E-DPNCT: an enhanced attack resilient differential privacy model for smart grids using split noise cancellation.

High frequency reporting of energy consumption data in smart grids can be used to infer sensitive information regarding the consumer's life style and poses serious security and privacy threats. Differential privacy (DP) based privacy models for smart grids ensure privacy when analysing energy consumption data for billing and load monitoring. However, DP models for smart grids are vulnerable to collusion attack where an adversary colludes with malicious smart meters and un-trusted aggregator in order to get private information from other smart meters. We first show the vulnerability of DP based privacy model for smart grids against collusion attacks to establish the need of a collusion resistant privacy model. Then, we propose an Enhanced Differential Private Noise Cancellation Model for Load Monitoring and Billing for Smart Meters (E-DPNCT) which not only provides resistance against collusion attacks but also protects the privacy of the smart grid data while providing accurate billing and load monitoring. We use differential privacy with a split noise cancellation protocol with multiple master smart meters (MSMs) to achieve collusion resistance. We propose an Enhanced Differential Private Noise Cancellation Model for Load Monitoring and Billing for Smart Meters (E-DPNCT) to protect the privacy of the smart grid data using a split noise cancellation protocol with multiple master smart meters (MSMs) to provide accurate billing and load monitoring and resistance against collusion attacks. We did extensive comparison of our E-DPNCT model with state of the art attack resistant privacy preserving models such as EPIC for collusion attack. We simulate our E-DPNCT model with real time data which shows significant improvement in privacy attack scenarios. Further, we analyze the impact of selecting different sensitivity parameters for calibrating DP noise over the privacy of customer electricity profile and accuracy of electricity data aggregation such as load monitoring and billing.

Ethical Dilemmas and Privacy Issues in Emerging Technologies: A Review.

Industry 5.0 is projected to be an exemplary improvement in digital transformation allowing for mass customization and production efficiencies using emerging technologies such as universal machines, autonomous and self-driving robots, self-healing networks, cloud data analytics, etc., to supersede the limitations of Industry 4.0. To successfully pave the way for acceptance of these technologies, we must be bound and adhere to ethical and regulatory standards. Presently, with ethical standards still under development, and each region following a different set of standards and policies, the complexity of being compliant increases. Having vague and inconsistent ethical guidelines leaves potential gray areas leading to privacy, ethical, and data breaches that must be resolved. This paper examines the ethical dimensions and dilemmas associated with emerging technologies and provides potential methods to mitigate their legal/regulatory issues.

The Stream Exchange Protocol: A Secure and Lightweight Tool for Decentralized Connection Establishment.

With the growing availability and prevalence of internet-capable devices, the complexity of networks and associated connection management increases. Depending on the use case, different approaches in handling connectivity have emerged over the years, tackling diverse challenges in each distinct area. Exposing centralized web-services facilitates reachability; distributing information in a peer-to-peer fashion offers availability; and segregating virtual private sub-networks promotes confidentiality. A common challenge herein lies in connection establishment, particularly in discovering, and securely connecting to peers. However, unifying different aspects, including the usability, scalability, and security of this process in a single framework, remains a challenge. In this paper, we present the Stream Exchange Protocol (SEP) collection, which provides a set of building blocks for secure, lightweight, and decentralized connection establishment. These building blocks use unique identities that enable both the identification and authentication of single communication partners. By utilizing federated directories as decentralized databases, peers are able to reliably share authentic data, such as current network locations and available endpoints. Overall, this collection of building blocks is universally applicable, easy to use, and protected by state-of-the-art security mechanisms by design. We demonstrate the capabilities and versatility of the SEP collection by providing three tools that utilize our building blocks: a decentralized file sharing application, a point-to-point network tunnel using the SEP trust model, and an application that utilizes our decentralized discovery mechanism for authentic and asynchronous data distribution.

Industrial IoT, Cyber Threats, and Standards Landscape: Evaluation and Roadmap.

