An Efficient and Secure Symmetric key used for EasySMS protocol

SMS (Short Message Service) is a widely used communication between the end users. SMS is being used in our different applications. The Short Message Service (SMS) usually whatever we exchange the original format, sometimes we used to send the some secret message like our email password, pass code and bank password. We send SMS is in original format, our traditional SMS does not secure this trusted information, so the proposed protocol called EasySMS it will provide very secure and protect the trusted information between the end users. DOI: 10.17762/ijritcc2321-8169.15028

Elliptic Curve Cryptography Services for Mobile Operating Systems

Mobile devices as smartphones, tablets and laptops, are nowadays considered indispensable objects by most people in developed countries. A s personal and work assistant s , some of th e s e devices store , process and transmit sensitive and private data. Naturally , the number of mobile applications with integrated cryptographic mechanisms or offering security services has been significantly increasing in the last few years. Unfortunately, not all of those applications are secure by design, while other may not implement the cryptographic primitives correctly. Even the ones that implement them correctly may suffer from longevity problems, since cryptographic primitives that are considered secure nowadays may become obsolete in the next few years. Rivest, Shamir and Adleman (RSA) is an example of an widely used cryptosystem that may become depleted shorty . While the security issues in the mobile computing environment may be of median severity for casual users, they may be critical for several professional classes, namely lawyers, journalists and law enforcement agents. As such, it is important to approach these problems in a structured manner. This master’s program is focused on the engineering and implementation of a mobile application offering a series of security services. The application was engineered to be secure by design for the Windows Phone 8.1 Operating System (OS) which, at the time of writing this dissertation, was the platform with the most discreet offer in terms of applications of this type. The application provides services such as secure exchange of a cryptographic secret, encryption and digital signature of messages and files, management of contacts and encryption keys and secure password generation and storage. Part of the cryptographic primitives used in this work are from the Elliptic Curve Cryptography (ECC) theory, for which the discrete logarithm problem is believed to be harder and key handling is easier. The library defining a series of curves and containing the procedures and operations supporting the ECC primitives was implemented from scratch, since there was none available, comprising one of the contributions of this work. The work evolved from the analysis of the state-of-the-art to the requirements analysis and software engineering phase, thoroughly described herein, ending up with the development of a prototype. The engineering of the application included the definition of a trust model for the exchange of public keys and the modeling of the supporting database. The most visible outcomes of this master’s program are the fully working prototype of a mobile application offering the aforementioned security services, the implementation of an ECC library for the .NET framework, and this dissertation. The source code for the ECC library was made available online on GitHub with the name ECCryptoLib [Ana15]. Its development and improvement was mostly dominated by unit testing. The library and the mobile application were developed in C?. The level of security offered by the application is guaranteed via the orchestration and combination of state-of-the-art symmetric key cryptography algorithms, as the Advanced Encryption Standard (AES) and Secure Hash Algorithm 256 (SHA256) with the ECC primitives. The generation of passwords is done by using several sensors and inputs as entropy sources, which are fed to a cryptographically secure hash function. The passwords are stored in an encrypted database, whose encryption key changes every time it is opened, obtained using a Password-Based Key Derivation Function 2 (PBKDF2) from a master password. The trust model for the public keys designed in the scope of this work is inspired in Pretty Good Privacy (PGP), but granularity of the trust levels is larger.Dispositivos móveis como computadores portáteis, smartphones ou tablets, são, nos dias de hoje, considerados objectos indispensáveis pela grande maioria das pessoas residentes em países desenvolvidos. Por serem utilizados como assistentes pessoais ou de trabalho, alguns destes dispositivos guardam, processam e transmitem dados sensíveis ou privados. Naturalmente, o número de aplicações móveis com mecanismos criptográficos integrados ou que oferecem serviços de segurança, tem vindo a aumentar de forma significativa nos últimos anos. Infelizmente, nem todas as aplicações são seguras por construção, e outras podem não implementar as primitivas criptográficas corretamente. Mesmo aquelas que as implementam corretamente podem sofrer de problemas de longevidade, já que primitivas criptográficas que são hoje em dia consideradas seguras podem tornar-se obsoletas nos próximos anos. O Rivest, Shamir and Adleman (RSA) constitui um exemplo de um sistema criptográfico muito popular que se pode tornar obsoleto a curto prazo. Enquanto que os problemas de segurança em ambientes de computação móvel podem ser de média severidade para utilizadores casuais, estes são normalmente críticos para várias classes profissionais, nomeadamente advogados, jornalistas e oficiais da justiça. É, por isso, importante, abordar estes problemas de uma forma estruturada. Este programa de mestrado foca-se na engenharia e implementação de uma aplicação móvel que oferece uma série de serviços de segurança. A aplicação foi desenhada para ser segura por construção para o sistema operativo Windows Phone 8.1 que, altura em que esta dissertação foi escrita, era a plataforma com a oferta mais discreta em termos de aplicações deste tipo. A aplicação fornece funcionalidades como trocar um segredo criptográfico entre duas entidades de forma segura, cifra, decifra e assinatura digital de mensagens e ficheiros, gestão de contactos e chaves de cifra, e geração e armazenamento seguro de palavras-passe. Parte das primitivas criptográficas utilizadas neste trabalho fazem parte da teoria da criptografia em curvas elípticas, para a qual se acredita que o problema do logaritmo discreto é de mais difícil resolução e para o qual a manipulação de chaves é mais simples. A biblioteca que define uma série de curvas, e contendo os procedimentos e operações que suportam as primitivas criptográficas, foi totalmente implementada no âmbito deste trabalho, dado ainda não existir nenhuma disponível no seu início, compreendendo assim uma das suas contribuições. O trabalho evoluiu da análise do estado da arte para o levantamento dos requisitos e para a fase de engenharia de software, aqui descrita detalhadamente, culminando no desenvolvimento de um protótipo. A engenharia da aplicação incluiu a definição de um sistema de confiança para troca de chaves públicas e também modelação da base de dados de suporte. Os resultados mais visíveis deste programa de mestrado são o protótipo da aplicação móvel, completamente funcional e disponibilizando as funcionalidades de segurança acima mencionadas, a implementação de uma biblioteca Elliptic Curve Cryptography (ECC) para framework .NET, e esta dissertação. O código fonte com a implementação da biblioteca foi publicada online. O seu desenvolvimento e melhoramento foi sobretudo dominado por testes unitários. A biblioteca e a aplicação móvel foram desenvolvidas em C?. O nível de segurança oferecido pela aplicação é garantido através da orquestração e combinação de algoritmos da criptografia de chave simétrica atuais, como o Advanced Encryption Standard (AES) e o Secure Hash Algorithm 256 (SHA256), com as primitivas ECC. A geração de palavras-passe é feita recorrendo utilizando vários sensores e dispoitivos de entrada como fontes de entropia, que posteriormente são alimentadas a uma função de hash criptográfica. As palavras-passe são guardadas numa base de dados cifrada, cuja chave de cifra muda sempre que a base de dados é aberta, sendo obtida através da aplicação de um Password-Based Key Derivation Function 2 (PBKDF2) a uma palavrapasse mestre. O modelo de confiança para chaves públicas desenhado no âmbito deste trabalho é inspirado no Pretty Good Privacy (PGP), mas a granularidade dos níveis de confiança é superior

