scholarly journals Efficient distributed network covert channels for Internet of things environments†

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Krzysztof Cabaj ◽  
Piotr Żórawski ◽  
Piotr Nowakowski ◽  
Maciej Purski ◽  
Wojciech Mazurczyk
Keyword(s):  
Internet Of Things ◽  
Communication Networks ◽  
Data Hiding ◽  
Network Traffic ◽  
Data Transfer ◽  
Research Area ◽  
Distributed Network ◽  
Covert Channels ◽  
Secret Communication ◽  
Iot Devices

Abstract Each day more and more Internet of Things (IoT) devices are being connected to the Internet. In general, their applications are diverse but from the security perspective, it is evident that they are increasingly targeted by cybercriminals and used for nefarious purposes. Network covert channels form a subgroup of the information-hiding research area where secrets are sent over communication networks embedded within the network traffic. Such techniques can be used, among others, by malware developers to enable confidential data exfiltration or stealth communications. Recently, distributed network covert channels have raised the attention of security professionals as they allow the cloaking of secret transmission by spreading the covert bits among many different types of data-hiding techniques. However, although there are many works dealing with IoT security, little effort so far has been devoted in determining how effective the covert channels threat can be in the IoT henvironments. That is why, in this article, we present an extensive analysis on how distributed network covert channels that utilize network traffic from IoT devices can be used to perform efficient secret communication. More importantly, we do not focus on developing novel data-hiding techniques but, instead, considering the nature of IoT traffic, we investigate how to combine existing covert channels so the resulting data transfer is less visible. Moreover, as another contribution of our work, we prepare and share with the community the network traffic dataset that can be used to develop effective countermeasures against such threats.

Transcriptional Regulatory Network Topology with Applications to Bio-inspired Networking: A Survey

2022 ◽  
Vol 54 (8) ◽  
pp. 1-36
Author(s):  
Satyaki Roy ◽  
Preetam Ghosh ◽  
Nirnay Ghosh ◽  
Sajal K. Das
Keyword(s):  
Communication Networks ◽  
Biological Networks ◽  
Regulatory Network ◽  
Large Scale ◽  
Data Transfer ◽  
Transcriptional Regulatory Network ◽  
Future Research ◽  
Transcriptional Regulatory ◽  
Iot Devices ◽  
Networking Protocols

The advent of the edge computing network paradigm places the computational and storage resources away from the data centers and closer to the edge of the network largely comprising the heterogeneous IoT devices collecting huge volumes of data. This paradigm has led to considerable improvement in network latency and bandwidth usage over the traditional cloud-centric paradigm. However, the next generation networks continue to be stymied by their inability to achieve adaptive, energy-efficient, timely data transfer in a dynamic and failure-prone environment—the very optimization challenges that are dealt with by biological networks as a consequence of millions of years of evolution. The transcriptional regulatory network (TRN) is a biological network whose innate topological robustness is a function of its underlying graph topology. In this article, we survey these properties of TRN and the metrics derived therefrom that lend themselves to the design of smart networking protocols and architectures. We then review a body of literature on bio-inspired networking solutions that leverage the stated properties of TRN. Finally, we present a vision for specific aspects of TRNs that may inspire future research directions in the fields of large-scale social and communication networks.

Energy Harvesting Methods for Internet of Things

2016 ◽  
pp. 51-70 ◽  
Author(s):  
Vasaki Ponnusamy ◽  
Yen Pei Tay ◽  
Lam Hong Lee ◽  
Tang Jung Low ◽  
Cheah Wai Zhao
Keyword(s):  
Energy Harvesting ◽  
Internet Of Things ◽  
Research Area ◽  
Energy Scavenging ◽  
Distributed Data ◽  
Full Spectrum ◽  
Current Application ◽  
Future Design ◽  
Iot Devices ◽  
New Research

