Biblio

Wireless Sensor Network (WSN) are spread everywhere throughout the world and are ordinarily used to gather physical data from the encompassing scene. WSN play a focal part in the Internet of Things (IoT) vision. WSN is rising as a noticeable component in the middleware connecting together the Internet of Things (IoT) and the Web of Things (WoT). But the integration of WSN to WoT brings new challenges that cannot be solved in a satisfactory way with traditional layer of security. This paper examined the security issue of integration between WSN and WoT, aiming to shed light on how the WSN and WoT security issue are understood and applied, both in academia and industries. This paper introduces security perfective of integration WSN to WoT which offers capabilities to identify and connect worldwide physical objects into a unified system. As a part of the integration, serious concerns are raised over access of personal information pertaining to device (smart thing) and individual privacy. The motivation of this paper is to summarizes the security threats of the integration and suggestion to mitigate the threat.

A Software-Defined Wireless Sensor Network (SD-WSN) is a recently developed model which is expected to play a large role not only in the development of the Internet of Things (IoT) paradigm but also as a platform for other applications such as smart water management. This model makes use of a Software-Defined Networking (SDN) approach to manage a Wireless Sensor Network (WSN) in order to solve most of the inherent issues surrounding WSNs. One of the most important aspects of any network, is security. This is an area that has received little attention within the development of SDWSNs, as most research addresses security concerns within SDN and WSNs independently. There is a need for research into the security of SDWSN. Some concepts from both SDN and WSN security can be adjusted to suit the SDWSN model while others cannot. Further research is needed into consolidating SDN and WSN security measures to consider security in SDWSN. Threats, challenges and potential solutions to securing SDWSN are presented by considering both the WSN and SDN paradigms.

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.

Separation of network control from devices in Software Defined Network (SDN) allows for centralized implementation and management of security policies in a cloud computing environment. The ease of programmability also makes SDN a great platform implementation of various initiatives that involve application deployment, dynamic topology changes, and decentralized network management in a multi-tenant data center environment. Dynamic change of network topology, or host reconfiguration in such networks might require corresponding changes to the flow rules in the SDN based cloud environment. Verifying adherence of these new flow policies in the environment to the organizational security policies and ensuring a conflict free environment is especially challenging. In this paper, we extend the work on rule conflicts from a traditional environment to an SDN environment, introducing a new classification to describe conflicts stemming from cross-layer conflicts. Our framework ensures that in any SDN based cloud, flow rules do not have conflicts at any layer; thereby ensuring that changes to the environment do not lead to unintended consequences. We demonstrate the correctness, feasibility and scalability of our framework through a proof-of-concept prototype.

Software defined networking promises network operators to dramatically simplify network management. It provides flexibility and innovation through network programmability. With SDN, network management moves from codifying functionality in terms of low-level device configuration to building software that facilitates network management and debugging[1]. SDN provides new techniques to solve long-standing problems in networking like routing by separating the complexity of state distribution from network specification. Despite all the hype surrounding SDNs, exploiting its full potential is demanding. Security is still the major issue and a striking challenge that reduces the growth of SDNs. Moreover the introduction of various architectural components and up cycling of novel entities of SDN poses new security issues and threats. SDN is considered as major target for digital threats and cyber-attacks[2] and have more devastating effects than simple networks. Initial SDN design doesn't considered security as its part; therefore, it must be raised on the agenda. This article discusses the security solutions proposed to secure SDNs. We categorize the security solutions in the article by presenting a thematic taxonomy based on SDN architectural layers/interfaces[3], security measures and goals, simulation framework. Moreover, the literature also points out the possible attacks[2] targeting different layers/interfaces of SDNs. For securing SDNs, the potential requirements and their key enablers are also identified and presented. Also, the articles sketch the design of secure and dependable SDNs. At last, we discuss open issues and challenges of SDN security that may be rated appropriate to be handled by professionals and researchers in the future.

