Blockchains and the commons

Blockchain phenomena is similar to the last century gold rush. Blockchain technologies are publicized as being the technical solution for fully decentralizing activities that were for centuries centralized such as administration and banking. Therefore, prominent socio-economical actors all over the world are attracted and ready to invest in these technologies. Despite their large publicity, blockchains are far from being a technology ready to be used in critical economical applications and scientists multiply their effort in warning about the risks of using this technology before understanding and fully mastering it. That is, a blockchain technology evolves in a complex environment where rational and irrational behaviors are melted with faults and attacks. This position paper advocates that the theoretical foundations of blockchains should be a cross research between classical distributed systems, distributed cryptography, self-organized micro-economies, game theory and formal methods. We discuss in the following a set of open research directions interesting in this context

A Survey on Smartphone-Based Crowdsensing Solutions

© 2016 Willian Zamora et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.[EN] In recent years, the widespread adoption of mobile phones, combined with the ever-increasing number of sensors that smartphones are equipped with, greatly simplified the generalized adoption of crowdsensing solutions by reducing hardware requirements and costs to a minimum. These factors have led to an outstanding growth of crowdsensing proposals from both academia and industry. In this paper, we provide a survey of smartphone-based crowdsensing solutions that have emerged in the past few years, focusing on 64 works published in top-ranked journals and conferences. To properly analyze these previous works, we first define a reference framework based on how we classify the different proposals under study. The results of our survey evidence that there is still much heterogeneity in terms of technologies adopted and deployment approaches, although modular designs at both client and server elements seem to be dominant. Also, the preferred client platform is Android, while server platforms are typically web-based, and client-server communications mostly rely on XML or JSON over HTTP. The main detected pitfall concerns the performance evaluation of the different proposals, which typically fail to make a scalability analysis despite being critical issue when targeting very large communities of users.This work was partially supported by the Ministerio de Economia y Competitividad, Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad, Proyectos I+D+I 2014, Spain, under Grant TEC2014-52690-R, the "Universidad Laica Eloy Alfaro de Manabi-ULEAM," and the "Programa de Becas SENESCYT de la Republica del Ecuador."Zamora-Mero, WJ.; Tavares De Araujo Cesariny Calafate, CM.; Cano Escribá, JC.; Manzoni, P. (2016). A Survey on Smartphone-Based Crowdsensing Solutions. Mobile Information Systems. 2016:1-26. https://doi.org/10.1155/2016/9681842S126201

Android Application Security Scanning Process

This chapter presents the security scanning process for Android applications. The aim is to guide researchers and developers to the core phases/steps required to analyze Android applications, check their trustworthiness, and protect Android users and their devices from being victims to different malware attacks. The scanning process is comprehensive, explaining the main phases and how they are conducted including (a) the download of the apps themselves; (b) Android application package (APK) reverse engineering; (c) app feature extraction, considering both static and dynamic analysis; (d) dataset creation and/or utilization; and (e) data analysis and data mining that result in producing detection systems, classification systems, and ranking systems. Furthermore, this chapter highlights the app features, evaluation metrics, mechanisms and tools, and datasets that are frequently used during the app’s security scanning process

A Weighted Minimum Redundancy Maximum Relevance Technique for Ransomware Early Detection in Industrial IoT

Ransomware attacks against Industrial Internet of Things (IIoT) have catastrophic consequences not only to the targeted infrastructure, but also the services provided to the public. By encrypting the operational data, the ransomware attacks can disrupt the normal operations, which represents a serious problem for industrial systems. Ransomware employs several avoidance techniques, such as packing, obfuscation, noise insertion, irrelevant and redundant system call injection, to deceive the security measures and make both static and dynamic analysis more difficult. In this paper, a Weighted minimum Redundancy maximum Relevance (WmRmR) technique was proposed for better feature significance estimation in the data captured during the early stages of ransomware attacks. The technique combines an enhanced mRMR (EmRmR) with the Term Frequency-Inverse Document Frequency (TF-IDF) so that it can filter out the runtime noisy behavior based on the weights calculated by the TF-IDF. The proposed technique has the capability to assess whether a feature in the relevant set is important or not. It has low-dimensional complexity and a smaller number of evaluations compared to the original mRmR method. The TF-IDF was used to evaluate the weights of the features generated by the EmRmR algorithm. Then, an inclusive entropy-based refinement method was used to decrease the size of the extracted data by identifying the system calls with strong behavioral indication. After extensive experimentation, the proposed technique has shown to be effective for ransomware early detection with low-complexity and few false-positive rates. To evaluate the proposed technique, we compared it with existing behavioral detection methods

Computer Science 2019 APR Self-Study & Documents

UNM Computer Science APR self-study report and review team report for Spring 2019, fulfilling requirements of the Higher Learning Commission

Implementation of DEMOS Voting

Η εργασία αυτή ασχολείται τις προκλήσεις στην υλοποίηση των συστημάτων ηλεκτρονικής ψηφοφορίας. Στο πρώτο μέρος αναλύονται οι προδιαγραφές με τις οποίες τα συστήματα ψηφοφορίας (είτε παραδοσιακά, είτε ηλεκτρονικά) οφείλουν να συμμορφώνονται. Έμφαση δίνεται στις λεπτομέρειες υλοποίησης των συστημάτων ηλεκτρονικής ψηφοφορίας και στο πως αυτά συγκρίνονται με τα συστήματα που βασίζονται σε έντυπα. Στο δεύτερο μέρος περιγράφεται ένα νέο σύστημα ηλεκτρονικής ψηφοφορίας που υλοποιήθηκε στα πλαίσια αυτής της εργασίας. Στόχος αυτού του συστήματος είναι να ικανοποιήσει τις παραπάνω απαιτήσεις.This work deals with the implementation challenges of electronic voting systems. The first part analyzes the standards that an ideal voting system (either traditional or electronic) should comply with. Focus is put on the implementation details of electronic voting systems and how they compare to paper-based ones. The second part describes a new electronic voting system that was implemented as part of this work. The goal of this system is to fulfill the above requirements

LEVERAGING PEER-TO-PEER ENERGY SHARING FOR RESOURCE OPTIMIZATION IN MOBILE SOCIAL NETWORKS

Mobile Opportunistic Networks (MSNs) enable the interaction of mobile users in the vicinity through various short-range wireless communication technologies (e.g., Bluetooth, WiFi) and let them discover and exchange information directly or in ad hoc manner. Despite their promise to enable many exciting applications, limited battery capacity of mobile devices has become the biggest impediment to these appli- cations. The recent breakthroughs in the areas of wireless power transfer (WPT) and rechargeable lithium batteries promise the use of peer-to-peer (P2P) energy sharing (i.e., the transfer of energy from the battery of one member of the mobile network to the battery of the another member) for the efficient utilization of scarce energy resources in the network. However, due to uncertain mobility and communication opportunities in the network, resource optimization in these opportunistic networks is very challenging. In this dissertation, we study energy utilization in three different applications in Mobile Social Networks and target to improve the energy efficiency in the network by benefiting from P2P energy sharing among the nodes. More specifi- xi cally, we look at the problems of (i) optimal energy usage and sharing between friendly nodes in order to reduce the burden of wall-based charging, (ii) optimal content and energy sharing when energy is considered as an incentive for carrying the content for other nodes, and (iii) energy balancing among nodes for prolonging the network lifetime. We have proposed various novel protocols for the corresponding applications and have shown that they outperform the state-of-the-art solutions and improve the energy efficiency in MSNs while the application requirements are satisfied