Biblio

Wearable Internet-of-Things (WIoT) environments have demonstrated great potential in a broad range of applications in healthcare and well-being. Security is essential for WIoT environments. Lack of security in WIoTs not only harms user privacy, but may also harm the user's safety. Though devices in the WIoT can be attacked in many ways, in this paper we focus on adversaries who mount what we call sensor-hijacking attacks, which prevent the constituent medical devices from accurately collecting and reporting the user's health state (e.g., reporting old or wrong physiological measurements). In this paper we outline some of our experiences in implementing a data-driven security solution for detecting sensor-hijacking attack on a secure wearable internet-of-things (WIoT) base station called the Amulet. Given the limited capabilities (computation, memory, battery power) of the Amulet platform, implementing such a security solution is quite challenging and presents several trade-offs with respect to detection accuracy and resources requirements. We conclude the paper with a list of insights into what capabilities constrained WIoT platforms should provide developers so as to make the inclusion of data-driven security primitives in such systems.

In recent years a wide range of wearable IoT healthcare applications have been developed and deployed. The rapid increase in wearable devices allows the transfer of patient personal information between different devices, at the same time personal health and wellness information of patients can be tracked and attacked. There are many techniques that are used for protecting patient information in medical and wearable devices. In this research a comparative study of the complexity for cyber security architecture and its application in IoT healthcare industry has been carried out. The objective of the study is for protecting healthcare industry from cyber attacks focusing on IoT based healthcare devices. The design has been implemented on Xilinx Zynq-7000, targeting XC7Z030 - 3fbg676 FPGA device.

In the Internet of Things (IoT), smart devices are connected using various communication protocols, such as Wi-Fi, ZigBee. Some IoT devices have multiple built-in communication modules. If an IoT device equipped with multiple communication protocols is compromised by an attacker using one communication protocol (e.g., Wi-Fi), it can be exploited as an entry point to the IoT network. Another protocol (e.g., ZigBee) of this IoT device could be used to exploit vulnerabilities of other IoT devices using the same communication protocol. In order to find potential attacks caused by this kind of cross-protocol devices, we group IoT devices based on their communication protocols and construct a graphical security model for each group of devices using the same communication protocol. We combine the security models via the cross-protocol devices and compute hidden attack paths traversing different groups of devices. We use two use cases in the smart home scenario to demonstrate our approach and discuss some feasible countermeasures.

Identity-Based Encryption (IBE) was introduced as an elegant concept for secure data exchange due to its simplified key management by specifically addressing the asymmetric key distribution problems in multi-user scenarios. In the context of ad-hoc network connections that are of particular importance in the emerging Internet of Things, the simple key discovery procedures as provided by IBE are very beneficial in many situations. In this work we demonstrate for the first time that IBE has become practical even for a range of embedded devices that are populated with low-cost ARM Cortex-M microcontrollers or reconfigurable hardware components. More precisely, we adopt the IBE scheme proposed by Ducas et al. at ASIACRYPT 2014 based on the RLWE problem for which we provide implementation results for two security levels on the aforementioned embedded platforms. We give evidence that the implementations of the basic scheme are efficient, as for a security level of 80 bits it requires 103 ms and 36 ms for encryption and decryption, respectively, on the smallest ARM Cortex-M0 microcontroller.

Internet of Thing (IoT) provide services by linking the different platform devices. They have the limitation in providing intelligent service. The IoT devices are heterogeneous which includes wireless sensors to less resource constrained devices. These devices are prone to hardware/software and network attacks. If not properly secured, it may lead to security issues like privacy and confidentiality. To resolve the above problem, an Intelligent Security Framework for IoT Devices is proposed in this paper. The proposed method is made up of (1) the light weight Asymmetric cryptography for securing the End-To-End devices which protects the IoT service gateway and the low power sensor nodes and (2) implements Lattice-based cryptography for securing the Broker devices/Gateway and the cloud services. The proposed architecture implements Asymmetric Key Encryption to share session key between the nodes and then uses this session key for message transfer This protects the system from Distributed Denial of Service Attacks, eavesdropping and Quantum algorithm attacks. The proposed protocol uses the unique Device ID of the sensors to generate key pair to establish mutual authentication between Devices and Services. Finally, the Mutual authentication mechanism is implemented in the gateway.

