Biblio

Securing cloud configurations is an elusive task, which is left up to system administrators who have to base their decisions on "trial and error" experimentations or by observing good practices (e.g., CIS Benchmarks). We propose a knowledge, AND/OR, graphs approach to model cloud deployment security objects and vulnerabilities. In this way, we can capture relationships between configurations, permissions (e.g., CAP\_SYS\_ADMIN), and security profiles (e.g., AppArmor and SecComp). Such an approach allows us to suggest alternative and safer configurations, support administrators in the study of what-if scenarios, and scale the analysis to large scale deployments. We present an initial validation and illustrate the approach with three real vulnerabilities from known sources.

Distributed computation and AI processing at the edge has been identified as an efficient solution to deliver real-time IoT services and applications compared to cloud-based paradigms. These solutions are expected to support the delay-sensitive IoT applications, autonomic decision making, and smart service creation at the edge in comparison to traditional IoT solutions. However, existing solutions have limitations concerning distributed and simultaneous resource management for AI computation and data processing at the edge; concurrent and real-time application execution; and platform-independent deployment. Hence, first, we propose a novel three-layer architecture that facilitates the above service requirements. Then we have developed a novel platform and relevant modules with integrated AI processing and edge computer paradigms considering issues related to scalability, heterogeneity, security, and interoperability of IoT services. Further, each component is designed to handle the control signals, data flows, microservice orchestration, and resource composition to match with the IoT application requirements. Finally, the effectiveness of the proposed platform is tested and have been verified.

The service mesh is a dedicated infrastructure layer in a microservice architecture. It manages service-to-service communication within an application between decoupled or loosely coupled microservices (called services) without modifying their implementations. The service mesh includes APIs for security, traffic and policy management, and observability features. These features are enabled using a pre-defined configuration, which can be changed at runtime with human intervention. However, it has no autonomy to self-manage changes to the microservice application’s operational environment. A better configuration is one that can be customized according to environmental conditions during execution to protect the application from potential threats. This customization requires enabling self-protection mechanisms within the service mesh that evaluate the risk of environmental condition changes and enable appropriate configurations to defend the application from impending threats. In this paper, we design an assessment component into a service mesh that includes a security assurance case to define the threat model and dynamically assess the application given environment changes. We experiment with a demo application, Bookinfo, using an open-source service mesh platform, Istio, to enable self-protection. We consider certain parameters extracted from the service request as environmental conditions. We evaluate those parameters against the threat model and determine the risk of violating a security requirement for controlled and authorized information flow.

Nowadays, the increasing complexity of digital applications for social and business activities has required more and more advanced mechanisms to prove the identity of subjects like those based on the Two-Factor Authentication (2FA). Such an approach improves the typical authentication paradigm but it has still some weaknesses. Specifically, it has to deal with the disadvantages of a centralized architecture causing several security threats like denial of service (DoS) and man-in-the-middle (MITM). In fact, an attacker who succeeds in violating the central authentication server could be able to impersonate an authorized user or block the whole service. This work advances the state of art of 2FA solutions by proposing a decentralized Microservices and Blockchain Based One Time Password (MBB-OTP) protocol for security-enhanced authentication able to mitigate the aforementioned threats and to fit different application scenarios. Experiments prove the goodness of our MBB-OTP protocol considering both private and public Blockchain configurations.

In the economics environment, Job Matching is always a challenge involving the evolution of knowledge and skills. A good matching of skills and jobs can stimulate the growth of economics. Recommender System (RecSys), as one kind of Job Matching, can help the candidates predict the future job relevant to their preferences. However, RecSys still has the problem of cold start and data sparsity. The content-based filtering in RecSys needs the adaptive data for the specific staffing tasks of Bidirectional Encoder Representations from Transformers (BERT). In this paper, we propose a job RecSys based on skills and locations using a domain-specific Knowledge Graph (KG). This system has three parts: a pipeline of Named Entity Recognition (NER) and Relation Extraction (RE) using BERT; a standardization system for pre-processing, semantic enrichment and semantic similarity measurement; a domain-specific Knowledge Graph (KG). Two different relations in the KG are computed by cosine similarity and Term Frequency-Inverse Document Frequency (TF-IDF) respectively. The raw data used in the staffing RecSys include 3000 descriptions of job offers from Indeed, 126 Curriculum Vitae (CV) in English from Kaggle and 106 CV in French from Linx of Capgemini Engineering. The staffing RecSys is integrated under an architecture of Microservices. The autonomy and effectiveness of the staffing RecSys are verified through the experiment using Discounted Cumulative Gain (DCG). Finally, we propose several potential research directions for this research.