Industrial IoT (IIoT) is a novel concept of a fully connected, transparent, automated, and intelligent factory setup improving manufacturing processes and efficiency. To achieve this, existing hierarchical models must transition to a fully connected vertical model. Since IIoT is a novel approach, the environment is susceptible to cyber threat vectors, standardization, and interoperability issues, bridging the gaps at the IT/OT ICS (industrial control systems) level. IIoT M2M communication relies on new communication models (5G, TSN ethernet, self-driving networks, etc.) and technologies which require challenging approaches to achieve the desired levels of data security. Currently there are no methods to assess the vulnerabilities/risk impact which may be exploited by malicious actors through system gaps left due to improper implementation of security standards. The authors are currently working on an Industry 4.0 cybersecurity project and the insights provided in this paper are derived from the project. This research enables an understanding of converged/hybrid cybersecurity standards, reviews the best practices, and provides a roadmap for identifying, aligning, mapping, converging, and implementing the right cybersecurity standards and strategies for securing M2M communications in the IIoT.

Real-Time Secure/Unsecure Video Latency Measurement/Analysis with FPGA-Based Bump-in-the-Wire Security.

With the growth of the internet of things (IoT), many challenges like information security and privacy, interoperability/standard, and regulatory and legal issues are arising. This work focused on the information security issue, which is one of the primary challenges faced by connected systems that needs to be resolved without impairing system behaviour. Information, which is made available on the Internet by the things, varies from insensitive information (e.g., readings from outdoor temperature sensors) to extremely sensitive information (e.g., video stream from a camera) and needs to be secured over the Internet. Things which utilise cameras as a source of information pertain to a subclass of the IoT called IoVT (internet of video things). This paper presents secured and unsecured video latency measurement results over the Internet for a marine ROV (remotely operated vehicle). A LabVIEW field programmable gate arrays (FPGAs)-based bump-in-the-wire (BITW) secure core is used to provide an AES (advanced encryption standard)-enabled security feature on the video stream of an IoVT node (ROV equipped with a live-feed camera). The designed LabVIEW-based software architecture provides an option to enable/disable the AES encryption for the video transmission. The latency effects of embedding encryption on the stream with real-time constraints are measured and presented. It is found that the encryption mechanism used does not greatly influence the video feedback performance of the observed IoVT node, which is critical for real-time secure video communication for ROV remote control and piloting. The video latency measurement results are taken using 128, 256 and 512 bytes block lengths of AES for both H.264 and MJPEG encoding schemes transmitted over both TCP and UDP transmission protocols. The latency measurement is performed in two scenarios (i.e., with matching equipment and different equipment on either end of the transmission).

Underwater Depth and Temperature Sensing Based on Fiber Optic Technology for Marine and Fresh Water Applications.

Oceanic conditions play an important role in determining the effects of climate change and these effects can be monitored through the changes in the physical properties of sea water. In fact, Oceanographers use various probes for measuring the properties within the water column. CTDs (Conductivity, Temperature and Depth) provide profiles of physical and chemical parameters of the water column. A CTD device consists of Conductivity (C), Temperature (T) and Depth (D) probes to monitor the water column changes with respect to relative depth. An optical fibre-based point sensor used as a combined pressure (depth) and temperature sensor and the sensor system are described. Measurements accruing from underwater trials of a miniature sensor for pressure (depth) and temperature in the ocean and in fresh water are reported. The sensor exhibits excellent stability and its performance is shown to be comparable with the Sea-Bird Scientific commercial sensor: SBE9Plus.

An Experimental Study of the Effects of External Physiological Parameters on the Photoplethysmography Signals in the Context of Local Blood Pressure (Hydrostatic Pressure Changes).

