PAAL : a framework based on authentication, aggregation, and local differential privacy for internet of multimedia things

Internet of Multimedia Things (IoMT) applications generate huge volumes of multimedia data that are uploaded to cloud servers for storage and processing. During the uploading process, the IoMT applications face three major challenges, i.e., node management, privacy-preserving, and network protection. In this article, we propose a multilayer framework (PAAL) based on a multilevel edge computing architecture to manage end and edge devices, preserve the privacy of end-devices and data, and protect the underlying network from external attacks. The proposed framework has three layers. In the first layer, the underlying network is partitioned into multiple clusters to manage end-devices and level-one edge devices (LOEDs). In the second layer, the LOEDs apply an efficient aggregation technique to reduce the volumes of generated data and preserve the privacy of end-devices. The privacy of sensitive information in aggregated data is protected through a local differential privacy-based technique. In the last layer, the mobile sinks are registered with a level-two edge device via a handshaking mechanism to protect the underlying network from external threats. Experimental results show that the proposed framework performs better as compared to existing frameworks in terms of managing the nodes, preserving the privacy of end-devices and sensitive information, and protecting the underlying network. © 2014 IEEE

An Overview of Security Challenges in Vehicular Ad-Hoc Networks

© 2017 IEEE. Vehicular Ad hoc Networks (VANET) is emerging as a promising technology of the Intelligent Transportation systems (ITS) due to its potential benefits for travel planning, notifying road hazards, cautioning of emergency scenarios, alleviating congestion, provisioning parking facilities and environmental predicaments. But, the security threats hinder its wide deployment and acceptability by users. This paper gives an overview of the security threats at the various layers of the VANET communication stack and discuss some of the existing solutions, thus concluding why designing a security framework for VANET needs to consider these threats for overcoming security challenges in VANET

Blockchain and Federated Learning-enabled Distributed Secure and Privacy-preserving Computing Architecture for IoT Network

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Secure data collection and critical data transmission technique in mobile sink wireless sensor networks

In Mobile sink wireless sensor networks (MSWSN) Sensor nodes are low cost tiny devices with limited storage,computational capability and power except the sink node. Mobile sink has no resource limitation. It has wide range of application in the real world problem like military and civilian domain etc. The nodes in the network are unattended and unprotected so energy efficient and security are two major issues of sensor network. The sensors have limited battery power and low computational capability, requires a security mechanism that must be energy efficient. In this proposed system model mobile sink traverse the network to collect the data. Here we proposed energy efficient secure data collection techniques with mobile sink wireless sensor networks based on symmetric key cryptography. In proposed data collection technique mobile sink traverse network and collect data from one hop neighbors. Proposed cryptosystem is time based as after each fixed amount of time sink generates a large prime number. Using the prime number all nodes in the network update their key to avoid replay attack keep. Data collection MSWSN is three step process. At each new position mobile sink broadcast a beacon frame to alert the static sensors about its presence, secondly sensors send their sensed data towards sink node and finaly mobile sink broad cast another beacon frame to stop the data transmission by sensors. Sensor authenticate the mobile sink with the shared key concept, if it finds that sink is the legitimate node then sensor encrypt their data and transmit it to the sink. A static sensor sense some critical information and sink is not within its range, that that time sensor needs to transmit its data towards sink immediately. It cannot wait till sink come to its range. For that we proved an existing protocol Sensor Protocol for Information via Negation (SPIN) is efficient for critical data transmission to the mobile sink. Then we make it as the secured protocol by using symmetric key cryptography. Here we use the previous assumption to make it as the secure protocol. All the simulation has been carried out with NS 2.34. This thesis is supported bythe literature survey in the area of Mobile Sink Wireless Sensor Networks to make it complete

Design and Discovery of Sensor Web Registry Services for Wireless Sensor Network with x-SOA Approach

The application of wireless sensor network is emerging as a new trend in different sphere of modern society. However due to the advancement of SWE, designing & discovering sensor web registry services throughout heterogeneous environments is becoming a challenging task and raises several concerns like performance, reliability, and robustness. Many approaches and frameworks have been proposed to discover the sensor web registry services. Some of the approaches assume that the requests are placed in SOAP compatible formats while others focus on GUI based parametric query processing. We have formulated an approach that uses the Natural Language Query Processing which is a convenient and easy method of data access, especially for casual users who do not understand complicated database query languages such as SQL or XML based Query Language like XQuery and XPath. SOA is the proven technology for designing an efficient Sensor Web Registry by describing various parameters and sensor web services needed. We also propose an architecture based on x-SOA that organizes the method of sensor web registry service discovery in an efficient and structured manner using an intermediary, requester friendly layer called the Request Parser & Query Generator (RPQ) between the service provider and service requester via a service registry. We describe how RPQ facilitates the processing of plain text request query to a most appropriate sensor web service and also an algorithm with implementation for a complete cycle of sensor web registry service discovery