Cybernetic closed loop regulators are used to model socio-technical systems in adversarial contexts. Cybernetic principles regarding these idealized control loops are applied to show how the incompleteness of system models enables system exploitation. We consider abstractions as a case study of model incompleteness, and we characterize the ways that attackers and defenders interact in such a formalism. We end by arguing that the science of security is most like a military science, whose foundations are analytical and generative rather than normative.

Control theory and SDN (Software Defined Networking) are key components for NFV (Network Function Virtualization) deployment. However little has been done to use a control-theoretic approach for SDN and NFV management. In this demo, we describe a use case for NFV management using control theory and SDN. We use the management architecture of RINA (a clean-slate Recursive InterNetwork Architecture) to manage Virtual Network Function (VNF) instances over the GENI testbed. We deploy Snort, an Intrusion Detection System (IDS) as the VNF. Our network topology has source and destination hosts, multiple IDSes, an Open vSwitch (OVS) and an OpenFlow controller. A distributed management application running on RINA measures the state of the VNF instances and communicates this information to a Proportional Integral (PI) controller, which then provides load balancing information to the OpenFlow controller. The latter controller in turn updates traffic flow forwarding rules on the OVS switch, thus balancing load across the VNF instances. This demo demonstrates the benefits of using such a control-theoretic load balancing approach and the RINA management architecture in virtualized environments for NFV management. It also illustrates that the GENI testbed can easily support a wide range of SDN and NFV related experiments.

Industrial Control Systems (ICS) which among others are comprised of Supervisory Control and Data Acquisition (SCADA) and Distributed Control Systems (DCS) are used to control industrial processes. ICS have now been connected to other Information Technology (IT) systems and have as a result become vulnerable to Advanced Persistent Threats (APT). APTs are targeted attacks that use zero-day attacks to attack systems. Current ICS security mechanisms fail to deter APTs from infiltrating ICS. An analysis of possible solutions to deter APTs was done. This paper proposes the use of Artificial Immune Systems to secure ICS from APTs.

The proliferation of digital devices in a networked industrial ecosystem, along with an exponential growth in complexity and scope, has resulted in elevated security concerns and management complexity issues. This paper describes a novel architecture utilizing concepts of autonomic computing and a simple object access protocol (SOAP)-based interface to metadata access points (IF-MAP) external communication layer to create a network security sensor. This approach simplifies integration of legacy software and supports a secure, scalable, and self-managed framework. The contribution of this paper is twofold: 1) A flexible two-level communication layer based on autonomic computing and service oriented architecture is detailed and 2) three complementary modules that dynamically reconfigure in response to a changing environment are presented. One module utilizes clustering and fuzzy logic to monitor traffic for abnormal behavior. Another module passively monitors network traffic and deploys deceptive virtual network hosts. These components of the sensor system were implemented in C++ and PERL and utilize a common internal D-Bus communication mechanism. A proof of concept prototype was deployed on a mixed-use test network showing the possible real-world applicability. In testing, 45 of the 46 network attached devices were recognized and 10 of the 12 emulated devices were created with specific operating system and port configurations. In addition, the anomaly detection algorithm achieved a 99.9% recognition rate. All output from the modules were correctly distributed using the common communication structure.

In the paper a programmable management framework for SDN networks is presented. The concept is in-line with SDN philosophy - it can be programmed from scratch. The implemented management functions can be case dependent. The concept introduces a new node in the SDN architecture, namely the SDN manager. In compliance with the latest trends in network management the approach allows for embedded management of all network nodes and gradual implementation of management functions providing their code lifecycle management as well as the ability to on-the-fly code update. The described concept is a bottom-up approach, which key element is distributed execution environment (PDEE) that is based on well-established technologies like OSGI and FIPA. The described management idea has strong impact on the evolution of the SDN architecture, because the proposed distributed execution environment is a generic one, therefore it can be used not only for the management, but also for distributing of control or application functions.
 