A comprehensive study of the effect of a wide range of controlled human subject motion on Photoplethysmographic signals is reported. The investigation includes testing of two separate groups of 5 and 18 subjects who were asked to undertake set exercises whilst simultaneously monitoring a wide range of physiological parameters including Breathing Rate, Heart Rate and Localised Blood Pressure using commercial clinical sensing systems. The unique finger mounted PPG probe equipped with miniature three axis accelerometers for undertaking this investigation was a purpose built in-house version which is designed to facilitate reproducible application to a wide range of human subjects and the study of motion. The subjects were required to undertake several motion based exercises including standing, sitting and lying down and transitions between these states. They were also required to undertake set arm movements including arm-swinging and wrist rotation. A comprehensive set of experimental results corresponding to all motion inducing exercises have been recorded and analysed including the baseline (BL) value (DC component) and the amplitude of the oscillation of the PPG. All physiological parameters were also recorded as a simultaneous time varying waveform. The effects of the motion and specifically the localised Blood Pressure (BP) have been studied and related to possible influences of the Autonomic Nervous System (ANS) and hemodynamic pressure variations. It is envisaged that a comprehensive study of the effect of motion and the localised pressure fluctuations will provide valuable information for the future minimisation of motion artefact effect on the PPG signals of this probe and allow the accurate assessment of total haemoglobin concentration which is the primary function of the probe.

An Optical Fibre Depth (Pressure) Sensor for Remote Operated Vehicles in Underwater Applications.

A miniature sensor for accurate measurement of pressure (depth) with temperature compensation in the ocean environment is described. The sensor is based on an optical fibre Extrinsic Fabry-Perot interferometer (EFPI) combined with a Fibre Bragg Grating (FBG). The EFPI provides pressure measurements while the Fibre Bragg Grating (FBG) provides temperature measurements. The sensor is mechanically robust, corrosion-resistant and suitable for use in underwater applications. The combined pressure and temperature sensor system was mounted on-board a mini remotely operated underwater vehicle (ROV) in order to monitor the pressure changes at various depths. The reflected optical spectrum from the sensor was monitored online and a pressure or temperature change caused a corresponding observable shift in the received optical spectrum. The sensor exhibited excellent stability when measured over a 2 h period underwater and its performance is compared with a commercially available reference sensor also mounted on the ROV. The measurements illustrates that the EFPI/FBG sensor is more accurate for depth measurements (depth of ~0.020 m).

Secure and Efficient Key Coordination Algorithm for Line Topology Network Maintenance for Use in Maritime Wireless Sensor Networks.

There has been a significant increase in the proliferation and implementation of Wireless Sensor Networks (WSNs) in different disciplines, including the monitoring of maritime environments, healthcare systems, and industrial sectors. It has now become critical to address the security issues of data communication while considering sensor node constraints. There are many proposed schemes, including the scheme being proposed in this paper, to ensure that there is a high level of security in WSNs. This paper presents a symmetric security scheme for a maritime coastal environment monitoring WSN. The scheme provides security for travelling packets via individually encrypted links between authenticated neighbors, thus avoiding a reiteration of a global rekeying process. Furthermore, this scheme proposes a dynamic update key based on a trusted node configuration, called a leader node, which works as a trusted third party. The technique has been implemented in real time on a Waspmote test bed sensor platform and the results from both field testing and indoor bench testing environments are discussed in this paper.

Defence against Black Hole and Selective Forwarding Attacks for Medical WSNs in the IoT.

Wireless sensor networks (WSNs) are being used to facilitate monitoring of patients in hospital and home environments. These systems consist of a variety of different components/sensors and many processes like clustering, routing, security, and self-organization. Routing is necessary for medical-based WSNs because it allows remote data delivery and it facilitates network scalability in large hospitals. However, routing entails several problems, mainly due to the open nature of wireless networks, and these need to be addressed. This paper looks at two of the problems that arise due to wireless routing between the nodes and access points of a medical WSN (for IoT use): black hole and selective forwarding (SF) attacks. A solution to the former can readily be provided through the use of cryptographic hashes, while the latter makes use of a neighbourhood watch and threshold-based analysis to detect and correct SF attacks. The scheme proposed here is capable of detecting a selective forwarding attack with over 96% accuracy and successfully identifying the malicious node with 83% accuracy.