Elsevier

Telematics and Informatics

Volume 27, Issue 4, November 2010, Pages 377-393
Telematics and Informatics

A remote interactive non-repudiation multimedia-based m-learning system

https://doi.org/10.1016/j.tele.2010.01.001Get rights and content

Abstract

One of the current challenges regarding distance learning systems, from a performance point of view, is the efficient and timely delivery of multimedia-enriched learning materials. Providing guaranteed Class of Service (CoS) and Quality of Service (QoS) are also challenging especially for remote sites and rural areas where Internet coverage tends to be limited. On a different note, another challenge is to track the audience accessing the learning materials and more importantly to monitor the true identity of the examination attendees. This paper aims to investigate both of these issues simultaneously, with an introduction of a non-repudiation system that provides a security mechanism, as well as maintaining certain QoS measures. This system not only authenticates the intended party, but also integrates a digital signature scheme accompanied with the transmitted multimedia-based information. The included digital signature prevents a later dispute from the involved parties that the communication ever took place or they ever took part in the communication.

Therefore this paper introduces and discusses a multimedia-enriched interactive non-repudiation system involved in a mobile-based learning (m-learning) environment. The performance of this system is considered and discussed in terms of network-centric parameters, including end-to-end delays, overhead, and bandwidth, using Labview 8.5 mobile-transmitter and mobile-receiver testbeds.

Introduction

In this paper we study the security requirements of m-learning systems and develop an application layer non-repudiation multi-level signature-based system, which features a biometric scheme to create digital IDs. These IDs are based on both unique device and biometric characteristics, specific to each user, which we refer to as: identity data or digital ID. Digital signatures will be created based on a digital ID. In parallel, three cross-layer-based parameters are extracted and imported to the application layer and the application layer encoder takes these parameters into account for proper multimedia encoding. A hash function is then applied to the entire data payload (identity data, cross-layer information, and the generated digital signature), and the resulted hash value is added to the pre-hashed payload and the entire information is packed in the UDP (User Datagram Protocol) payload. The hash value is used to prevent any unnoticed illegitimate changes to the UDP payload. The UDP packet streams are then further processed at lower layers (i.e., network, MAC, and physical layers) and transmitted via a Wi-Fi link. The sender and the receiver can both be on the same Distributed System (DS), in which case the entire end-to-end path will be explicitly wirelessly. The sender and receiver can also be located in two different geographical locations, in which case, the end-to-end data path may include several hops with partial wired segments.

Once the UDP payloads are received and unpacked, the three components: identity data, cross-layer information, and the digital signature are separated and used accordingly. The digital signature and the subsequent identity data are used to correctly identify the user proper user/device identification and for a non-repudiation purpose. The performance of this system is discussed in details using analytical and real data transmission flows simulated by Labview 8.5.

The organization of this paper is as follows: Section 2 discusses the current security approaches in m-learning scenarios. Section 3 is focused on the system’s overall architecture and algorithm. Section 4 discusses application layer, including the cross-layer interaction and the multimedia encoding. Section 5 considers the required handling at the transport, network, MAC, and PHY layers. Section 6 presents the details of the multi-layer system design. Section 7 includes the Quality of Service (QoS) performance discussions, including; end-to-end delays, jitter, and bandwidth figures. Section 8 presents the security analysis of the system. Section 9 provides the conclusion following by the reference.

Section snippets

Current Implementations

Electronic-learning (e-learning) is a learning method where the involved parties are usually in different geographical locations and the instruction information are passed through computer networks and viewed by computer-based systems. e-Learning systems and techniques have evolved over the recent years and have progressed to a limit that face-to-face interactions are becoming less required. In particular, various conferencing technologies, including; teleconferencing (voice-based),

System’s architecture

Fig. 2 shows the proposed system’s flowchart, which includes a digital signature processing unit that is fed by the biometric authentication unit and outputs digital signature information. This system is able to transmit multimedia traffic (text, voice, and video), digital signature, and cross-layer data simultaneously. The cross-layer data, as mentioned, is used to optimize the multimedia encoding function. For voice; G.711 and for video; H.264 codecs are used. These codecs are explained in a

Application layer functions

At the application layer, we are dealing with messages and security processes can be applied to messages rather than packet-level processing. Here are the functions taking place at the application layer:

Transport, network, MAC, and PHY layers data handling

Once data is passed from the application layer to the transport layer, UDP starts shaping the incoming information into its payloads. Fig. 4 shows the hierarchy of functions and data handling procedures. UDP is the main transport protocol conveying the payload (i.e., hash, cross-layer, digital signature, and multimedia information).

The network layer is responsible for three main functions; providing remote internetwork address (IP address), the routing QoS (IP-DSCP), and the routing security

Application layer

The main communication protocols conveying digital ID, CLPs, and other information is UDP, which operates on top of IP. Besides the digital ID and the CLPs, two parties will be communicating in the following formats:

Text: This can be non-interactive (email) or interactive (text-chat). In this case, keyboard key strokes are captured and placed in the UDP payload along with CLP and digital ID.

Interactive typing requires a very low bandwidth. An average professional typist reaches 50–70 words per

QoS discussions

Table 9 gathers the summary of the system’s performance measures in terms total payload and overhead. An observation while hashing is performed indicates that the delay figures given in Table 6 are delay per block, therefore to calculate the total amount of delay overhead, one has to find the total number of blocks in which the hashing algorithm requires and multiple the value given in the delay per block column by the number of resulted blocks. For instance UDP payload with DSA and voice has a

Security analysis

Table 16 summarizes the security summary of the entire system. It includes the algorithms used in each layer and to point to the fact that the specific algorithm is either vulnerable or secure. With appropriate selections (based on AES), both network and MAC layers can be considered as secure and the rest of the layers may have security vulnerabilities. There are remedies listed for each security weakness, however depending on the scenarios, the remedies may or may not be conclusive. Denial of

Conclusion

In this paper we studied the security requirements of m-learning systems and developed an application layer non-repudiation system based on a person’s biometric information, which resulted in the generation of a digital ID. These IDs were based on certain biometric characteristics and were uniquely created for each user and then digital signatures were created based on the digital IDs. In parallel, three cross-layer-based parameters were extracted from the cross-layer system and imported to the

Acknowledgement

This work was supported in part by the Natural Sciences and Engineering Research Council of Canada.

Sasan Adibi (BS’95, MS’99, MS’05) is a Ph.D. student in his final semester at the Electrical and Computer Engineering Department of the University of Waterloo, Canada. His current research interests include; security and Quality of Service (QoS) in wireless technologies.

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    Sasan Adibi (BS’95, MS’99, MS’05) is a Ph.D. student in his final semester at the Electrical and Computer Engineering Department of the University of Waterloo, Canada. His current research interests include; security and Quality of Service (QoS) in wireless technologies.

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