Biblio
Data Distribution Service (DDS) is a realtime peer-to-peer protocol that serves as a scalable middleware between distributed networked systems found in many Industrial IoT domains such as automotive, medical, energy, and defense. Since the initial ratification of the standard, specifications have introduced a Security Model and Service Plugin Interface (SPI) architecture, facilitating authenticated encryption and data centric access control while preserving interoperable data exchange. However, as Secure DDS v1.1, the default plugin specifications presently exchanges digitally signed capability lists of both participants in the clear during the crypto handshake for permission attestation; thus breaching confidentiality of the context of the connection. In this work, we present an attacker model that makes use of network reconnaissance afforded by this leaked context in conjunction with formal verification and model checking to arbitrarily reason about the underlying topology and reachability of information flow, enabling targeted attacks such as selective denial of service, adversarial partitioning of the data bus, or vulnerability excavation of vendor implementations.
The paper presents a conceptual framework for security embedded task offloading requirements for IoT-Fog based future communication networks. The focus of the paper is to enumerate the need of embedded security requirements in this IoT-Fog paradigm including the middleware technologies in the overall architecture. Task offloading plays a significant role in the load balancing, energy and data management, security, reducing information processing and propagation latencies. The motivation behind introducing the embedded security is to meet the challenges of future smart networks including two main reasons namely; to improve the data protection and to minimize the internet disturbance and intrusiveness. We further discuss the middleware technologies such as cloudlets, mobile edge computing, micro datacenters, self-healing infrastructures and delay tolerant networks for security provision, optimized energy consumption and to reduce the latency. The paper introduces concepts of system virtualization and parallelism in IoT-Fog based systems and highlight the security features of the system. Some research opportunities and challenges are discussed to improve secure offloading from IoT into fog.
Internet of Things (IoT) stack models differ in their architecture, applications and needs. Hence, there are different approaches to apply IoT; for instance, it can be based on traditional data center or based on cloud computing. In fact, Cloud-based IoT is gaining more popularity due to its high scalability and cost effectiveness; hence, it is becoming the norm. However, Cloud is usually located far from the IoT devices and some recent research suggests using Fog-Based IoT by using a nearby light-weight middleware to bridge the gap and to provide the essential support and communication between devices, sensors, receptors and the servers. Therefore, Fog reduces centrality and provides local processing for faster analysis, especially for the time-sensitive applications. Thus, processing is done faster, giving the system flexibility for faster response time. Fog-Based Internet of Things security architecture should be suitable to the environment and provide the necessary measures to improve all security aspects with respect to the available resources and within performance constraints. In this work, we discuss some of these challenges, analyze performance of Fog based IoT and propose a security scheme based on MQTT protocol. Moreover, we present a discussion on security-performance tradeoffs.
Nowadays, physical health of equipment controlled by Cyber-Physical Systems (CPS) is a significant concern. This paper reports a work, in which, a hardware is placed between Programmable Logic Controller (PLC) and the actuator as a solution. The proposed hardware operates in two conditions, i.e. passive and active. Operation of the proposed solution is based on the repetitive operational profile of the actuators. The normal operational profile of the actuator is fed to the protective hardware and is considered as the normal operating condition. In the normal operating condition, the middleware operates in its passive mode and simply monitors electronic signals passing between PLC and Actuator. In case of any malicious operation, the proposed hardware operates in its active mode and both slowly stops the actuator and sends an alert to SCADA server initiating execution of the actuator's emergency profile. Thus, the proposed hardware gains control over the actuator and prevents any physical damage on the operating devices. Two sample experiments are reported in which, results of implementing the proposed solution are reported and assessed. Results show that once the PLC sends incorrect data to actuator, the proposed hardware detects it as an anomaly. Therefore, it does not allow the PLC to send incorrect and unauthorized data pattern to its actuator. Significance of the paper is in introducing a solution to prevent destruction of physical devices apart from source or purpose of the encountered anomaly and apart from CPS functionality or PLC model and operation.
