Secure entity authentication

According to Wikipedia, authentication is the act of confirming the truth of an attribute of a single piece of a datum claimed true by an entity. Specifically, entity authentication is the process by which an agent in a distributed system gains confidence in the identity of a communicating partner (Bellare et al.). Legacy password authentication is still the most popular one, however, it suffers from many limitations, such as hacking through social engineering techniques, dictionary attack or database leak. To address the security concerns in legacy password-based authentication, many new authentication factors are introduced, such as PINs (Personal Identification Numbers) delivered through out-of-band channels, human biometrics and hardware tokens. However, each of these authentication factors has its own inherent weaknesses and security limitations. For example, phishing is still effective even when using out-of-band-channels to deliver PINs (Personal Identification Numbers). In this dissertation, three types of secure entity authentication schemes are developed to alleviate the weaknesses and limitations of existing authentication mechanisms: (1) End user authentication scheme based on Network Round-Trip Time (NRTT) to complement location based authentication mechanisms; (2) Apache Hadoop authentication mechanism based on Trusted Platform Module (TPM) technology; and (3) Web server authentication mechanism for phishing detection with a new detection factor NRTT. In the first work, a new authentication factor based on NRTT is presented. Two research challenges (i.e., the secure measurement of NRTT and the network instabilities) are addressed to show that NRTT can be used to uniquely and securely identify login locations and hence can support location-based web authentication mechanisms. The experiments and analysis show that NRTT has superior usability, deploy-ability, security, and performance properties compared to the state-of-the-art web authentication factors. In the second work, departing from the Kerb eros-centric approach, an authentication framework for Hadoop that utilizes Trusted Platform Module (TPM) technology is proposed. It is proven that pushing the security down to the hardware level in conjunction with software techniques provides better protection over software only solutions. The proposed approach provides significant security guarantees against insider threats, which manipulate the execution environment without the consent of legitimate clients. Extensive experiments are conducted to validate the performance and the security properties of the proposed approach. Moreover, the correctness and the security guarantees are formally proved via Burrows-Abadi-Needham (BAN) logic. In the third work, together with a phishing victim identification algorithm, NRTT is used as a new phishing detection feature to improve the detection accuracy of existing phishing detection approaches. The state-of-art phishing detection methods fall into two categories: heuristics and blacklist. The experiments show that the combination of NRTT with existing heuristics can improve the overall detection accuracy while maintaining a low false positive rate. In the future, to develop a more robust and efficient phishing detection scheme, it is paramount for phishing detection approaches to carefully select the features that strike the right balance between detection accuracy and robustness in the face of potential manipulations. In addition, leveraging Deep Learning (DL) algorithms to improve the performance of phishing detection schemes could be a viable alternative to traditional machine learning algorithms (e.g., SVM, LR), especially when handling complex and large scale datasets

Multiprotocol Authentication Device for HPC and Cloud Environments Based on Elliptic Curve Cryptography

Multifactor authentication is a relevant tool in securing IT infrastructures combining two or more credentials. We can find smartcards and hardware tokens to leverage the authentication process, but they have some limitations. Users connect these devices in the client node to log in or request access to services. Alternatively, if an application wants to use these resources, the code has to be amended with bespoke solutions to provide access. Thanks to advances in system-on-chip devices, we can integrate cryptographically robust, low-cost solutions. In this work, we present an autonomous device that allows multifactor authentication in client–server systems in a transparent way, which facilitates its integration in High-Performance Computing (HPC) and cloud systems, through a generic gateway. The proposed electronic token (eToken), based on the system-on-chip ESP32, provides an extra layer of security based on elliptic curve cryptography. Secure communications between elements use Message Queuing Telemetry Transport (MQTT) to facilitate their interconnection. We have evaluated different types of possible attacks and the impact on communications. The proposed system offers an efficient solution to increase security in access to services and systems.Spanish Ministry of Science, Innovation and Universities (MICINN) PGC2018-096663-B-C44European Union (EU

Big Data and Large-scale Data Analytics: Efficiency of Sustainable Scalability and Security of Centralized Clouds and Edge Deployment Architectures

One of the significant shifts of the next-generation computing technologies will certainly be in the development of Big Data (BD) deployment architectures. Apache Hadoop, the BD landmark, evolved as a widely deployed BD operating system. Its new features include federation structure and many associated frameworks, which provide Hadoop 3.x with the maturity to serve different markets. This dissertation addresses two leading issues involved in exploiting BD and large-scale data analytics realm using the Hadoop platform. Namely, (i)Scalability that directly affects the system performance and overall throughput using portable Docker containers. (ii) Security that spread the adoption of data protection practices among practitioners using access controls. An Enhanced Mapreduce Environment (EME), OPportunistic and Elastic Resource Allocation (OPERA) scheduler, BD Federation Access Broker (BDFAB), and a Secure Intelligent Transportation System (SITS) of multi-tiers architecture for data streaming to the cloud computing are the main contribution of this thesis study

A JSON Token-Based Authentication and Access Management Schema for Cloud SaaS Applications

Cloud computing is significantly reshaping the computing industry built around core concepts such as virtualization, processing power, connectivity and elasticity to store and share IT resources via a broad network. It has emerged as the key technology that unleashes the potency of Big Data, Internet of Things, Mobile and Web Applications, and other related technologies, but it also comes with its challenges - such as governance, security, and privacy. This paper is focused on the security and privacy challenges of cloud computing with specific reference to user authentication and access management for cloud SaaS applications. The suggested model uses a framework that harnesses the stateless and secure nature of JWT for client authentication and session management. Furthermore, authorized access to protected cloud SaaS resources have been efficiently managed. Accordingly, a Policy Match Gate (PMG) component and a Policy Activity Monitor (PAM) component have been introduced. In addition, other subcomponents such as a Policy Validation Unit (PVU) and a Policy Proxy DB (PPDB) have also been established for optimized service delivery. A theoretical analysis of the proposed model portrays a system that is secure, lightweight and highly scalable for improved cloud resource security and management.Comment: 6 Page

Fast-Sec: an approach to secure Big Data processing in the cloud

Group Security is an important concern in computer systems, which is especially remarkable when the system has to handle large amounts of data and some different users accessing this data with different accessing permissions. This work proposes an innovative approach for providing a security infrastructure support to Big Data Analytic in Cloud-based systems named Fast-sec. Fast-Sec handles systems with large volumes of data from heterogeneous sources, in which users may access the system by different platforms, consuming or providing data. The security infrastructure proposed in Fast-Sec provides an authentication mechanism for users, and data access control adapted to high demands from cloud-based Big Data environment. The reported results show the adequacy of the proposed safety infrastructure to the cloud-based systems processing Big Data. © 2017 Informa UK Limited, trading as Taylor & Franci

Parallel network file systems using authenticated key exchange protocols

The keyestablishment for secure many-to-many communications is very important nowadays. The problem is inspired by the proliferation of large-scale distributed file systems supporting parallel access to multiple storage devices. In this, a variety of authenticated key exchange protocols that are designed to address the issues. This shows that these protocols are capable of reducing the workload of the metadata server and concurrently supporting forward secrecy and escrow-freeness. All this requires only a small fraction of increased computation overhead at the client. This proposed three authenticated key exchange protocols for parallel network file system (pNFS). The protocols offer three appealing advantages over the existing Kerberos-based protocol. First, the metadata server executing these protocols has much lower workload than that of the Kerberos-based approach. Second, two of these protocols provide forward secrecy: one is partially forward secure (with respect to multiple sessions within a time period), while the other is fully forward secure (with respect to a session). Third, designed a protocol which not only provides forward secrecy, but is also escrow-free