experiments specially crafted to tickle different aspects of the system. This fills a clear shortcoming of the evaluation methods for 3D displays found in literature, that are, for the most part, qualitative.

Related Ontology Subjects/Areas/Topics (5)

Applications		Perception		Virtual Environments
Pattern Recognition		Software Engineering

Probabilistic Evidence Accumulation for Clustering Ensembles

Topics: Ensemble Methods; Clustering

Authors: André Lourenço ¹ , Samuel Rota Bulò ² , Nicola Rebagliati ² , Ana Fred ³ , Mário Figueiredo ³ and Marcello Pelillo ²

Affiliations: ¹ Instituto Superior de Engenharia de Lisboa and Instituto Superior Técnico, Portugal , ² Università Ca’ Foscari Venezia, Italy , ³ Instituto Superior Técnico, Portugal

Digital Object Identifier: 10.5220/0004267900580067

Proceedings of ICPRAM 2013, ISBN: 978-989-8565-41-9

Quick Abstract

Ensemble clustering methods derive a consensus partition of a set of objects starting from the results of a collection of base clustering algorithms forming the ensemble. Each partition in the ensemble provides a set of pairwise observations of the co-occurrence of objects in a same cluster. The evidence accumulation clustering paradigm uses these co-occurrence statistics to derive a similarity matrix, referred to as co-association matrix, which is fed to a pairwise similarity clustering algorithm to obtain a final consensus clustering. The advantage of this solution is the avoidance of the label correspondence problem, which affects other ensemble clustering schemes. In this paper we derive a principled approach for the extraction of a consensus clustering from the observations encoded in the co-association matrix. We introduce a probabilistic model for the co-association matrix parameterized by the unknown assignments of objects to clusters, which are in turn estimated using a maximum likelihood approach. Additionally, we propose a novel algorithm to carry out the parameter estimation with convergence guarantees towards a local solution. Experiments on both synthetic and real benchmark data show the effectiveness of the proposed approach.

Related Ontology Subjects/Areas/Topics (4)

Clustering		Pattern Recognition		Theory and Methods
Ensemble Methods

Tukra: An Abstract Program Slicing Tool

Topics: Model Analysis and Checking; Model Tools

Authors: Raju Halder and Agostino Cortesi

Affiliation: Università Ca' Foscari Venezia, Italy

Digital Object Identifier: 10.5220/0004069801780183

Proceedings of ICSOFT 2012, ISBN: 978-989-8565-19-8

Quick Abstract

We introduce Tukra, a tool that allows the practical evaluation of abstract program slicing algorithms. The tool exploits the notions of statement relevancy, semantic data dependences and conditional dependences. The combination of these three notions allows Tukra to refine traditional syntax-based program dependence graphs, generating more accurate slices. We provide the architecture of the tool, some snapshots describing how it works, and some preliminary experimental results giving evidence of the accuracy improvements it supports.

Related Ontology Subjects/Areas/Topics (5)

Model Analysis and Checking		Models		Software Engineering
Model Tools		Paradigm Trends

PROPERTY DRIVEN PROGRAM SLICING REFINEMENT

Topics: Algorithms and Data Structures; Software Testing and Maintenance; Programming Languages

Authors: Sukriti Bhattacharya and Agostino Cortesi

Affiliation: Ca’ Foscari University of Venice, Italy

Digital Object Identifier: 10.5220/0003490101490155

Proceedings of ICSOFT 2011, ISBN: 978-989-8425-77-5

Quick Abstract

A slice is usually computed by analyzing how the effects of a computation are propagated through the code, i.e., by inferring dependencies. The aim of this paper is to further refine the traditional slicing technique by combining it with a static analysis in Abstract Interpretation based framework. This results into a deeper insight on the strong relation between slicing and property based dependency.

Related Ontology Subjects/Areas/Topics (5)

Algorithms and Data Structures		Software Engineering		Software Testing and Maintenance
Programming Languages		Software Engineering Methods and Techniques

TYPE-FLOW ANALYSIS FOR LEGACY COBOL CODE

Topics: Reverse Engineering; Programming Languages

Authors: Alvise Spanò , Michele Bugliesi and Agostino Cortesi

Affiliation: Università Ca’ Foscari Venezia, Italy

Digital Object Identifier: 10.5220/0003506700640075

Proceedings of ICSOFT 2011, ISBN: 978-989-8425-77-5

Quick Abstract

Many business applications today still rely on COBOL programs written decades ago that are difficult to maintain and upgrade due to technological limitations and lack of experts in the language. Several companies have been trying to migrate their software base to modern platforms, but code translation is problematic because most business processes implemented are often no longer documented or even known. Applying existing Program Understanding techniques to COBOL could be a way for aiding IT specialists in charge of a porting - but useful raw information must be extracted from the source code in order to get these techniques yield to meaningful results. We believe that the types of variables used in programs are an important part of such raw information and we present an approach based on static analysis of types rather than data. Our system is capable of reconstructing the type-flow of a COBOL program throughout branches, jumps and loops in finite time and to track type information on reused variables occurring in the code. It also detects a number of error-prone situations, type mismatches or misuses and notifies that by means of messages annotated in the code along with types inferred for each variable occurrence.

Related Ontology Subjects/Areas/Topics (6)

Health Engineering and Technology Applications		Neurotechnology, Electronics and Informatics		Reverse Engineering
Neurocomputing		Programming Languages		Software Engineering

DATABASE AUTHENTICATION BY DISTORTION FREE WATERMARKING

Topics: Data Warehouses and Data Mining; Data Exchange and Integration

Authors: Sukriti Bhattacharya and Agostino Cortesi

Affiliation: Universita Ca’ Foscari di Venezia, Italy

Digital Object Identifier: 10.5220/0002929302190226

Proceedings of ICSOFT 2010, ISBN: 978-989-8425-22-5

Quick Abstract

In this paper we introduce a distortion free watermarking technique that strengthen the verification of integrity of the relational databases by using a public zero distortion authentication mechanism based on the Abstract Interpretation framework. The watermarking technique is partition based. The partitioning can be seen as a virtual grouping, which does not change neither the value of the table’s elements nor their physical positions. Instead of inserting the watermark directly to the database partition, we treat it as an abstract representation of that concrete partition, such that any change in the concrete domain reflects in its abstract counterpart. The main idea is to generate a gray scale image of the partition as a watermark of that partition, that serves as tamper detection procedure, followed by employing a public zero distortion authentication mechanism to verify the ownership.

Related Ontology Subjects/Areas/Topics (7)

Business Analytics	Data Exchange and Integration	e-Business
Communication and Software Technologies and Architectures	Data Warehouses and Data Mining	Enterprise Information Systems
Data Engineering