Cloud services are widely used to virtualize the management and actuation of the real-world the Internet of Things (IoT). Due to the increasing privacy concerns regarding querying untrusted cloud servers, query anonymity has become a critical issue to all the stakeholders which are related to assessment of the dependability and security of the IoT system. The paper presents our study on the problem of query receiver-anonymity in the cloud-based IoT system, where the trade-off between the offered query-anonymity and the incurred communication is considered. The paper will investigate whether the accepted worst-case communication cost is sufficient to achieve a specific query anonymity or not. By way of extensive theoretical analysis, it shows that the bounds of worst-case communication cost is quadratically increased as the offered level of anonymity is increased, and they are quadratic in the network diameter for the opposite range. Extensive simulation is conducted to verify the analytical assertions.

Internet-of-Things devices often collect and transmit sensitive information like camera footage, health monitoring data, or whether someone is home. These devices protect data in transit with end-to-end encryption, typically using TLS connections between devices and associated cloud services. But these TLS connections also prevent device owners from observing what their own devices are saying about them. Unlike in traditional Internet applications, where the end user controls one end of a connection (e.g., their web browser) and can observe its communication, Internet-of-Things vendors typically control the software in both the device and the cloud. As a result, owners have no way to audit the behavior of their own devices, leaving them little choice but to hope that these devices are transmitting only what they should. This paper presents TLS–Rotate and Release (TLS-RaR), a system that allows device owners (e.g., consumers, security researchers, and consumer watchdogs) to authorize devices, called auditors, to decrypt and verify recent TLS traffic without compromising future traffic. Unlike prior work, TLS-RaR requires no changes to TLS's wire format or cipher suites, and it allows the device's owner to conduct a surprise inspection of recent traffic, without prior notice to the device that its communications will be audited.

The Information Centric Networking (ICN) is a novel concept of a large scale ecosystem of wireless actuators and computing technologies. ICN technologies are getting popular in the development of various applications to bring day-to-day comfort and ease in human life. The e-healthcare monitoring services is a subset of ICN services which has been utilized to monitor patient's health condition in a smart and ubiquitous way. However, there are several challenges and attacks on ICN. In this paper we have discussed ICN attacks and ICN based healthcare scenario. We have proposed a novel ICN stack for healthcare scenario for securing biomedical data communication instead of communication networks. However, the biomedical data communication between patient and Doctor requires reliable and secure networks for the global access.

Smart Internet of Things (IoT) applications will rely on advanced IoT platforms that not only provide access to IoT sensors and actuators, but also provide access to cloud services and data analytics. Future IoT platforms should thus provide connectivity and intelligence. One approach to connecting IoT devices, IoT networks to cloud networks and services is to use network federation mechanisms over the internet to create network slices across heterogeneous platforms. Network slices also need to be protected from potential external and internal threats. In this paper we describe an approach for enforcing global security policies in the federated cloud and IoT networks. Our approach allows a global security to be defined in the form of a single service manifest and enforced across all federation network segments. It relies on network function virtualisation (NFV) and service function chaining (SFC) to enforce the security policy. The approach is illustrated with two case studies: one for a user that wishes to securely access IoT devices and another in which an IoT infrastructure administrator wishes to securely access some remote cloud and data analytics services.

Internet of Things (IoT) devices are resource constrained devices in terms of power, memory, bandwidth, and processing. On the other hand, multicast communication is considered more efficient in group oriented applications compared to unicast communication as transmission takes place using fewer resources. That is why many of IoT applications rely on multicast in their transmission. This multicast traffic need to be secured specially for critical applications involving actuators control. Securing multicast traffic by itself is cumbersome as it requires an efficient and scalable Group Key Management (GKM) protocol. In case of IoT, the situation is more difficult because of the dynamic nature of IoT scenarios. This paper introduces a solution based on using context aware security server accompanied with a group of key servers to efficiently distribute group encryption keys to IoT devices in order to secure the multicast sessions. The proposed solution is evaluated relative to the Logical Key Hierarchy (LKH) protocol. The comparison shows that the proposed scheme efficiently reduces the load on the key servers. Moreover, the key storage cost on both members and key servers is reduced.