Microservices-based architectures gain more and more attention in industry and academia due to their tremendous advantages such as providing resiliency, scalability, composability, etc. To benefit from these advantages, a proper architectural design is very important. The decomposition model of services into microservices and the granularity of these microservices affect the different aspects of the system such as flexibility, maintainability, performance, and security. An inappropriate service decomposition into microservices (improper granularity) may increase the attack surface of the system and lower its security level. In this paper, first, we study the probability of compromising services before and after decomposition. Then we formulate the impacts of possible service decomposition models on confidentiality, integrity, and availability attributes of the system. To do so, we provide equations for measuring confidentiality, integrity, and availability risks of the decomposed services in the system. It is also shown that the number of entry points to the decomposed services and the size of the microservices affect the security attributes of the system. As a use case, we propose three different service decomposition models for the 5G NRF (Network Repository Function) and calculate the impacts of these decomposition models on the confidentiality, integrity, and availability of the system using the provided equations.

Containers technology radically changed the ways for packaging applications and deploying them as services in cloud environments. According to the recent report on security predictions of 2020 by Trend Micro, the vulnerabilities in container components deployed with cloud architecture have been one of the top security concerns for development and operations teams in enterprises. Docker is one of the leading container technologies that automate the deployment of applications into containers. Docker Hub is a public repository by Docker for storing and sharing the Docker images. These Docker images are pulled from the Docker Hub repository and the security of images being used from the repositories in any cloud environment could be at risk. Vulnerabilities in Docker images could have a detrimental effect on enterprise applications. In this paper, the focus is on securing the Docker images using vulnerability centric approach (VCA) to detect the vulnerabilities. A set of use cases compliant with the NIST SP 800-190 Application Container Security Guide is developed for audit compliance of Docker container images with the OWASP Container Security Verification Standards (CSVS). In this paper, firs vulnerabilities of Docker container images are identified and assessed using the VCA. Then, a set of use cases to identify presence of the vulnerabilities is developed to facilitate the security audit of the container images. Finally, it is illustrated how the proposed use cases can be mapped with the requirements of the OWASP Container Security Verification Standards. The use cases can serve as a security auditing tool during the development, deployment, and maintenance of cloud microservices applications.

Cyber-Physical Systems (CPS) such as intelligent connected vehicles, smart farming and smart logistics are constantly generating tons of data and requiring real-time data processing capabilities. Therefore, Edge Computing which provisions computing resources close to the End Devices from the network edge is becoming the ideal platform for CPS. However, it also brings many issues and one of the most prominent challenges is how to ensure the development of trustworthy smart services given the dynamic and distributed nature of Edge Computing. To tackle this challenge, this paper proposes a novel Federated Learning based Edge Computing platform for CPS, named “FengHuoLun”. Specifically, based on FengHuoLun, we can: 1) implement smart services where machine learning models are trained in a trusted Federated Learning framework; 2) assure the trustworthiness of smart services where CPS behaviours are tested and monitored using the Federated Learning framework. As a work in progress, we have presented an overview of the FengHuoLun platform and also some preliminary studies on its key components, and finally discussed some important future research directions.

Microservice architectures adoption is growing expeditiously in market size and adoption, including in business-critical systems. This is due to agility in development and deployment further increased by containers and their characteristics. Ensuring security is still a major concern due to challenges faced such as resource separation and isolation, as improper access to one service might compromise complete systems. This doctoral work intends to advance the security of microservice systems through research and improvement of methodologies for detection, tolerance and mitigation of security intrusions, while overcoming challenges related to multi-tenancy, heterogeneity, dynamicity of systems and environments. Our preliminary research shows that host-based IDSes are applicable in container environments. This will be extended to dynamic scenarios, serving as a steppingstone to research intrusion tolerance techniques suited to these environments. These methodologies will be demonstrated in realistic microservice systems: complex, dynamic, scalable and elastic.