Towards efficient and lightweight security architecture for big sensing data streams

University of Technology Sydney. Faculty of Engineering and Information Technology.A large number of mission critical applications from disaster management to health monitoring are contributing to the Internet of Things (IoT) by deploying a number of smart sensing devices in a heterogeneous environment. Resource constrained sensing devices are being used widely to build and deploy self-organising wireless sensor networks for a variety of critical applications. Many such devices sense the deployed environment and generate a variety of data and send them to the server for analysis as data streams. The key requirement of such applications is the need for near real-time stream data processing in large scale sensing networks. This trend gives birth to an area called big sensing data streams. One of the key problems in big data is to ensure end-to-end security where a Data Stream Manager (DSM) must always verify the security of the data before executing a query to ensure data security (i.e., confidentiality, integrity, authenticity, availability and freshness) as the medium of communication is untrusted. A malicious adversary may access or tamper with the data in transit. One of the challenging tasks in such applications is to ensure the trustworthiness of collected data so that any decisions are made on the correct data, followed by protecting the data streams from information leakage and unauthorised access. This thesis considers end-to-end means from source sensors to cloud data centre. Although some security issues are not new, the situation is aggravated due to the features of the five Vs of big sensing data streams: Volume, Velocity, Variety, Veracity and Value. Therefore, it is still a significant challenge to achieve data security in big sensing data streams. Providing data security for big sensing data streams in the context of near real time analytics is a challenging problem. This thesis mainly investigates the problems and security issues of big sensing data streams from the perspectives of efficient and lightweight processing. The big data streams computing advantages including real-time processing in efficient and lightweight fashion are exploited to address the problem, aiming at gaining high scalability and effectiveness. Specifically, the thesis examines three major properties in the lifecycle of security in big data streams environments. The three properties include authenticity, integrity and confidentiality also known as the AIC triad, which is different to CIA triad used in general data security. Accordingly, a lightweight security framework is proposed to maintain data integrity and a selective encryption technique to maintain data confidentiality over big sensing data streams. These solutions provide data security from source sensing devices to the processing layer of cloud data centre. The thesis also explore a further proposal on a lattice based information flow control model to protect data against information leakage and unauthorised access after performing the security verification at DSM. By integrating the access control model, this thesis provides an end-to-end security of big sensing data streams i.e. source sensing device to the cloud data centre processing layer. This thesis demonstrates that our solutions not only strengthen the data security but also significantly improve the performance and efficiency of big sensing data streams compared with existing approaches

A Synchronized Shared Key Generation Method for Maintaining End-to-End Security of Big Data Streams

A large number of mission critical applications ranging from disaster management to smart city are built on the Internet of Things (IoT) platform by deploying a number of smart sensors in a heterogeneous environment. The key requirements of such applications are the need of near real-time stream data processing in large scale sensing networks. This trend gives birth of an area called big data stream. One of the key problems in big data stream is to ensure the end-to-end security. To address this challenge, we proposed Dynamic Prime Number Based Security Verification (DPBSV) and Dynamic Key Length Based Security Framework (DLSeF) methods for big data streams based on the shared key derived from synchronized prime numbers in our earlier works. One of the major shortcomings of these methods is that they assume synchronization of the shared key. However, the assumption does not hold when the communication between Data Stream Manager (DSM) and sensing devices is broken. To address this problem, this paper proposes an adaptive technique to synchronize the shared key without communication between sensing devices and DSM, where sensing devices obtain the shared key re-initialization properties from its neighbours. Theoretical analyses and experimental results show that the proposed technique can be integrated with our DPBSV and DLSeF methods without degrading the performance and efficiency. We observed that the proposed synchronization method also strengthens the security of the models

Quality of Service Provisioning with modified IEEE 802.11 MAC Protocol

There has been a phenomenal increase in the demand of quality-of-service (QoS) in wireless networks over the years due to rapid growth in the number of wireless and mobile devices. Such devices are in use to access Internet and QoS aware applications such as video conferencing, voice-over IP, interactive video-on-demand and many other multimedia applications. wireless local area networks (WLANs) confirming to the IEEE 802.11 standard have become extremely popular at an unprecedented rate. As a result, WLAN networks are gaining the momentum and making their way into residential, commercial, industrial and public areas. These trends are more and more accelerated in places like airports, hotels and coffee shop, this typically has many floating end users. The time stringent applications are delay sensitive that require throughput and delay bound creates an urgent need for QoS support in WLANs