The Internet Protocol version 6 (IPv6) over Low Power Wireless Personal Area Networks (6LoWPAN), which is a promising technology to promote the development of the Internet of Things (IoT), has been proposed to connect millions of IP-based sensing devices over the open Internet. To support the mobility of these resource constrained sensing nodes, the Proxy Mobile IPv6 (PMIPv6) has been proposed as the standard. Although the standard has specified some issues of security and mobility in 6LoWPANs, the issues of supporting secure group handovers have not been addressed much by the current existing solutions. In this paper, to reduce the handover latency and signaling cost, an efficient and secure group mobility scheme is designed to support seamless handovers for a group of resource constrained 6LoWPAN devices. With the consideration of the devices holding limited energy capacities, only simple hash and symmetric encryption method is used. The security analysis and the performance evaluation results show that the proposed 6LoWPAN group handover scheme could not only enhance the security functionalities but also support fast authentication for handovers.

The Internet of Things leads to the inter-connectivity of a wide range of devices. This heterogeneity of hardware and software poses significant challenges to security. Constrained IoT devices often do not have enough resources to carry the overhead of an intrusion protection system or complex security protocols. A typical initial step in network security is a network scan in order to find vulnerable nodes. In the context of IoT, the initiator of the scan can be particularly interested in finding constrained devices, assuming that they are easier targets. In IoT networks hosting devices of various types, performing a scan with a high discovery rate can be a challenging task, since low-power networks such as IEEE 802.15.4 are easily overloaded. In this paper, we propose an approach to increase the efficiency of network scans by combining them with active network measurements. The measurements allow the scanner to differentiate IoT nodes by the used network technology. We show that the knowledge gained from this differentiation can be used to control the scan strategy in order to reduce probe losses.

Internet Protocol version 6 (IPv6) over Low power Wireless Personal Area Networks (6LoWPAN) is extensively used in wireless sensor networks (WSNs) due to its ability to transmit IPv6 packet with low bandwidth and limited resources. 6LoWPAN has several operations in each layer. Most existing security challenges are focused on the network layer, which is represented by its routing protocol for low-power and lossy network (RPL). RPL components include WSN nodes that have constrained resources. Therefore, the exposure of RPL to various attacks may lead to network damage. A sinkhole attack is a routing attack that could affect the network topology. This paper aims to investigate the existing detection mechanisms used in detecting sinkhole attack on RPL-based networks. This work categorizes and presents each mechanism according to certain aspects. Then, their advantages and drawbacks with regard to resource consumption and false positive rate are discussed and compared.

This paper addresses the need for standard communication protocols for IoT devices with limited power and computational capabilities. The world is rapidly changing with the proliferation and deployment of IoT devices. This will bring in new communication challenges as these devices are connected to Internet and need to communicate with each other in real time. The paper provides an overview of IoT system architecture and the forthcoming challenges it will bring. There is an urging need to establish standards for communication in the IoT world. With the recent development of new protocols like CoAP, 6LowPAN, IEEE 802.15.4 and Thread in different layers of OSI model, additional challenges also present themselves. Performance and data management is becoming more critical than ever before due to the complexity of connecting raging number of IoT devices. The performance of the systems dealing with IoT devices will require appropriate capacity planning the associated development of data centers. Finally, the paper also presents some reasonable approaches to address the above issues in the IoT world.

6L0WPAN is a communication protocol for Internet of Things. 6LoWPAN is IPv6 protocol modified for low power and lossy personal area networks. 6LoWPAN inherits threats from its predecessors IPv4 and IPv6. IP spoofing is a known attack prevalent in IPv4 and IPv6 networks but there are new vulnerabilities which creates new paths, leading to the attack. This study performs the experimental study to check the feasibility of performing IP spoofing attack on 6LoWPAN Network. Intruder misuses 6LoWPAN control messages which results into wrong IPv6-MAC binding in router. Attack is also simulated in cooja simulator. Simulated results are analyzed for finding cost to the attacker in terms of energy and memory consumption.

The 6L0WPAN adaptation layer is widely used in many Internet of Things (IoT) and vehicular networking applications. The current IoT framework [1], which introduced 6LoWPAN to the TCP/IP model, does not specif the implementation for managing its received-fragments buffer. This paper looks into the effect of current implementations of buffer management strategies at 6LoWPAN's response in case of fragmentation-based, buffer reservation Denial of Service (DoS) attacks. The Packet Drop Rate (PDR) is used to analyze how successful the attacker is for each management technique. Our investigation uses different defence strategies, which include our implementation of the Split Buffer mechanism [2] and a modified version of this mechanism that we devise in this paper as well. In particular, we introduce dynamic calculation for the average time between consecutive fragments and the use of a list of previously dropped packets tags. NS3 is used to simulate all the implementations. Our results show that using a ``slotted'' buffer would enhance 6LoWPAN's response against these attacks. The simulations also provide an in-depth look at using scoring systems to manage buffer cleanups.