This paper presents Foggy, an anonymous communication system focusing on providing users with anonymous web browsing. Foggy provides a microservice-based proxy for web browsing and other low-latency network activities without exposing users' metadata and browsed content to adversaries. It is designed with decentralized information management, web caching, and configurable service selection. Although Foggy seems to be more centralized compared with Tor, it gains an advantage in manageability while retaining anonymity. Foggy can be deployed by several agencies to become more decentralized. We prototype Foggy and test its performance. Our experiments show Foggy's low latency and deployability, demonstrating its potential to be a commercial solution for real-world deployment.

Microservices architecture has become one of the most prominent software architectures in the software development processes due to its features such as scalability, maintainability, resilience, and composability. It allows developing business applications in a decentralized manner by dividing the important business logic into separate independent services. Digital certificates are used to verify the identity of microservices in most cases. However, the certificate authorities (CA) who issue the certificates to microservices cannot be trusted always since they can issue certificates without the consent of the relevant microservice. Nevertheless, existing implementations of certificate transparency are mostly centralized and has the vulnerability of the single point of failure. The distributed ledger technologies such as blockchain can be used to achieve decentralized nature in certificate transparency implementations. A blockchain-based decentralized certificate transparency system specified for microservices architecture is proposed in this paper to ensure secure communication among services. After the implementation and deployment in a cloud service, the system expressed average certificate querying time of 643 milliseconds along with the highly secured service provided.

With the rapid growth in Natural Language Processing (NLP), all types of industries find a need for analyzing a massive amount of data. Sentiment analysis is becoming a more exciting area for the businessmen and researchers in Text mining & NLP. This process includes the calculation of various sentiments with the help of text mining. Supplementary to this, the world is connected through Information Technology and, businesses are moving toward the next step of the development to make their system more intelligent. Microservices have fulfilled the need for development platforms which help the developers to use various development tools (Languages and applications) efficiently. With the consideration of data analysis for business growth, data security becomes a major concern in front of developers. This paper gives a solution to keep the data secured by providing required access to data scientists without disturbing the base system software. This paper has discussed data storage and exchange policies of microservices through common JavaScript Object Notation (JSON) response which performs the sentiment analysis of customer's data fetched from various microservices through secured APIs.

While the IT industry is embracing the cloud-native technologies, migrating from monolithic architecture to service-oriented architecture is not a trivial process. It involves a lot of dissection and abstraction. The layer of abstraction designed for simplifying the development quickly becomes the barrier of visibility and the source of misconfigurations. The complexity may give microservices a larger attack surface compared to monolithic applications. This talk presents a microservices threat modeling that uncovers the attack vectors hidden in each abstraction layer. Scenarios of security breaches in microservices platforms are discussed, followed by the countermeasures to close these attack vectors. Finally, a decision-making process for architecting secure microservices is presented.

Since cyber-physical systems are inherently vulnerable to information leaks, software architects need to reason about security policies to define desired and undesired information flow through a system. The microservice architectural style requires the architects to refine a macro-level security policy into micro-level policies for individual microservices. However, when policies are refined in an ill-formed way, information leaks can emerge on composition of microservices. Related approaches to prevent such leaks do not take into account characteristics of cyber-physical systems like real-time behavior or message passing communication. In this paper, we enable the refinement and verification of information-flow security policies for cyber-physical microservice architectures. We provide architects with a set of well-formedness rules for refining a macro-level policy in a way that enforces its security restrictions. Based on the resulting micro-level policies, we present a verification technique to check if the real-time message passing of microservices is secure. In combination, our contributions prevent information leaks from emerging on composition. We evaluate the accuracy of our approach using an extension of the CoCoME case study.

Advances in our understanding of the nature of cognition in its myriad forms (Embodied, Embedded, Extended, and Enactive) displayed in all living beings (cellular organisms, animals, plants, and humans) and new theories of information, info-computation and knowledge are throwing light on how we should build software systems in the digital universe which mimic and interact with intelligent, sentient and resilient beings in the physical universe. Recent attempts to infuse cognition into computing systems to push the boundaries of Church-Turing thesis have led to new computing models that mimic biological systems in encoding knowledge structures using both algorithms executed in stored program control machines and neural networks. This paper presents a new model and implements an application as hierarchical named network composed of microservices to create a managed process workflow by enabling dynamic configuration and reconfiguration of the microservice network. We demonstrate the resiliency, efficiency and scaling of the named microservice network using a novel edge cloud platform by Platina Systems. The platform eliminates the need for Virtual Machine overlay and provides high performance and low-latency with L3 based 100 GbE network and SSD support with RDMA and NVMeoE. The hierarchical named microservice network using Kubernetes provisioning stack provides all the cloud features such as elasticity, autoscaling, self-repair and live-migration without reboot. The model is derived from a recent theoretical framework for unification of different models of computation using "Structural Machines.'' They are shown to simulate Turing machines, inductive Turing machines and also are proved to be more efficient than Turing machines. The structural machine framework with a hierarchy of controllers managing the named service connections provides dynamic reconfiguration of the service network from browsers to database to address rapid fluctuations in the demand for or the availability of resources without having to reconfigure IP address base networks.

