New Anomaly Network Intrusion Detection System in Cloud Environment Based on Optimized Back Propagation Neural Network Using Improved Genetic Algorithm

Cloud computing is distributed architecture, providing computing facilities and storage resource as a service over an open environment (Internet), this lead to different matters related to the security and privacy in cloud computing. Thus, defending network accessible Cloud resources and services from various threats and attacks is of great concern. To address this issue, it is essential to create an efficient and effective Network Intrusion System (NIDS) to detect both outsider and insider intruders with high detection precision in the cloud environment. NIDS has become popular as an important component of the network security infrastructure, which detects malicious activities by monitoring network traffic. In this work, we propose to optimize a very popular soft computing tool widely used for intrusion detection namely, Back Propagation Neural Network (BPNN) using an Improved Genetic Algorithm (IGA). Genetic Algorithm (GA) is improved through optimization strategies, namely Parallel Processing and Fitness Value Hashing, which reduce execution time, convergence time and save processing power. Since,  Learning rate and Momentum term are among the most relevant parameters that impact the performance of BPNN classifier, we have employed IGA to find the optimal or near-optimal values of these two parameters which ensure high detection rate, high accuracy and low false alarm rate. The CloudSim simulator 4.0 and DARPA’s KDD cup datasets 1999 are used for simulation. From the detailed performance analysis, it is clear that the proposed system called “ANIDS BPNN-IGA” (Anomaly NIDS based on BPNN and IGA) outperforms several state-of-art methods and it is more suitable for network anomaly detection

Sistema de anonimización de datos estructurados

Las aproximaciones más empleadas en la industria para proteger los datos privados implican deteriorar su utilidad para los ejercicios de analítica. Por ello, este trabajo propone Anonylitics, un sistema para la anonimización de datos estructurados, que se fundamenta en la preservación de la distribución de los datos numéricos, al mismo tiempo que se garantiza su privacidad. La propuesta realizada permite seguir teniendo información útil para la analítica de datos a nivel empresarial, lo cual es evidenciado a través de la validación efectuada mediante la anonimización de dos conjuntos de datos reales que demuestran el potencial del sistema y sus algoritmos.The most used approaches in the industry to protect private data imply to impair its utility for analytical exercises. For this reason, this work proposes Anonylitics, a system for the anonymization of structured data, which is based on the preservation of the distribution of numerical data, at the same time that their privacy is guaranteed. The proposal makes it possible to continue having useful information for business data analytics, which is evidenced through the validation carried out by anonymizing two sets of real data that demonstrate the potential of the system and its algorithms.Magíster en Ingeniería de Sistemas y ComputaciónMaestrí

Mobile user authentication system (MUAS) for e-commerce applications.

The rapid growth of e-commerce has many associated security concerns. Thus, several studies to develop secure online authentication systems have emerged. Most studies begin with the premise that the intermediate network is the primary point of compromise. In this thesis, we assume that the point of compromise lies within the end-host or browser; this security threat is called the man-in-the-browser (MITB) attack. MITB attacks can bypass security measures of public key infrastructures (PKI), as well as encryption mechanisms for secure socket layers and transport layer security (SSL/TLS) protocol. This thesis focuses on developing a system that can circumvent MITB attacks using a two-phase secure-user authentication system, with phases that include challenge and response generation. The proposed system represents the first step in conducting an online business transaction.The proposed authentication system design contributes to protect the confidentiality of the initiating client by requesting minimal and non-confidential information to bypass the MITB attack and transition the authentication mechanism from the infected browser to a mobile-based system via a challenge/response mechanism. The challenge and response generation process depends on validating the submitted information and ensuring the mobile phone legitimacy. Both phases within the MUAS context mitigate the denial-of-service (DOS) attack via registration information, which includes the client’s mobile number and the International Mobile Equipment Identity (IMEI) of the client’s mobile phone.This novel authentication scheme circumvents the MITB attack by utilising the legitimate client’s personal mobile phone as a detached platform to generate the challenge response and conduct business transactions. Although the MITB attacker may have taken over the challenge generation phase by failing to satisfy the required security properties, the response generation phase generates a secure response from the registered legitimate mobile phone by employing security attributes from both phases. Thus, the detached challenge- and response generation phases are logically linked