Internet of Things (IoT) has becoming a central theme in current technology trend whereby objects, people or even animals and plants can exchange information over the Internet. IoT can be referred as a network of interconnected devices such as wearables, sensors and implantables, that has the ability to sense, interact and make collective decisions autonomously. In short, IoT enables a full spectrum of machine-to-machine communications equipped with distributed data collection capabilities and connected through the cloud to facilitate centralized data analysis. Despite its great potential, the reliability of IoT devices is impeded with limited energy supply if these devices were to deploy particularly in energy-scarced locations or where no human intervention is possible. The best possible deployment of IoT technology is directed to cater for unattended situations like structural or environmental health monitoring. This opens up a new research area in IoT energy efficiency domain. A possible alternative to address such energy constraint is to look into re-generating power of IoT devices or more precisely known as energy harvesting or energy scavenging. This chapter presents the review of various energy harvesting mechanisms, current application of energy harvesting in IoT domain and its future design challenges.

scholarly journals Bluetooth Low Energy Mesh Networks

2020 ◽  
Author(s):  
Muhammad Rizwan Ghori ◽  
Tat-Chee Wan
Keyword(s):  
Internet Of Things ◽  
Mesh Networks ◽  
Research Area ◽  
Low Energy ◽  
Mesh Network ◽  
Security Threats ◽  
Bluetooth Low Energy ◽  
Mesh Topology ◽  
Reliable Communications ◽  
Iot Devices

Bluetooth Low Energy (BLE) Mesh Networks enable flexible and reliable communications for low-power Internet of Things (IoT) devices. Most BLE-based mesh protocols are implemented as overlays on top of the standard Bluetooth star topologies while using piconets and scatternets. Nonetheless, mesh topology support has increased the vulnerability of BLE to security threats, since a larger number of devices can participate in a BLE Mesh network. To address these concerns, BLE version 5 enhanced existing BLE security features to deal with various authenticity, integrity, and confidentiality issues. Despite of the BLE version 5 security enhancements, viable IDS solutions for BLE Mesh networks remain a nascent research area.

scholarly journals Power Efficient Time-Division Random-Access Model Based in Wireless Communication Networks

2021 ◽  
Vol 2 (4) ◽  
pp. 155-159
Author(s):  
Suma V
Keyword(s):  
Internet Of Things ◽  
Communication Networks ◽  
Radio Channel ◽  
Random Access ◽  
Wireless Communication Networks ◽  
Power Efficient ◽  
Massive Number ◽  
Iot Devices ◽  
Time Division ◽  
Access Model

The conventional infrastructure for mobile-communication is used for providing internet-of-things (IoT) services by the third-generation partnership project (3GPP) with the help of the recently developed cellular internet-of-things (CIoT) scheme. Random-access procedure can be used for connecting the large number of IoT devices using the CIoT systems. This process is advantages as the huge devices are accessed in a concurrent manner. When random access procedures are used simultaneously on a massive number of devices, the probability of congestion is high. This can be controlled to a certain extent through the time division scheme. A power efficient time-division random access model is developed in this paper to offer reliable coverage enhancement (CE) based on the coverage levels (CL). The quality of radio-channel is used for categorization of the CIoT devices after assigning them with CLs. The performance of random-access model can be improved and the instantaneous contention is relaxed greatly by distributing the loads based on their coverage levels into different time periods. Markov chain is used for mathematical analysis of the behavior and state of the devices. The probability of blocking access, success rate and collision control are enhanced by a significant level using this model in comparison to the conventional schemes.

Energy Harvesting Methods for Internet of Things

2020 ◽  
pp. 956-976 ◽  
Author(s):  
Vasaki Ponnusamy ◽  
Yen Pei Tay ◽  
Lam Hong Lee ◽  
Tang Jung Low ◽  
Cheah Wai Zhao
Keyword(s):  
Energy Harvesting ◽  
Internet Of Things ◽  
Research Area ◽  
Energy Scavenging ◽  
Distributed Data ◽  
Full Spectrum ◽  
Current Application ◽  
Future Design ◽  
Iot Devices ◽  
New Research