Internet of Things (IoT) is experiencing exponential scalability. This scalability introduces new challenges regarding management of IoT networks. The question that emerges is how we can trust the constrained infrastructure that shortly is expected to be formed by millions of 'things.' The answer is not to trust. This research introduces Amatista, a blockchain-based middleware for management in IoT. Amatista presents a novel zero-trust hierarchical mining process that allows validating the infrastructure and transactions at different levels of trust. This research evaluates Amatista on Edison Arduino Boards.
Security is a key concern in Internet of Things (IoT) designs. In a heterogeneous and complex environment, service providers and service requesters must trust each other. On-off attack is a sophisticated trust threat in which a malicious device can perform good and bad services randomly to avoid being rated as a low trust node. Some countermeasures demands prior level of trust knowing and time to classify a node behavior. In this paper, we introduce a Smart Middleware that automatically assesses the IoT resources trust, evaluating service providers attributes to protect against On-off attacks.
Today's emerging Industrial Internet of Things (IIoT) scenarios are characterized by the exchange of data between services across enterprises. Traditional access and usage control mechanisms are only able to determine if data may be used by a subject, but lack an understanding of how it may be used. The ability to control the way how data is processed is however crucial for enterprises to guarantee (and provide evidence of) compliant processing of critical data, as well as for users who need to control if their private data may be analyzed or linked with additional information - a major concern in IoT applications processing personal information. In this paper, we introduce LUCON, a data-centric security policy framework for distributed systems that considers data flows by controlling how messages may be routed across services and how they are combined and processed. LUCON policies prevent information leaks, bind data usage to obligations, and enforce data flows across services. Policy enforcement is based on a dynamic taint analysis at runtime and an upfront static verification of message routes against policies. We discuss the semantics of these two complementing enforcement models and illustrate how LUCON policies are compiled from a simple policy language into a first-order logic representation. We demonstrate the practical application of LUCON in a real-world IoT middleware and discuss its integration into Apache Camel. Finally, we evaluate the runtime impact of LUCON and discuss performance and scalability aspects.
Internet of Things (IoT) devices offer new sources of contextual information, which can be leveraged by applications to make smart decisions. However, due to the decentralized and heterogeneous nature of such devices - each only having a partial view of their surroundings - there is an inherent risk of uncertain, unreliable and inconsistent observations. This is a serious concern for applications making security related decisions, such as context-aware authentication. We propose and evaluate a middleware for IoT that provides trustworthy context for a collaborative authentication use case. It abstracts a dynamic and distributed fusion scheme that extends the Chair-Varshney (CV) optimal decision fusion rule such that it can be used in a highly dynamic IoT environment. We compare performance and cost trade-offs against regular CV. Experimental evaluation demonstrates that our solution outperforms CV with 10% in a highly dynamic IoT environments, with the ability to detect and mitigate unreliable sensors.
Creating and implementing fault-tolerant distributed algorithms is a challenging task in highly safety-critical industries. Using formal methods supports design and development of complex algorithms. However, formal methods are often perceived as an unjustifiable overhead. This paper presents the experience and insights when using TLA+ and PlusCal to model and develop fault-tolerant and safety-critical modules for TAS Control Platform, a platform for railway control applications up to safety integrity level (SIL) 4. We show how formal methods helped us improve the correctness of the algorithms, improved development efficiency and how part of the gap between model and implementation has been closed by translation to C code. Additionally, we describe how we gained trust in the formal model and tools by following a specific design process called property-driven design, which also implicitly addresses software quality metrics such as code coverage metrics.
In the multi-cloud tenancy environments, Web Service offers an standard approach for discovering and using capabilities in an environment that transcends ownership domains. This brings into concern the ownership and security related to Web Service governance. Our approach for this issue involves an ESB-integrated middleware for security criteria regulation on Clouds. It uses an attribute-based security policy model for the exhibition of assets consumers' security profiles and deducing service accessing decision. Assets represent computing power/functionality and information/data provided by entities. Experiments show the middleware to bring minor governance burdens on the hardware aspect, as well as better performance with colosum scaling property, dealing well with cumbersome policy files, which is probably the situation of complex composite service scenarios.