The proliferation of digital devices in a networked industrial ecosystem, along with an exponential growth in complexity and scope, has resulted in elevated security concerns and management complexity issues. This paper describes a novel architecture utilizing concepts of autonomic computing and a simple object access protocol (SOAP)-based interface to metadata access points (IF-MAP) external communication layer to create a network security sensor. This approach simplifies integration of legacy software and supports a secure, scalable, and self-managed framework. The contribution of this paper is twofold: 1) A flexible two-level communication layer based on autonomic computing and service oriented architecture is detailed and 2) three complementary modules that dynamically reconfigure in response to a changing environment are presented. One module utilizes clustering and fuzzy logic to monitor traffic for abnormal behavior. Another module passively monitors network traffic and deploys deceptive virtual network hosts. These components of the sensor system were implemented in C++ and PERL and utilize a common internal D-Bus communication mechanism. A proof of concept prototype was deployed on a mixed-use test network showing the possible real-world applicability. In testing, 45 of the 46 network attached devices were recognized and 10 of the 12 emulated devices were created with specific operating system and port configurations. In addition, the anomaly detection algorithm achieved a 99.9% recognition rate. All output from the modules were correctly distributed using the common communication structure.

The research question of this study is: How Integration Readiness Level (IRL) metrics can be understood and realized in the domain of border control information systems. The study address to the IRL metrics and their definition, criteria, references, and questionnaires for validation of border control information systems in case of the shared maritime situational awareness system. The target of study is in improvements of ways for acceptance, operational validation, risk assessment, and development of sharing mechanisms and integration of information systems and border control information interactions and collaboration concepts in Finnish national and European border control domains.
 

Distributed and parallel applications are critical information technology systems in multiple industries, including academia, military, government, financial, medical, and transportation. These applications present target rich environments for malicious attackers seeking to disrupt the confidentiality, integrity and availability of these systems. Applying the military concept of defense cyber maneuver to these systems can provide protection and defense mechanisms that allow survivability and operational continuity. Understanding the tradeoffs between information systems security and operational performance when applying maneuver principles is of interest to administrators, users, and researchers. To this end, we present a model of a defensive maneuver cyber platform using Stochastic Petri Nets. This model enables the understanding and evaluation of the costs and benefits of maneuverability in a distributed application environment, specifically focusing on moving target defense and deceptive defense strategies.
 

Security is a major challenge preventing wide deployment of the smart grid technology. Typically, the classical power grid is protected with a set of isolated security tools applied to individual grid components and layers ignoring their cross-layer interaction. Such an approach does not address the smart grid security requirements because usually intricate attacks are cross-layer exploiting multiple vulnerabilities at various grid layers and domains. We advance a conceptual layering model of the smart grid and a high-level overview of a security framework, termed CyNetPhy, towards enabling cross-layer security of the smart grid. CyNetPhy tightly integrates and coordinates between three interrelated, and highly cooperative real-time security systems crossing section various layers of the grid cyber and physical domains to simultaneously address the grid's operational and security requirements. In this article, we present in detail the physical security layer (PSL) in CyNetPhy. We describe an attack scenario raising the emerging hardware Trojan threat in process control systems (PCSes) and its novel PSL resolution leveraging the model predictive control principles. Initial simulation results illustrate the feasibility and effectiveness of the PSL.
 

The OpenFlow architecture is a proposal from the Clean Slate initiative to define a new Internet architecture where the network devices are simple, and the control and management plane is performed by a centralized controller. The simplicity and centralization architecture makes it reliable and inexpensive. However, this architecture does not provide mechanisms to detect conflicting in flows, allowing that unreachable flows can be configured in the network elements, and the network may not behave as expected. This paper proposes an approach to conflict detection using first-order logic to define possible antagonisms and employ an inference engine to detect conflicting flows before the OpenFlow controller implement in the network elements.
 