Internet of Things (IoT) has becoming a central theme in current technology trend whereby objects, people or even animals and plants can exchange information over the Internet. IoT can be referred as a network of interconnected devices such as wearables, sensors and implantables, that has the ability to sense, interact and make collective decisions autonomously. In short, IoT enables a full spectrum of machine-to-machine communications equipped with distributed data collection capabilities and connected through the cloud to facilitate centralized data analysis. Despite its great potential, the reliability of IoT devices is impeded with limited energy supply if these devices were to deploy particularly in energy-scarced locations or where no human intervention is possible. The best possible deployment of IoT technology is directed to cater for unattended situations like structural or environmental health monitoring. This opens up a new research area in IoT energy efficiency domain. A possible alternative to address such energy constraint is to look into re-generating power of IoT devices or more precisely known as energy harvesting or energy scavenging. This chapter presents the review of various energy harvesting mechanisms, current application of energy harvesting in IoT domain and its future design challenges.

Blockchain-Enabled Decentralized Reliable Smart Industrial Internet of Things (BCIIoT)

2021 ◽  
pp. 192-204
Author(s):  
Chandramohan Dhasarathan ◽  
Shanmugam M. ◽  
Shailesh Pancham Khapre ◽  
Alok Kumar Shukla ◽  
Achyut Shankar
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Wireless Communication ◽  
Information Flow ◽  
Data Transfer ◽  
Base Station ◽  
Transmission Power ◽  
Wireless Devices ◽  
Industrial Internet ◽  
Iot Devices

The development of wireless communication in the information technological era, collecting data, and transfering it from unmanned systems or devices could be monitored by any application while it is online. Direct and aliveness of countless wireless devices in a cluster of the medium could legitimate unwanted users to interrupt easily in an information flow. It would lead to data loss and security breach. Many traditional algorithms are effectively contributed to the support of cryptography-based encryption to ensure the user's data security. IoT devices with limited transmission power constraints have to communicate with the base station, and the data collected from the zones would need optimal transmission power. There is a need for a machine learning-based algorithm or optimization algorithm to maximize data transfer in a secure and safe transmission.

A Novel Insider Attack and Machine Learning Based Detection for the Internet of Things

2021 ◽  
Vol 2 (4) ◽  
pp. 1-23
Author(s):  
Morshed Chowdhury ◽  
Biplob Ray ◽  
Sujan Chowdhury ◽  
Sutharshan Rajasegarar
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Network Traffic ◽  
The Internet ◽  
Traffic Data ◽  
Lossy Networks ◽  
Insider Attack ◽  
Iot Devices ◽  
The Impact ◽  
The Internet Of Things

Due to the widespread functional benefits, such as supporting internet connectivity, having high visibility and enabling easy connectivity between sensors, the Internet of Things (IoT) has become popular and used in many applications, such as for smart city, smart health, smart home, and smart vehicle realizations. These IoT-based systems contribute to both daily life and business, including sensitive and emergency situations. In general, the devices or sensors used in the IoT have very limited computational power, storage capacity, and communication capabilities, but they help to collect a large amount of data as well as maintain communication with the other devices in the network. Since most of the IoT devices have no physical security, and often are open to everyone via radio communication and via the internet, they are highly vulnerable to existing and emerging novel security attacks. Further, the IoT devices are usually integrated with the corporate networks; in this case, the impact of attacks will be much more significant than operating in isolation. Due to the constraints of the IoT devices, and the nature of their operation, existing security mechanisms are less effective for countering the attacks that are specific to the IoT-based systems. This article presents a new insider attack, named loophole attack , that exploits the vulnerabilities present in a widely used IPv6 routing protocol in IoT-based systems, called RPL (Routing over Low Power and Lossy Networks). To protect the IoT system from this insider attack, a machine learning based security mechanism is presented. The proposed attack has been implemented using a Contiki IoT operating system that runs on the Cooja simulator, and the impacts of the attack are analyzed. Evaluation on the collected network traffic data demonstrates that the machine learning based approaches, along with the proposed features, help to accurately detect the insider attack from the network traffic data.

scholarly journals E-HIP: An Energy-Efficient OpenHIP-Based Security in Internet of Things Networks