Contemporary enterprise systems focus primarily on performance and development/maintenance costs. Dealing with cyber-threats and system compromise is relegated to good coding (i.e., defensive programming) and secure environment (e.g., patched OS, firewalls, etc.). This approach, while a necessary start, is not sufficient. Such security relies on no missteps, and compromise only need a single flaw; consequently, we must design for compromise and mitigate its impact. One approach is to utilize fine-grained modularization and isolation. In such a system, decomposition ensures that compromise of a single module presents limited and known risk to data/resource theft and denial. We propose mechanisms for automating such modular composition and consider its system performance impact.

Thanks to its decentralized structure and immutability, blockchain technology has the potential to address relevant security and privacy challenges in the Internet of Things (IoT). In particular, by hosting and executing smart contracts, blockchain allows secure, flexible, and traceable message communication between IoT devices. The unique characteristics of IoT systems, such as heterogeneity and pervasiveness, however, pose challenges in designing smart contracts for such systems. In this paper, we study these challenges and propose a design approach for smart contracts used in IoT systems. The main goal of our design model is to enhance the development of IoT smart contracts based on the inherent pervasive attributes of IoT systems. In particular, the design model allows the smart contracts to encapsulate functionalities such as contractlevel communication between IoT devices, access to data-sources within contracts, and interoperability of heterogeneous IoT smart contracts. The essence of our approach is structuring the design of IoT smart contracts as self-contained software services, inspired by the microservice architecture model. The flexibility, scalability and modularity of this model make it an efficient approach for developing pervasive IoT smart contracts.

Traditional Intrusion Detection Systems (IDSes) are generally implemented on vendor proprietary appliances or middleboxes, which usually lack a general programming interface, and their versatility and flexibility are also very poor. Emerging Network Function Virtualization (NFV) technology can virtualize IDSes and elastically scale them to deal with attack traffic variations. However, existing NFV solutions treat a virtualized IDS as a monolithic piece of software, which could lead to inflexibility and significant waste of resources. In this paper, we propose a novel approach to virtualize IDSes as microservices where the virtualized IDSes can be customized on demand, and the underlying microservices could be shared and scaled independently. We also conduct experiments, which demonstrate that virtualizing IDSes as microservices can gain greater flexibility and resource efficiency.

Current software platforms for service composition are based on orchestration, choreography or hierarchical orchestration. However, such approaches for service composition only support partial compositionality; thereby, increasing the complexity of SOA development. In this paper, we propose DX-MAN, a platform that supports total compositionality. We describe the main concepts of DX-MAN with the help of a case study based on the popular MusicCorp.

Service composition is currently done by (hierarchical) orchestration and choreography. However, these approaches do not support explicit control flow and total compositionality, which are crucial for the scalability of service-oriented systems. In this paper, we propose exogenous connectors for service composition. These connectors support both explicit control flow and total compositionality in hierarchical service composition. To validate and evaluate our proposal, we present a case study based on the popular MusicCorp.

Given the advent of cyber-physical systems (CPS), event-based control paradigms such as complex event processing (CEP) are vital enablers for adaptive analytical control mechanisms. CPS are becoming a high-profile research topic as they are key to disruptive digital innovations such as autonomous driving, industrial internet, smart grid and ambient assisted living. However, organizational and technological scalability of today's CEP approaches is limited by their monolithic architectures. This leads to the research idea for atomic CEP entities and the hypothesis that a network of small event-based control services is better suited for CPS development and operation than current centralised approaches. In addition, the paper summarizes preliminary results of the presented doctoral work and outlines questions for future research as well as an evaluation plan.