Internet of Things security

The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. IoT is one of the fastest developing fields in the history of computing, with an estimated 50 billion devices by the end of 2020. However, the crosscutting nature of IoT systems and the multidisciplinary components involved in the deployment of such systems have introduced new security challenges. Implementing security measures, such as encryption, authentication, access control, network and application security for IoT devices and their inherent vulnerabilities is ineffective. Therefore, existing security methods should be enhanced to effectively secure the IoT ecosystem. Machine learning and deep learning (ML/DL) have advanced considerably over the last few years, and machine intelligence has transitioned from laboratory novelty to practical machinery in several important applications. Consequently, ML/DL methods are important in transforming the security of IoT systems from merely facilitating secure communication between devices to security-based intelligence systems. The goal of this work is to provide a comprehensive survey of ML methods and recent advances in DL methods that can be used to develop enhanced security methods for IoT systems. IoT security threats that are related to inherent or newly introduced threats are presented, and various potential IoT system attack surfaces and the possible threats related to each surface are discussed. We then thoroughly review ML/DL methods for IoT security and present the opportunities, advantages and shortcomings of each method. We discuss the opportunities and challenges involved in applying ML/DL to IoT security. These opportunities and challenges can serve as potential future research directions.

A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security

Machine learning based solutions for security of Internet of Things (IoT): A survey

The increasing pervasiveness of wireless sensor networks (WSNs) in diverse application domains including critical infrastructure systems, sets an extremely high security bar in the design of WSN systems to exploit their full benefits, increasing trust while avoiding loss. Nevertheless, a combination of resource restrictions and the physical exposure of sensor devices inevitably cause such networks to be vulnerable to security threats, both external and internal. While several researchers have provided a set of open problems and challenges in WSN security and privacy, there is a gap in the systematic study of the security implications arising from the nature of existing communication protocols in WSNs. Therefore, we have carried out a deep-dive into the main security mechanisms and their effects on the most popular protocols and standards used in WSN deployments, i.e., IEEE 802.15.4, Berkeley media access control for low-power sensor networks, IPv6 over low-power wireless personal area networks, outing protocol for routing protocol for low-power and lossy networks (RPL), backpressure collection protocol, collection tree protocol, and constrained application protocol, where potential security threats and existing countermeasures are discussed at each layer of WSN stack. This paper culminates in a deeper analysis of network layer attacks deployed against the RPL routing protocol. We quantify the impact of individual attacks on the performance of a network using the Cooja network simulator. Finally, we discuss new research opportunities in network layer security and how to use Cooja as a benchmark for developing new defenses for WSN systems.

/pdf/a-survey-of-potential-security-issues-in-existing-wireless-5502h2c0ox.pdf

A Survey of Potential Security Issues in Existing Wireless Sensor Network Protocols

This paper reports world averages of measurements of b -hadron, c -hadron, and -lepton properties obtained by the Heavy Flavour Averaging Group using results available through September 2018. In rare cases, significant results obtained several months later are also used. For the averaging, common input parameters used in the various analyses are adjusted (rescaled) to common values, and known correlations are taken into account. The averages include branching fractions, lifetimes, neutral meson mixing parameters,  violation parameters, parameters of semileptonic decays, and Cabibbo–Kobayashi–Maskawa matrix elements.

Averages of b-hadron, c-hadron, and $$\tau $$-lepton properties as of 2018: Heavy Flavor Averaging Group (HFLAV)

In the present-day context, man-made sources of ground-borne vibration are rising at a very rapid rate due to increasing construction work, blasting activities, and rapidly expanding rail a...

/pdf/efficiency-of-open-and-infill-trenches-in-mitigating-ground-dkop0hysps.pdf

Efficiency of Open and Infill Trenches in Mitigating Ground-Borne Vibrations

Purpose



– The purpose of this paper is to study lightweight security scheme for Internet of Things (IoT) applications using Constrained Application Protocol (CoAP). Resource-constrained characteristics of IoT systems have ushered in compelling requirements for lightweight application protocol and security suites. CoAP has already been established as the candidate protocol for IoT systems. However, low overhead security scheme for CoAP is still an open problem. Existing security solutions like Datagram Transport Layer Security (DTLS) is not suitable, particularly due to its expensive handshaking, public key infrastructure (PKI)-based authentication and lengthy ciphersuite agreement process. 




Design/methodology/approach



– This paper proposes a lightweight security scheme in CoAP using Advanced Encryption Standard (AES) 128 symmetric key algorithm. The paper presents an object security (payload embedded)-based robust authentication mechanism with integrated key management. The paper introduces few unique modifications to CoAP header to optimize security operation and minimize communication cost. 




