A comparison of hole-filling methods in 3D

This paper presents a review of the most relevant current techniques that deal with hole-filling in 3D models. Contrary to earlier reports, which approach mesh repairing in a sparse and global manner, the objective of this review is twofold. First, a specific and comprehensive review of hole-filling techniques (as a relevant part in the field of mesh repairing) is carried out. We present a brief summary of each technique with attention paid to its algorithmic essence, main contributions and limitations. Second, a solid comparison between 34 methods is established. To do this, we define 19 possible meaningful features and properties that can be found in a generic hole-filling process. Then, we use these features to assess the virtues and deficiencies of the method and to build comparative tables. The purpose of this review is to make a comparative hole-filling state-of-the-art available to researchers, showing pros and cons in a common framework.• Ministerio de Economía y Competitividad: Proyecto DPI2013-43344-R (I+D+i) • Gobierno de Castilla-La Mancha: Proyecto PEII-2014-017-PpeerReviewe

New models for efficient authenticated dictionaries

International audienceWe propose models for data authentication which take into account the behavior of the clients who perform queries. Our models reduce the size of the authenticated proof when the frequency of the query corresponding to a given data is higher. Existing models implicitly assume the frequency distribution of queries to be uniform, but in reality, this distribution generally follows Zipf's law. Our models better reflect reality and the communication cost between clients and the server provider is reduced allowing the server to save bandwidth. The obtained gain on the average proof size compared to existing schemes depends on the parameter of Zipf law. The greater the parameter, the greater the gain. When the frequency distribution follows a perfect Zipf's law, we obtain a gain that can reach 26%. Experiments show the existence of applications for which Zipf parameter is greater than 1, leading to even higher gains

Cryptographic Protocols, Sensor Network Key Management, and RFID Authentication

This thesis includes my research on efficient cryptographic protocols, sensor network key management, and radio frequency identification (RFID) authentication protocols. Key exchange, identification, and public key encryption are among the fundamental protocols studied in cryptography. There are two important requirements for these protocols: efficiency and security. Efficiency is evaluated using the computational overhead to execute a protocol. In modern cryptography, one way to ensure the security of a protocol is by means of provable security. Provable security consists of a security model that specifies the capabilities and the goals of an adversary against the protocol, one or more cryptographic assumptions, and a reduction showing that breaking the protocol within the security model leads to breaking the assumptions. Often, efficiency and provable security are not easy to achieve simultaneously. The design of efficient protocols in a strict security model with a tight reduction is challenging. Security requirements raised by emerging applications bring up new research challenges in cryptography. One such application is pervasive communication and computation systems, including sensor networks and radio frequency identification (RFID) systems. Specifically, sensor network key management and RFID authentication protocols have drawn much attention in recent years. In the cryptographic protocol part, we study identification protocols, key exchange protocols, and ElGamal encryption and its variant. A formal security model for challenge-response identification protocols is proposed, and a simple identification protocol is proposed and proved secure in this model. Two authenticated key exchange (AKE) protocols are proposed and proved secure in the extended Canetti-Krawczyk (eCK) model. The proposed AKE protocols achieve tight security reduction and efficient computation. We also study the security of ElGamal encryption and its variant, Damgard’s ElGamal encryption (DEG). Key management is the cornerstone of the security of sensor networks. A commonly recommended key establishment mechanism is based on key predistribution schemes (KPS). Several KPSs have been proposed in the literature. A KPS installs pre-assigned keys to sensor nodes so that two nodes can communicate securely if they share a key. Multi-path key establishment (MPKE) is one component of KPS which enables two nodes without a shared key to establish a key via multiple node-disjoint paths in the network. In this thesis, methods to compute the k-connectivity property of several representative key predistribution schemes are developed. A security model for MPKE and efficient and secure MPKE schemes are proposed. Scalable, privacy-preserving, and efficient authentication protocols are essential for the success of RFID systems. Two such protocols are proposed in this thesis. One protocol uses finite field polynomial operations to solve the scalability challenge. Its security is based on the hardness of the polynomial reconstruction problem. The other protocol improves a randomized Rabin encryption based RFID authentication protocol. It reduces the hardware cost of an RFID tag by using a residue number system in the computation, and it provides provable security by using secure padding schemes

Applied Formal Methods in Wireless Sensor Networks

This work covers the application of formal methods to the world of wireless sensor networks. Mainly two different perspectives are analyzed through mathematical models which can be distinct for example into qualitative statements like "Is the system error free?" From the perspective of quantitative propositions we investigate protocol optimal parameter settings for an energy efficient operation

DINE : a framework for deep incomplete network embedding

Network representation learning (NRL) plays a vital role in a variety of tasks such as node classification and link prediction. It aims to learn low-dimensional vector representations for nodes based on network structures or node attributes. While embedding techniques on complete networks have been intensively studied, in real-world applications, it is still a challenging task to collect complete networks. To bridge the gap, in this paper, we propose a Deep Incomplete Network Embedding method, namely DINE. Specifically, we first complete the missing part including both nodes and edges in a partially observable network by using the expectation-maximization framework. To improve the embedding performance, we consider both network structures and node attributes to learn node representations. Empirically, we evaluate DINE over three networks on multi-label classification and link prediction tasks. The results demonstrate the superiority of our proposed approach compared against state-of-the-art baselines. © 2019, Springer Nature Switzerland AG.E