Security and Privacy for Green IoT-based Agriculture: Review, Blockchain solutions, and Challenges

open access articleThis paper presents research challenges on security and privacy issues in the field of green IoT-based agriculture. We start by describing a four-tier green IoT-based agriculture architecture and summarizing the existing surveys that deal with smart agriculture. Then, we provide a classification of threat models against green IoT-based agriculture into five categories, including, attacks against privacy, authentication, confidentiality, availability, and integrity properties. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward secure and privacy-preserving technologies for IoT applications and how they will be adapted for green IoT-based agriculture. In addition, we analyze the privacy-oriented blockchain-based solutions as well as consensus algorithms for IoT applications and how they will be adapted for green IoT-based agriculture. Based on the current survey, we highlight open research challenges and discuss possible future research directions in the security and privacy of green IoT-based agriculture

SDAMQ: Secure Data Aggregation for Multiple Queries in Wireless Sensor Networks

Wireless Sensor Network consists of severely energy constrained sensor nodes and are susceptible to security attacks due to broadcast communication model. It is necessary to optimize the transmission of packets to reduce the energy consumption. In addition data has to be encrypted in order to overcome the attack from the compromising nodes. We propose Secure Data Aggregation for Multiple Queries (SDAMQ) in Wireless Sensor Networks where multiple aggregate queries from the sink are authenticated and distributed to the sensor nodes. The sensor nodes respond by aggregating data belonging to multiple coexisting queries into a single packet, there by reducing the transmission cost. The intermediary nodes aggregate the encrypted data using additively homomorphic encryption. Thus authenticated query propagation combined with homomorphic encryption provide secure data aggregation at low energy consumption. Simulation results shows that SDAMQ provides better performance

Security and Privacy Issues in Wireless Mesh Networks: A Survey

This book chapter identifies various security threats in wireless mesh network (WMN). Keeping in mind the critical requirement of security and user privacy in WMNs, this chapter provides a comprehensive overview of various possible attacks on different layers of the communication protocol stack for WMNs and their corresponding defense mechanisms. First, it identifies the security vulnerabilities in the physical, link, network, transport, application layers. Furthermore, various possible attacks on the key management protocols, user authentication and access control protocols, and user privacy preservation protocols are presented. After enumerating various possible attacks, the chapter provides a detailed discussion on various existing security mechanisms and protocols to defend against and wherever possible prevent the possible attacks. Comparative analyses are also presented on the security schemes with regards to the cryptographic schemes used, key management strategies deployed, use of any trusted third party, computation and communication overhead involved etc. The chapter then presents a brief discussion on various trust management approaches for WMNs since trust and reputation-based schemes are increasingly becoming popular for enforcing security in wireless networks. A number of open problems in security and privacy issues for WMNs are subsequently discussed before the chapter is finally concluded.Comment: 62 pages, 12 figures, 6 tables. This chapter is an extension of the author's previous submission in arXiv submission: arXiv:1102.1226. There are some text overlaps with the previous submissio

Location based services in wireless ad hoc networks

In this dissertation, we investigate location based services in wireless ad hoc networks from four different aspects - i) location privacy in wireless sensor networks (privacy), ii) end-to-end secure communication in randomly deployed wireless sensor networks (security), iii) quality versus latency trade-off in content retrieval under ad hoc node mobility (performance) and iv) location clustering based Sybil attack detection in vehicular ad hoc networks (trust). The first contribution of this dissertation is in addressing location privacy in wireless sensor networks. We propose a non-cooperative sensor localization algorithm showing how an external entity can stealthily invade into the location privacy of sensors in a network. We then design a location privacy preserving tracking algorithm for defending against such adversarial localization attacks. Next we investigate secure end-to-end communication in randomly deployed wireless sensor networks. Here, due to lack of control on sensors\u27 locations post deployment, pre-fixing pairwise keys between sensors is not feasible especially under larger scale random deployments. Towards this premise, we propose differentiated key pre-distribution for secure end-to-end secure communication, and show how it improves existing routing algorithms. Our next contribution is in addressing quality versus latency trade-off in content retrieval under ad hoc node mobility. We propose a two-tiered architecture for efficient content retrieval in such environment. Finally we investigate Sybil attack detection in vehicular ad hoc networks. A Sybil attacker can create and use multiple counterfeit identities risking trust of a vehicular ad hoc network, and then easily escape the location of the attack avoiding detection. We propose a location based clustering of nodes leveraging vehicle platoon dispersion for detection of Sybil attacks in vehicular ad hoc networks --Abstract, page iii

An energy-efficient and secure data inference framework for internet of health things: A pilot study

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. Privacy protection in electronic healthcare applications is an important consideration, due to the sensitive nature of personal health data. Internet of Health Things (IoHT) networks that are used within a healthcare setting have unique challenges and security requirements (integrity, authentication, privacy, and availability) that must also be balanced with the need to maintain efficiency in order to conserve battery power, which can be a significant limitation in IoHT devices and networks. Data are usually transferred without undergoing filtering or optimization, and this traffic can overload sensors and cause rapid battery consumption when interacting with IoHT networks. This poses certain restrictions on the practical implementation of these devices. In order to address these issues, this paper proposes a privacy-preserving two-tier data inference framework solution that conserves battery consumption by inferring the sensed data and reducing data size for transmission, while also protecting sensitive data from leakage to adversaries. The results from experimental evaluations on efficiency and privacy show the validity of the proposed scheme, as well as significant data savings without compromising data transmission accuracy, which contributes to energy efficiency of IoHT sensor devices

Implementation of MD5 Framework for Privacy-Preserving Support for Mobile Healthcare

The improvement of science and technology has made life so easy and fast that smartphones and other touch-screen minicomputers have become the most trusted personal storage and communication devices for individuals. Comparable to the rich enhancement in wireless body sensor networks, it is valuable to the development of medical treatment to be exceptionally adaptable and become very flexible by means of smartphones through 2G and 3G system bearers. This has made treatment simple even to the common individual in the general public with less payable cash. In this paper, we introduce privacy-preserving support for mobile healthcare using message digest where we have used an MD5 algorithm instead of AES, which can certainly achieve an efficient way and minimizes the memory consumed and the large amount of PHI data of the medical user (patient) is reduced to a fixed amount of size compared to AES which in parallel increases the speed of the data to be sent to TA without any delay which in-turn. This study implements a secure and privacy-preserving opportunistic computing framework (SPOC) for mobile-health care emergency. Utilizing smartphones and SPOC, assets like computing power and energy can be gathered to reliably to take care of intensive personal health information (PHI) of the medicinal client when he/she is in critical situation with minimal privacy disclosure. With these, the healthcare authorities can treat the patients (restorative clients) remotely, where the patients live at home or at different spots they run. This sort of a treatment can be done under mHealth (Mobile-Healthcare). In malice of the fact that in them-medicinal services administration, there are numerous security and information protection issues to be succeed. The main aim of this paper is to bring medical health to patients in remote locations by providing the basic triage of an emergency to increase the patient’s body acceptance until they can reach a proper medical facility, in addition to providing emergency care in minimal payable cash