CONCISE: Compressed 'n' Composable Integer Set

Bit arrays, or bitmaps, are used to significantly speed up set operations in several areas, such as data warehousing, information retrieval, and data mining, to cite a few. However, bitmaps usually use a large storage space, thus requiring compression. Nevertheless, there is a space-time tradeoff among compression schemes. The Word Aligned Hybrid (WAH) bitmap compression trades some space to allow for bitwise operations without first decompressing bitmaps. WAH has been recognized as the most efficient scheme in terms of computation time. In this paper we present CONCISE (Compressed 'n' Composable Integer Set), a new scheme that enjoys significatively better performances than those of WAH. In particular, when compared to WAH, our algorithm is able to reduce the required memory up to 50%, by having similar or better performance in terms of computation time. Further, we show that CONCISE can be efficiently used to manipulate bitmaps representing sets of integral numbers in lieu of well-known data structures such as arrays, lists, hashtables, and self-balancing binary search trees. Extensive experiments over synthetic data show the effectiveness of our approach.Comment: Preprint submitted to Information Processing Letters, 7 page

DEVELOPMENT OF PREDICTIVE MODELS FOR QUALITY CONTROL OF CARROTS DURING DRYING

This thesis research project is aimed at setting up prediction models based on NIR spectroscopy, for quality control of organic carrot discs (Daucus carota L., var. Romance) during hot-air drying process (horizontal flow) up to 8 h. Hot-water blanching was tested at 95°C for 1.5 min, as pre-treatment to control the occurrence of enzymatic browning during drying. Hot-water blanching had a positive impact on the appearance of the carrot discs. PLS regression showed good performances for the prediction of aw (RMSE = 0.04; R2 = 0.96), moisture (RMSE = 0.04; R2 = 0.98), SSC (RMSE = 4.32-4.40 °Brix; R2 =0.88), carotenoids (RMSE = 21.75-23.10; R2 = 0.96) and changes in color (RMSE = 1.40-1.46; R2 = 0.85-0.86) during drying. Also PLSDA classification showed very good metrics (total accuracy 92.38%) in recognising 3-drying steps, both for control and hot-water blanched samples. Features selection by iPLS and iPLSDA algorithms showed results better/equal than models based on full spectrum. For these results, the implementation of low-cost NIR sensors on drier device, seems feasible

Foundations, Properties, and Security Applications of Puzzles: A Survey

Cryptographic algorithms have been used not only to create robust ciphertexts but also to generate cryptograms that, contrary to the classic goal of cryptography, are meant to be broken. These cryptograms, generally called puzzles, require the use of a certain amount of resources to be solved, hence introducing a cost that is often regarded as a time delay---though it could involve other metrics as well, such as bandwidth. These powerful features have made puzzles the core of many security protocols, acquiring increasing importance in the IT security landscape. The concept of a puzzle has subsequently been extended to other types of schemes that do not use cryptographic functions, such as CAPTCHAs, which are used to discriminate humans from machines. Overall, puzzles have experienced a renewed interest with the advent of Bitcoin, which uses a CPU-intensive puzzle as proof of work. In this paper, we provide a comprehensive study of the most important puzzle construction schemes available in the literature, categorizing them according to several attributes, such as resource type, verification type, and applications. We have redefined the term puzzle by collecting and integrating the scattered notions used in different works, to cover all the existing applications. Moreover, we provide an overview of the possible applications, identifying key requirements and different design approaches. Finally, we highlight the features and limitations of each approach, providing a useful guide for the future development of new puzzle schemes.Comment: This article has been accepted for publication in ACM Computing Survey

SpreadMeNot: A Provably Secure and Privacy-Preserving Contact Tracing Protocol

A plethora of contact tracing apps have been developed and deployed in several countries around the world in the battle against Covid-19. However, people are rightfully concerned about the security and privacy risks of such applications. To this end, the contribution of this work is twofold. First, we present an in-depth analysis of the security and privacy characteristics of the most prominent contact tracing protocols, under both passive and active adversaries. The results of our study indicate that all protocols are vulnerable to a variety of attacks, mainly due to the deterministic nature of the underlying cryptographic protocols. Our second contribution is the design and implementation of SpreadMeNot, a novel contact tracing protocol that can defend against most passive and active attacks, thus providing strong (provable) security and privacy guarantees that are necessary for such a sensitive application. Our detailed analysis, both formal and experimental, shows that SpreadMeNot satisfies security, privacy, and performance requirements, hence being an ideal candidate for building a contact tracing solution that can be adopted by the majority of the general public, as well as to serve as an open-source reference for further developments in the field