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4921 ◽  
Author(s):  
Peter Kaňuch ◽  
Dominik Macko
Keyword(s):  
Internet Of Things ◽  
Data Transfer ◽  
Security Protocols ◽  
Security Threats ◽  
Optimized Protocol ◽  
Host Identity ◽  
Iot Devices ◽  
High Level ◽  
Application Specific ◽  
The Internet Of Things

The rapidly growing segment of the Internet of Things (IoT) makes the security threats more prominent than ever. The research around communication security and cybersecurity in such networks is still a challenge, mainly due to the typically limited energy and computation resources of IoT devices. The strong security mechanisms require significant power and thus the energy wastage must be minimized. Optimized application-specific security protocols are commonly used to make the data transfer more efficient, while still offering a high level of security. The supported security features, such as confidentiality, integrity or authenticity, should not be affected by the optimization. Our work is focused on optimizing one of the existing security protocols for the use in the IoT area, namely the Host Identity Protocol (HIP). Based on the analysis of related works, we have identified multiple possibilities for optimization and combined some of them into the proposed E-HIP optimized protocol. For verification purpose, it has been implemented as a modification of the open-source OpenHIP library and applied on a communication between real hardware devices. The secured communication worked correctly. The resulting effect of the proposed optimization has been evaluated experimentally and it represents an increase in energy efficiency by about 20%. Compared to other HIP optimizations, the achieved results are similar; however, the proposed optimizations are unique and can be further combined with some of the existing ones to achieve even higher efficiency.

scholarly journals INTERNET OF THINGS BASED SMART AGRICULTURE SYSTEM USING PREDICTIVE ANALYTICS

2017 ◽  
Vol 10 (13) ◽  
pp. 148 ◽  
Author(s):  
Suhas M Patil ◽  
Sakkaravarthi R
Keyword(s):  
Internet Of Things ◽  
Data Transfer ◽  
Predictive Analytics ◽  
Weather Prediction ◽  
Soil Classification ◽  
Farming System ◽  
Quality Data ◽  
Growth Monitoring ◽  
Quality Of Data ◽  
Iot Devices

Due to the use of internet of things (IoT) devices, communication between different things is effective. The application of IoT in agriculture industryplays a key role to make functionalities easy. Using the concept of IoT and wireless sensor network (WSN), smart farming system has been developedin many areas of the world. Precision farming is one of the branches comes forward in this aspect. Many researchers have developed monitoring andautomation system for different functionalities of farming. Using WSN, data acquisition and transmission between IoT devices deployed in farms will be easy. In proposed technique, Kalman filter (KF) is used with prediction analysis to acquire quality data without any noise and to transmit this data for cluster-based WSNs. Due to the use of this approach, the quality of data used for analysis is improved as well as data transfer overhead is minimized in WSN application. Decision tree is used for decision making using prediction analytics for crop yield prediction, crop classification, soil classification, weather prediction, and crop disease prediction. IoT components, such as and cube (IOT Gateway) and Mobius (IOT Service platform), are integrated in proposed system to provide smart solution for crop growth monitoring to users. 

scholarly journals Enabling Processing Power Scalability with Internet of Things (IoT) Clusters

Electronics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 81
Author(s):  
Jorge Coelho ◽  
Luís Nogueira
Keyword(s):  
Internet Of Things ◽  
Programming Language ◽  
Network Traffic ◽  
Crucial Role ◽  
State Of The Art ◽  
End User ◽  
Processing Power ◽  
Increasing Demand ◽  
Iot Devices ◽  
Traditional Approaches

Internet of things (IoT) devices play a crucial role in the design of state-of-the-art infrastructures, with an increasing demand to support more complex services and applications. However, IoT devices are known for having limited computational capacities. Traditional approaches used to offload applications to the cloud to ease the burden on end-user devices, at the expense of a greater latency and increased network traffic. Our goal is to optimize the use of IoT devices, particularly those being underutilized. In this paper, we propose a pragmatic solution, built upon the Erlang programming language, that allows a group of IoT devices to collectively execute services, using their spare resources with minimal interference, and achieving a level of performance that otherwise would not be met by individual execution.

Sign in / Sign up

Export Citation Format

Share Document