Recent Advances on IoT-Assisted Wearable Sensor Systems for Healthcare Monitoring

Nowadays, the integration of Wireless Sensor Networks (WSN) and the Internet of Things (IoT) provides a great concern for the research community for enabling advanced services. An IoT network may comprise a large number of heterogeneous smart devices for gathering and forwarding huge data. Such diverse networks raise several research questions, such as processing, storage, and management of massive data. Furthermore, IoT devices have restricted constraints and expose to a variety of malicious network attacks. This paper presents a Secure Sensor Cloud Architecture (SASC) for IoT applications to improve network scalability with efficient data processing and security. The proposed architecture comprises two main phases. Firstly, network nodes are grouped using unsupervised machine learning and exploit weighted-based centroid vectors for the development of intelligent systems. Secondly, the proposed architecture makes the use of sensor-cloud infrastructure for boundless storage and consistent service delivery. Furthermore, the sensor-cloud infrastructure is protected against malicious nodes by using a mathematically unbreakable one-time pad (OTP) encryption scheme to provide data security. To evaluate the performance of the proposed architecture, different simulation experiments are conducted using Network Simulator (NS3). It has been observed through experimental results that the proposed architecture outperforms other state-of-the-art approaches in terms of network lifetime, packet drop ratio, energy consumption, and transmission overhead.

/pdf/sasc-secure-and-authentication-based-sensor-cloud-28r26humzg.pdf

SASC: Secure and Authentication-Based Sensor Cloud Architecture for Intelligent Internet of Things

A novel image encryption scheme of dynamic S-boxes and random blocks based on spatiotemporal chaotic system

Implementation of an improved chaotic encryption algorithm for real-time embedded systems by using a 32-bit microcontroller

Emerging IoT Applications in Sustainable Smart Cities for COVID-19: Network Security and Data Preservation Challenges with Future Directions.

Internet of Things is a fast growing technology and a network of devices in which everything (smart objects or smart devices) are associated to the internet for effective exchange of information between these connected objects. Internet of Things (IoT) serves as a method for healthcare and acts as an essential part in broad range of real-time healthcare monitoring applications. Previous work shows networked sensor devices, either equipped on the body or embedded inside living being or a camera, make possible in gathering real-time information to evaluate physical and mental health state of the patient by collecting body temperature, blood pressure, patient's image, etc. Communicating this collected real-time data to the doctor, making accurate assessment on the data gathered and notifying the patient is challenging task in the IoT. The architechture of Internet of Things comprises of three layers, and it is the network of devices embedded with sensor, software, and electronics, enabling this device to communicate with each other and exchange data over a computer network. The IoT-based real-time healthcare systems are highly vulnerable to cyber-attacks as the numbers of sensors are deployed in an unprotected network. These may even introduce the attacks, which cannot be monitored and controlled. This paper attempts to review the previous work done and a new scheme has been proposed, the new lightweight authentication protocol for smart real-time healthcare. The proposed scheme requires implementation with the authentication protocol. It is important to satisfy the major parameters of security: confidentiality, integrity, authentication, and access control. In this paper our focus is on the authentication of devices.

A review: a new authentication protocol for real-time healthcare monitoring system.

This paper proposes three different chaotic encryption methods using 1-D chaotic map known as Logistic map named as Logistic, NLFSR and Modified NLFSR according to the name of chaotic map and non-linear function involved in the scheme. The designed schemes have been crypt analyzed for five different methods for testing its strength. Cryptanalysis has been performed for various texts using various keys selected from domain of key space. Logistic and NLFSR methods are found to resist known plaintext attack for available first two characters of plaintext. Plaintext sensitivity of both methods is within small range along with medium key sensitivity. Identifiability for keys of first two of the scheme has not been derived concluding that methods may prove to be weak against brute-force attack. In the last modified scheme avalanche effect found to be improved compared to the previous ones and method is found to resist brute-force attack as it derives the conclusion for identifiability.

/pdf/chaotic-encryption-scheme-using-1-d-chaotic-map-2rpem21nmx.pdf

Chaotic Encryption Scheme Using 1-D Chaotic Map

An encryption method is proposed that uses self-invertible matrix, modular function, Non-Linear shift register and the chaotic map known as Logistic. Parameter of Logistic map act as secret key. As chaotic system used in this algorithm is 1-D system, the key space is lesser than 2100 which shows that the method is weak against Brute-force attack but identifiability property of the selected key from key space assures its strength against the attack. Key sensitivity and plaintext sensitivity of the key chosen from key space for the algorithm is analyzed and its strength against known-plaintext attack is also tested and conclusions are derived.

A Chaotic Encryption Algorithm: Robustness against Brute-Force Attack

This paper deals with the application of concept of identifiability based on output equality approach on chaotic ciphers developed using 2-D chaotic maps, Duffings and Arnolds Cat map and they are named as Duffings and Arnold’s Cat, according to the map used. Due to the less key space generally many chaotic cryptosystem developed are found to be weak against Brute force attack which is an essential issue to be solved. Thus, concept of identifiability proved to be a necessary condition to be fulfilled by the designed chaotic cipher to resist brute force attack, which is an exhaustive search. As 2-D chaotic maps provide more key space than 1-D maps thus they are considered to be more suitable. This work is accompanied with analysis results obtained from these developed cipher. Moreover, identifiable keys are searched for different input texts at various key values. The ciphers are also analyzed for plaintext sensitivity and key sensitivity for its validity to provide security.

Chaotic Cipher Using Arnolds and Duffings Map

This paper constructs two encryption methods using 2-D chaotic maps, Duffings and Arnold's cat maps respectively. Both of the methods are designed using message embedded scheme and are analyzed for their validity, for plaintext sensitivity, key sensitivity, known plaintext and brute-force attacks. Due to the less key space generally many chaotic cryptosystem developed are found to be weak against Brute force attack which is an essential issue to be solved. For this issue, concept of identifiability proved to be a necessary condition to be fulfilled by the designed chaotic cipher to resist brute force attack, which is a basic attack. As 2-D chaotic maps provide more key space than 1-D maps thus they are considered to be more suitable. This work is accompanied with analysis results obtained from these developed cipher. Moreover, identifiable keys are searched for different input texts at various key values. The methods are found to have good key sensitivity and possess identifiable keys thus concluding that they can resist linear attacks and brute-force attacks.

Message Embedded cipher using 2-D chaotic map

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