Cyber-physical systems (CPS) is a setup that controls and monitors the physical world around us. The advancement of these systems needs to incorporate an unequivocal spotlight on making these systems efficient. Blockchains and their inherent combination of consensus algorithms, distributed data storage, and secure protocols can be utilized to build robustness and reliability in these systems. Blockchain is the underlying technology behind bitcoins and it provides a decentralized framework to validate transactions and ensure that they cannot be modified. By distributing the role of information validation across the network peers, blockchain eliminates the risks associated with a centralized architecture. It is the most secure validation mechanism that is efficient and enables the provision of financial services, thereby giving users more freedom and power. This upcoming technology provides internet users with the capability to create value and authenticate digital information. It has the capability to revolutionize a diverse set of business applications, ranging from sharing economy to data management and prediction markets. In this paper, we present a holistic survey of various applications of CPS where blockchain has been utilized. Smart grids, health-care systems, and industrial production processes are some of the many applications that can benefit from the blockchain technology and will be discussed in the paper.

https://www.mdpi.com/1424-8220/20/1/282/pdf

A Survey of Blockchain Enabled Cyber-Physical Systems

In a general aspect, motion is detected based on wireless signals. In some aspects, a modulation type of a first signal is identified at a motion detector device. The first signal is based on a wireless signal transmitted through a space by a transmitter device and received by the motion detector device. A demodulator at the motion detector device generates a second signal from the first signal by demodulating the first signal according to the identified modulation type. A modulator at the motion detector device generates a third signal from the second signal by modulating the second signal according to the identified modulation type. A channel response is generated based on the first signal and the third signal. The channel response is used to detect motion of an object in the space.

Detecting signal modulation for motion detection

In a general aspect, a filter time aligns time varying RF-motion data. In some aspects, a method includes loading a first set of input signals (SISs) into an interference buffer over a first time period. The first SISs is based on a first set of wireless signals received by a wireless communication device (WCD) after being transmitted through a space. The method includes using the first SISs to determine an interference level. The method includes: in response to determining the interference level is below a threshold, executing a motion detection process in a second, subsequent time period over which a second SISs is loaded into the interference buffer. The motion detection process, using a subset of the first SISs, detects motion of an object in the space. The second SISs are based on a second set of wireless signals received by the WCD after being transmitted through the space.

Time-alignment of motion detection signals using buffers

Vehicular networks are considered as one of the most pertinent research topics in intelligent transportation systems and anchors for future smart city environment due to the ability to provide road safety and precautionary measures for the drivers and passengers. Due to the characteristics of vehicular networks, security, privacy, and trust management are challenging issues. Blockchain is an emerging decentralized and distributed computing platform that facilitates recording and tracking resources without the need for the centralized trusted authority. Therefore, the potential for security improvements in vehicular networks is enormous. The paper aims to review, classify, and discuss a range of the proposed models in blockchain-based vehicular networks. We presented summary comparisons of the available models with their main features and objectives regarding security, privacy preservation, and trust management. To the best of our knowledge, this is the first paper that provides a survey on blockchain-based solutions for security services’ improvements in vehicular networks.

Blockchain-based solutions for security, privacy, and trust management in vehicular networks: a survey

In a general aspect, the radio state of a wireless communication device is controlled. In some aspects, a first set of motion detection signals is processed by operation of a radio subsystem of a wireless communication device in a first radio state. An amount of variation in the first set of motion detection signals is determined based on values of a parameter of the motion detection signals. A counter is updated in response to a determination that the variation is greater than a first threshold, and the radio subsystem is changed to a second radio state based on comparing the value of the counter with a second threshold. A motion detection process is executed to detect motion of an object in the space based on a second set of motion detection signals processed by operation of the radio subsystem in the second radio state.

Controlling radio states for motion detection

A system and method for classifying an input signal suspected of being a wireless LAN signal. Bursts are isolated based on an analysis of an average power signal that is derived from the input signal. A correlation-based test is performed to determine if the input signal contains a Barker code typical of DSSS transmissions. Another correlation-based test is performed to determine of the input signal contains a long training sequence typical of OFDM transmissions. The results of the two tests are used to classify the input signal as being DSSS, OFDM or neither.

Classification of Wireless LAN Signals

Spectrum sensing in cognitive radio networks and metacognition for dynamic spectrum sharing between radar and communication system: A review

Connected vehicles are designed to make informed safety-related decisions based on data/information they receive from various on-board sensors and other vehicles in the vicinity. However, attacks directed towards on-board sensors and network attacks on the wireless communication channels can adversely impact the correctness and integrity of this information and present a grave security and safety challenge to connected vehicles. Current centralized security solutions are not a good fit as they do not scale well and are unable to validate the correctness of the shared data. Decentralizing security provisioning in connected vehicles by means of the upcoming blockchain technology is an interesting alternative for overcoming these limitations. However, current permission-less linear hash-chain based blockchain solutions have low transaction throughput, high computational cost and are resource intensive, thereby making their adoption for designing a security solution for resource constrained connected cars difficult. In this paper, we present TangleCV, a decentralized technique for secure message sharing and recording for connected vehicles using an approach like Tangle, a directed acyclic graph based blockchain architecture. We introduce an initial design of TangleCV and describe how it provides improved efficiency and scalability against information correctness and information integrity attacks in connected vehicle networks.

TangleCV: Decentralized Technique for Secure Message Sharing in Connected Vehicles

A method for testing GPS receivers may read GPS files with data for a plurality of GPS satellites, and two or more GPS satellites may be selected from that data. The method may receive parameters for a GPS receiver to be tested. The method may generate two or more GPS signals for the two or more selected GPS satellites. The method may operate on the two or more GPS signals using the received parameters for the GPS receiver to generate two or more calculated GPS signals. These two or more calculated GPS signals may be re-sampled to a common rate. The two or more re-sampled GPS signals may be added together to create a composite GPS signal. The composite GPS signal may be generated using a hardware signal generator, where the composite GPS signal used to test the GPS receiver.

Generation of Multi-satellite GPS Signals in Software

A system and method for determining the modulation type and constellation order of an input signal given that the modulation type and constellation order are known to belong to set of possible types/orders. A computer operates on samples of the input signal to compute signal features. The computer classifies the modulation type and the constellation order by comparing each feature to one or more corresponding threshold values. The results of the comparisons are used to determine the modulation type and constellation order of the input signal from the set of possible types/orders. The classification may be performed based on a decision tree, each leaf node of the decision tree corresponding to a type/order combination, and each non-leaf node corresponding to one or more of the comparisons. The set of possible types/order may include PSK with a number of different constellation orders and QAM with a number of different constellation orders.

Abhay Samant

Papers

Classification of Wireless LAN Signals

Spectrum sensing in cognitive radio networks and metacognition for dynamic spectrum sharing between radar and communication system: A review

TangleCV: Decentralized Technique for Secure Message Sharing in Connected Vehicles

Generation of Multi-satellite GPS Signals in Software

Detecting the Modulation Type and/or Constellation Order of a PSK/QAM-Modulated Signal