The publish/subscribe paradigm can be used to build IoT service communication infrastructure owing to its loose coupling and scalability. Its features of decoupling among event producers and event consumers make IoT services collaborations more real-time and flexible, and allow indirect, anonymous and multicast IoT service interactions. However, in this environment, the IoT service cannot directly control the access to the events. This paper proposes a cross-layer security solution to address the above issues. The design principle of our security solution is to embed security policies into events as well as allow the network to route events according to publishers' policies and requirements. This solution helps to improve the system's performance, while keeping features of IoT service interactions and minimizing the event visibility at the same time. Experimental results show that our approach is effective.
NoSQL databases have become popular with enterprises due to their scalable and flexible storage management of big data. Nevertheless, their popularity also brings up security concerns. Most NoSQL databases lacked secure data encryption, relying on developers to implement cryptographic methods at application level or middleware layer as a wrapper around the database. While this approach protects the integrity of data, it increases the difficulty of executing queries. We were motivated to design a system that not only provides NoSQL databases with the necessary data security, but also supports the execution of query over encrypted data. Furthermore, how to exploit the distributed fashion of NoSQL databases to deliver high performance and scalability with massive client accesses is another important challenge. In this research, we introduce Crypt-NoSQL, the first prototype to support execution of query over encrypted data on NoSQL databases with high performance. Three different models of Crypt-NoSQL were proposed and performance was evaluated with Yahoo! Cloud Service Benchmark (YCSB) considering an enormous number of clients. Our experimental results show that Crypt-NoSQL can process queries over encrypted data with high performance and scalability. A guidance of establishing service level agreement (SLA) for Crypt-NoSQL as a cloud service is also proposed.
Today's control systems such as smart environments have the ability to adapt to their environment in order to achieve a set of objectives (e.g., comfort, security and energy savings). This is done by changing their behaviour upon the occurrence of specific events. Building such a system requires to design and implement autonomic loops that collect events and measurements, make decisions and execute the corresponding actions.The design and the implementation of such loops are made difficult by several factors: the complexity of systems with multiple objectives, the risk of conflicting decisions between multiple loops, the inconsistencies that can result from communication errors and hardware failures and the heterogeneity of the devices.In this paper, we propose a design framework for reliable and self-adaptive systems, where multiple autonomic loops can be composed into complex managers, and we consider its application to smart environments. We build upon the proposed framework a generic autonomic loop which combines an automata-based controller that makes correct and coherent decisions, a transactional execution mechanism that avoids inconsistencies, and an abstraction layer that hides the heterogeneity of the devices.We propose patterns for composition of such loops, in parallel, coordinated, and hierarchically, with benefits from the leveraging of automata-based modular constructs, that provides for guarantees on the correct behaviour of the controlled system. We implement our framework with the transactional middleware LINC, the reactive language Heptagon/BZR and the abstraction framework PUTUTU. A case study in the field of building automation is presented to illustrate the proposed framework.
Wireless sensor networks (WSNs) are implemented in various Internet-of-Things applications such as energy management systems. As the applications may involve personal information, they must be protected from attackers attempting to read information or control network devices. Research on WSN security is essential to protect WSNs from attacks. Studies in such research domains propose solutions against the attacks. However, they focus mainly on the security measures rather than on their ease in implementation in WSNs. In this paper, we propose a coordination middleware that provides an environment for constructing updatable WSNs for security. The middleware is based on LINC, a rule-based coordination middleware. The proposed approach allows the development of WSNs and attaches or detaches security modules when required. We implemented three security modules on LINC and on a real network, as case studies. Moreover, we evaluated the implementation costs while comparing the case studies.
The Internet of Things(IoT) has become a popular technology, and various middleware has been proposed and developed for IoT systems. However, there have been few studies on the data management of IoT systems. In this paper, we consider graph database models for the data management of IoT systems because these models can specify relationships in a straightforward manner among entities such as devices, users, and information that constructs IoT systems. However, applying a graph database to the data management of IoT systems raises issues regarding distribution and security. For the former issue, we propose graph database operations integrated with REST APIs. For the latter, we extend a graph edge property by adding access protocol permissions and checking permissions using the APIs with authentication. We present the requirements for a use case scenario in addition to the features of a distributed graph database for IoT data management to solve the aforementioned issues, and implement a prototype of the graph database.