The Bonseyes EU H2020 collaborative project aims to develop a platform consisting of a Data Marketplace, a Deep Learning Toolbox, and Developer Reference Platforms for organizations wanting to adopt Artificial Intelligence. The project will be focused on using artificial intelligence in low power Internet of Things (IoT) devices ("edge computing"), embedded computing systems, and data center servers ("cloud computing"). It will bring about orders of magnitude improvements in efficiency, performance, reliability, security, and productivity in the design and programming of systems of artificial intelligence that incorporate Smart Cyber-Physical Systems (CPS). In addition, it will solve a causality problem for organizations who lack access to Data and Models. Its open software architecture will facilitate adoption of the whole concept on a wider scale. To evaluate the effectiveness, technical feasibility, and to quantify the real-world improvements in efficiency, security, performance, effort and cost of adding AI to products and services using the Bonseyes platform, four complementary demonstrators will be built. Bonseyes platform capabilities are aimed at being aligned with the European FI-PPP activities and take advantage of its flagship project FIWARE. This paper provides a description of the project motivation, goals and preliminary work.

In recent years, the emerging Internet-of-Things (IoT) has led to rising concerns about the security of networked embedded devices. In this work, we propose the SIPHON architecture–-a Scalable high-Interaction Honeypot platform for IoT devices. Our architecture leverages IoT devices that are physically at one location and are connected to the Internet through so-called $\backslash$emph\wormholes\ distributed around the world. The resulting architecture allows exposing few physical devices over a large number of geographically distributed IP addresses. We demonstrate the proposed architecture in a large scale experiment with 39 wormhole instances in 16 cities in 9 countries. Based on this setup, five physical IP cameras, one NVR and one IP printer are presented as 85 real IoT devices on the Internet, attracting a daily traffic of 700MB for a period of two months. A preliminary analysis of the collected traffic indicates that devices in some cities attracted significantly more traffic than others (ranging from 600 000 incoming TCP connections for the most popular destination to less than 50 000 for the least popular). We recorded over 400 brute-force login attempts to the web-interface of our devices using a total of 1826 distinct credentials, from which 11 attempts were successful. Moreover, we noted login attempts to Telnet and SSH ports some of which used credentials found in the recently disclosed Mirai malware.

The application of mobile Wireless Sensor Networks (WSNs) with a big amount of participants poses many challenges. For instance, high transmission loss rates which are caused i.a. by collisions might occur. Additionally, WSNs frequently operate under harsh conditions, where a high probability of link or node failures is inherently given. This leads to reliable data maintenance being a key issue. Existing approaches which were developed to keep data dependably in WSNs often either perform well in highly dynamic or in completely static scenarios, or require complex calculations. Herein, we present the Network Coding based Multicast Growth Codes (MCGC), which represent a solution for reliable data maintenance in large-scale WSNs. MCGC are able to tolerate high fault rates and reconstruct more originally collected data in a shorter period of time than compared existing approaches. Simulation results show performance improvements of up to 75% in comparison to Growth Codes (GC). These results are achieved independently of the systems' dynamics and despite of high fault probabilities.

Blockchain, the underlying technology of cryptocurrency networks like Bitcoin, can prove to be essential towards realizing the vision of a decentralized, secure, and open Internet of Things (IoT) revolution. There is a growing interest in many research groups towards leveraging blockchains to provide IoT data privacy without the need for a centralized data access model. This paper aims to propose a decentralized access model for IoT data, using a network architecture that we call a modular consortium architecture for IoT and blockchains. The proposed architecture facilitates IoT communications on top of a software stack of blockchains and peer-to-peer data storage mechanisms. The architecture is aimed to have privacy built into it, and to be adaptable for various IoT use cases. To understand the feasibility and deployment considerations for implementing the proposed architecture, we conduct performance analysis of existing blockchain development platforms, Ethereum and Monax.