Findings



– It is resilient to number of security attacks like replay attack, meet-in-the-middle attack and secure under chosen plaintext attack. This scheme is generic in nature, applicable for gamut of IoT applications. The paper proves efficacy of our proposed scheme for vehicle tracking application in emulated laboratory setup. Specifically, it compares with DTLS-enabled CoAP to establish the lightweight feature of our proposed solution. 




Research limitations/implications



– This paper mainly focuses on implementing in-vehicle tracking systems as an IoT application and used CoAP as the application protocol. 




Practical implications



– Such a lightweight security scheme would provide immense benefit in IoT systems so that resource constraint-sensing devices and nodes can be made secure. This would impact IoT eco systems to a large extent. 




Originality/value



– Such kind of security suite that provides both robustness and lightweight feature is hitherto not known to the authors, particularly in CoAP for IoT applications.

Lightweight security scheme for IoT applications using CoAP

Secure yet lightweight protocol for communication over the Internet is a pertinent problem for constrained environments in the context of Internet of Things (IoT) / Machine to Machine (M2M) applications. This paper extends the initial approaches published in [1], [2] and presents a novel cross-layer lightweight implementation to establish a secure channel. It distributes the responsibility of communication over secure channel in between the application and transport layers. Secure session establishment is performed using a payload embedded challenge response scheme over the Constrained Application Protocol (CoAP) [3]. Record encryption mechanism of Datagram Transport Layer Security (DTLS) [4] with Pre-Shared Key (PSK) [5] is used for encrypted exchange of application layer data. The secure session credentials derived from the application layer is used for encrypted exchange over the transport layer. The solution is designed in such a way that it can easily be integrated with an existing system deploying CoAP over DTLS-PSK. The proposed method is robust under different security attacks like replay attack, DoS and chosen cipher text. The improved performance of the proposed solution is established with comparative results and analysis.

LESS: Lightweight Establishment of Secure Session: A Cross-Layer Approach Using CoAP and DTLS-PSK Channel Encryption

IoT (Internet of Things) systems are resource-constrained and primarily depend on sensors for contextual, physiological and behavioral information. Sensitive nature of sensor data incurs high probability of privacy breaching risk due to intended or malicious disclosure. Uncertainty about privacy cost while sharing sensitive sensor data through Internet would mostly result in overprovisioning of security mechanisms and it is detrimental for IoT scalability. In this paper, we propose a novel method of optimizing the need for IoT security enablement, which is based on the estimated privacy risk of shareable sensor data. Particularly, our scheme serves two objectives, viz. privacy risk assessment and optimizing the secure transmission based on that assessment. The challenges are, firstly, to determine the degree of privacy, and evaluate a privacy score from the fine-grained sensor data and, secondly, to preserve the privacy content through secure transfer of the data, adapted based on the measured privacy score. We further meet this objective by introducing and adapting a lightweight scheme for secure channel establishment between the sensing device and the data collection unit/ backend application embedded within CoAP (Constrained Application Protocol), a candidate IoT application protocol and using UDP as a transport. We consider smart energy management, a killer IoT application, as the use-case where smart energy meter data contains private information about the residents. Our results with real household smart meter data demonstrate the efficacy of our scheme.

Why not keep your personal data secure yet private in IoT?: Our lightweight approach

In Internet of Things (IoT), numerous and diverse types of sensors generate a plethora of data that needs to be stored and processed with minimum loss of information. This demands efficient compression mechanisms where loss of information is minimized. Hence data generated by diverse sensors with different signal features require optimum balance between compression gain and information loss. This paper presents a unique analysis of contemporary lossy compression algorithms applied on real field sensor data with different sensor dynamics. The aim of the work is to classify the compression algorithms based on the signal characteristics of sensor data and to map them to different sensor data types to ensure efficient compression. The present work is the stepping stone for a future recommender system to choose the preferred compression techniques for the given type of sensor data.

Tulika Bose

Papers

Efficiency of Open and Infill Trenches in Mitigating Ground-Borne Vibrations

Lightweight security scheme for IoT applications using CoAP

LESS: Lightweight Establishment of Secure Session: A Cross-Layer Approach Using CoAP and DTLS-PSK Channel Encryption

Why not keep your personal data secure yet private in IoT?: Our lightweight approach

Signal Characteristics on Sensor Data Compression in IoT -An Investigation