It is expected that clean-slate network designs will be implemented for wide-area network applications. Multi-tenancy in OpenFlow networks is an effective method to supporting a clean-slate network design, because the cost-effectiveness is improved by the sharing of substrate networks. To guarantee the programmability of OpenFlow for tenants, a complete flow space (i.e., header values of the data packets) virtualization is necessary. Wide-area substrate networks typically have multiple administrators. We therefore need to implement a flow space virtualization over multiple administration networks. In existing techniques, a third party is solely responsible for managing the mapping of header values for flow space virtualization for substrate network administrators and tenants, despite the severity of a third party failure. In this paper, we propose an AutoVFlow mechanism that allows flow space virtualization in a wide-area networks without the need for a third party. Substrate network administrators implement a flow space virtualization autonomously. They are responsible for virtualizing a flow space involving switches in their own substrate networks. Using a prototype of AutoVFlow, we measured the virtualization overhead, the results of which show a negligible amount of overhead.
 

This paper presents a survey on cyber security issues in in current industrial automation and control systems, which also includes observations and insights collected and distilled through a series of discussion by some of major Japanese experts in this field. It also tries to provide a conceptual framework of those issues and big pictures of some ongoing projects to try to enhance it.
 

Wireless sensor networks (WSNs) are prone to propagating malware because of special characteristics of sensor nodes. Considering the fact that sensor nodes periodically enter sleep mode to save energy, we develop traditional epidemic theory and construct a malware propagation model consisting of seven states. We formulate differential equations to represent the dynamics between states. We view the decision-making problem between system and malware as an optimal control problem; therefore, we formulate a malware-defense differential game in which the system can dynamically choose its strategies to minimize the overall cost whereas the malware intelligently varies its strategies over time to maximize this cost. We prove the existence of the saddle-point in the game. Further, we attain optimal dynamic strategies for the system and malware, which are bang-bang controls that can be conveniently operated and are suitable for sensor nodes. Experiments identify factors that influence the propagation of malware. We also determine that optimal dynamic strategies can reduce the overall cost to a certain extent and can suppress the malware propagation. These results support a theoretical foundation to limit malware in WSNs.

In this paper we address the problem of designing a fault tolerant control scheme for an HVAC control system where sensing and actuation data are exchanged with a centralized controller via a wireless sensors and actuators network where the communication nodes are subject to permanent failures and malicious intrusions.

This paper deals with the robust H∞ cyber-attacks estimation problem for control systems under stochastic cyber-attacks and disturbances. The focus is on designing a H∞ filter which maximize the attack sensitivity and minimize the effect of disturbances. The design requires not only the disturbance attenuation, but also the residual to remain the attack sensitivity as much as possible while the effect of disturbance is minimized. A stochastic model of control system with stochastic cyber-attacks which satisfy the Markovian stochastic process is constructed. And we also present the stochastic attack models that a control system is possibly exposed to. Furthermore, applying H∞ filtering technique-based on linear matrix inequalities (LMIs), the paper obtains sufficient conditions that ensure the filtering error dynamic is asymptotically stable and satisfies a prescribed ratio between cyber-attack sensitivity and disturbance sensitivity. Finally, the results are applied to the control of a Quadruple-tank process (QTP) under a stochastic cyber-attack and a stochastic disturbance. The simulation results underline that the designed filters is effective and feasible in practical application.

The security of Smart Grid, being one of the very important aspects of the Smart Grid system, is studied in this paper. We first discuss different pitfalls in the security of the Smart Grid system considering the communication infrastructure among the sensors, actuators, and control systems. Following that, we derive a mathematical model of the system and propose a robust security framework for power grid. To effectively estimate the variables of a wide range of state processes in the model, we adopt Kalman Filter in the framework. The Kalman Filter estimates and system readings are then fed into the χ2-square detectors and the proposed Euclidean detectors, which can detect various attacks and faults in the power system including False Data Injection Attacks. The χ2-detector is a proven-effective exploratory method used with Kalman Filter for the measurement of the relationship between dependent variables and a series of predictor variables. The χ2-detector can detect system faults/attacks such as replay and DoS attacks. However, the study shows that the χ2-detector detectors are unable to detect statistically derived False Data Injection Attacks while the Euclidean distance metrics can identify such sophisticated injection attacks.