Besides its enormous benefits to the industry and community the Internet of Things (IoT) has introduced unique security challenges to its enablers and adopters. As the trend in cybersecurity threats continue to grow, it is likely to influence IoT deployments. Therefore it is eminent that besides strengthening the security of IoT systems we develop effective digital forensics techniques that when breaches occur we can track the sources of attacks and bring perpetrators to the due process with reliable digital evidence. The biggest challenge in this regard is the heterogeneous nature of devices in IoT systems and lack of unified standards. In this paper we investigate digital forensics from IoT perspectives. We argue that besides traditional digital forensics practices it is important to have application-specific forensics in place to ensure collection of evidence in context of specific IoT applications. We consider top three IoT applications and introduce a model which deals with not just traditional forensics but is applicable in digital as well as application-specific forensics process. We believe that the proposed model will enable collection, examination, analysis and reporting of forensically sound evidence in an IoT application-specific digital forensics investigation.

The majority of business activity of our integrated and connected world takes place in networks based on cloud computing infrastructure that cross national, geographic and jurisdictional boundaries. Such an efficient entity interconnection is made possible through an emerging networking paradigm, Software Defined Networking (SDN) that intends to vastly simplify policy enforcement and network reconfiguration in a dynamic manner. However, despite the obvious advantages this novel networking paradigm introduces, its increased attack surface compared to traditional networking deployments proved to be a thorny issue that creates skepticism when safety-critical applications are considered. Especially when SDN is used to support Internet-of-Things (IoT)-related networking elements, additional security concerns rise, due to the elevated vulnerability of such deployments to specific types of attacks and the necessity of inter-cloud communication any IoT application would require. The overall number of connected nodes makes the efficient monitoring of all entities a real challenge, that must be tackled to prevent system degradation and service outage. This position paper provides an overview of common security issues of SDN when linked to IoT clouds, describes the design principals of the recently introduced Blockchain paradigm and advocates the reasons that render Blockchain as a significant security factor for solutions where SDN and IoT are involved.

The majority of business activity of our integrated and connected world takes place in networks based on cloud computing infrastructure that cross national, geographic and jurisdictional boundaries. Such an efficient entity interconnection is made possible through an emerging networking paradigm, Software Defined Networking (SDN) that intends to vastly simplify policy enforcement and network reconfiguration in a dynamic manner. However, despite the obvious advantages this novel networking paradigm introduces, its increased attack surface compared to traditional networking deployments proved to be a thorny issue that creates skepticism when safety-critical applications are considered. Especially when SDN is used to support Internet-of-Things (IoT)-related networking elements, additional security concerns rise, due to the elevated vulnerability of such deployments to specific types of attacks and the necessity of inter-cloud communication any IoT application would require. The overall number of connected nodes makes the efficient monitoring of all entities a real challenge, that must be tackled to prevent system degradation and service outage. This position paper provides an overview of common security issues of SDN when linked to IoT clouds, describes the design principals of the recently introduced Blockchain paradigm and advocates the reasons that render Blockchain as a significant security factor for solutions where SDN and IoT are involved.

The article issue is the enterprise information protection within the internet of things concept. The aim of research is to develop arrangements set to ensure secure enterprise IPv6 network operating. The object of research is the enterprise IPv6 network. The subject of research is modern switching equipment as a tool to ensure network protection. The research task is to prioritize functioning of switches in production and corporation enterprise networks, to develop a network host protection algorithm, to test the developed algorithm on the Cisco Packet Tracer 7 software emulator. The result of research is the proposed approach to IPv6-network security based on analysis of modern switches functionality, developed and tested enterprise network host protection algorithm under IPv6-protocol with an automated network SLAAC-configuration control, a set of arrangements for resisting default enterprise gateway attacks, using ACL, VLAN, SEND, RA Guard security technology, which allows creating sufficiently high level of networks security.

RPL is a lightweight IPv6 network routing protocol specifically designed by IETF, which can make full use of the energy of intelligent devices and compute the resource to build the flexible topological structure. This paper analyzes the security problems of RPL, sets up a test network to test RPL network security, proposes a RPL based security routing protocol M-RPL. The routing protocol establishes a hierarchical clustering network topology, the intelligent device of the network establishes the backup path in different clusters during the route discovery phase, enable backup paths to ensure data routing when a network is compromised. Setting up a test prototype network, simulating some attacks against the routing protocols in the network. The test results show that the M-RPL network can effectively resist the routing attacks. M-RPL provides a solution to ensure the Internet of Things (IoT) security.