VoteLab: A Modular and Adaptive Experimentation Platform for Online Collective Decision Making

Digital democracy and new forms for direct digital participation in policy making gain unprecedented momentum. This is particularly the case for preferential voting methods and decision-support systems designed to promote fairer, more inclusive and legitimate collective decision-making processes in citizens assemblies, participatory budgeting and elections. However, a systematic human experimentation with different voting methods is cumbersome and costly. This paper introduces VoteLab, an open-source and thoroughly-documented platform for modular and adaptive design of voting experiments. It supports to visually and interactively build reusable campaigns with a choice of different voting methods, while voters can easily respond to subscribed voting questions on a smartphone. A proof-of-concept with four voting methods and questions on COVID-19 in an online lab experiment have been used to study the consistency of voting outcomes. It demonstrates the capability of VoteLab to support rigorous experimentation of complex voting scenarios

Security Management for The Internet of Things

The expansion of Internet connected automation provides a number of opportunities and applications that were not imaginable before. A prominent example is the Internet of things (IoT). IoT is a network system that consists of many wired or wireless smart sensors and applications. The development of IoT has been taking decades. However, cyberattacks threat the IoT since the day it was born; different threats and attacks may cause serious disasters to the network system without the essential security protection. Thus, the security and the management of the IoT security system become quite significant. This research work into security management of IoT involves five sections. We first point out the conception and background of the IoT. Then, the security requirements for the IoT have been discussed intensively. Next a proposed layered-security management architecture has been outlined and described. An example of how conveniently this proposed architecture can be used to come up with the security management for a network of the IoT is explained in detail. Finally, summarise the results of implementing the proposed security functions architecture to obtain the efficient and strong security in an IoT environment

MADAM: Effective and Efficient Behavior-based Android Malware Detection and Prevention

Android users are constantly threatened by an increasing number of malicious applications (apps), generically called malware. Malware constitutes a serious threat to user privacy, money, device and file integrity. In this paper we note that, by studying their actions, we can classify malware into a small number of behavioral classes, each of which performs a limited set of misbehaviors that characterize them. These misbehaviors can be defined by monitoring features belonging to different Android levels. In this paper we present MADAM, a novel host-based malware detection system for Android devices which simultaneously analyzes and correlates features at four levels: kernel, application, user and package, to detect and stop malicious behaviors. MADAM has been designed to take into account those behaviors characteristics of almost every real malware which can be found in the wild. MADAM detects and effectively blocks more than 96% of malicious apps, which come from three large datasets with about 2,800 apps, by exploiting the cooperation of two parallel classifiers and a behavioral signature-based detector. Extensive experiments, which also includes the analysis of a testbed of 9,804 genuine apps, have been conducted to show the low false alarm rate, the negligible performance overhead and limited battery consumption

Customer churn prediction in telecom using machine learning and social network analysis in big data platform

Customer churn is a major problem and one of the most important concerns for large companies. Due to the direct effect on the revenues of the companies, especially in the telecom field, companies are seeking to develop means to predict potential customer to churn. Therefore, finding factors that increase customer churn is important to take necessary actions to reduce this churn. The main contribution of our work is to develop a churn prediction model which assists telecom operators to predict customers who are most likely subject to churn. The model developed in this work uses machine learning techniques on big data platform and builds a new way of features' engineering and selection. In order to measure the performance of the model, the Area Under Curve (AUC) standard measure is adopted, and the AUC value obtained is 93.3%. Another main contribution is to use customer social network in the prediction model by extracting Social Network Analysis (SNA) features. The use of SNA enhanced the performance of the model from 84 to 93.3% against AUC standard. The model was prepared and tested through Spark environment by working on a large dataset created by transforming big raw data provided by SyriaTel telecom company. The dataset contained all customers' information over 9 months, and was used to train, test, and evaluate the system at SyriaTel. The model experimented four algorithms: Decision Tree, Random Forest, Gradient Boosted Machine Tree "GBM" and Extreme Gradient Boosting "XGBOOST". However, the best results were obtained by applying XGBOOST algorithm. This algorithm was used for classification in this churn predictive model.Comment: 24 pages, 14 figures. PDF https://rdcu.be/budK