17598350
Certified e-mail delivery with DSA receipts
In this paper we present two variant protocols DSA-CEMD1 and DSA-CEMD2 for certified e-mail delivery with DSA receipts. The protocols are based on a cryptographic primitive called Verifiable and Recoverable Encryption of a Signature (VRES) and are capable of achieving non-repudiation and strong fairness security properties. The novel design of the VRES primitive allows efficiency improvements in comparison with the related certified e-mail delivery protocols based on similar primitives. The protocols employ the services of an off-line and invisible trusted third party (TTP) only in case of dispute. In DSA-CEMD1 the content of the e-mail message is not revealed to the TTP during possible recovery and this is achieved at the cost of some additional cryptographic operations. In DSA-CEMD2 the confidentiality of the message is not protected from the TTP, but the protocol is slightly more efficient.
1660866
A General Fuzzified CMAC Controller with Eligibility
This paper presents an online neural network controller. Cerebellar Model Articulation Controller (CMAC) is suitable to online control due to its fast learning speed. By integrating the CMAC address scheme with fuzzy logic concept, a general fuzzified CMAC (GFAC) is proposed. Then by incorporating the concept of eligibility into the GFAC, a GFAC controller with eligibility is presented, named FACE. A learning algorithm for the FACE is derived to tune the model parameters. To achieve online control, an efficient implementation of the proposed FACE method is presented. As an example, the proposed FACE is applied to a ship steering control system. The simulation results show that the ship course can be properly controlled under the disturbances of wave, wind and current.
14935404
Levels of Authentication Assurance: an Investigation
The ES-LoA project, funded by the UK Joint Information Systems Committee (JISC) under its e- Infrastructure Security Programme, investigates current and future needs among UK research and education community for a more fine-grained authorisation scheme that would allow service providers to take into account of the levels of confidence in identifying a remote entity requesting for service access. Such a fine-grained authorisation scheme is attractive to service providers offering resources with varying levels of sensitivity and/or wishing to tailor their security protections based upon risk levels. Service providers may wish to restrict access to more sensitive resources only to those who have gone through a more stringent authentication process, or given the same remote entity, require the use of a stronger authentication token should the access request come from a more risky environment. In this way, the quality of an authentication instance, expressed as an authentication Level of Assurance (LoA), becomes one of the parameters used in access control decision making. This paper investigates the current worldwide efforts in defining LoA and identifies gaps in existing definitions when they are applied to a federated environment.
1884872
A mobility monitoring based advance reservation protocol
Future wireless cellular networks will be Internet Protocol (IP) based. Users of wireless devices in these networks will expect to run real-time applications that require guarantees of Quality of Service (QoS). Such a user will expect the same seamless QoS that he would receive if he were running real-time applications on a wired network. Achieving seamless QoS in a mobile environment implies that a reservation should be re-established at the new Base Station (BS) before hand-over occurs. However, making these advance reservations is wasteful of valuable bandwidth in the wireless network. This paper proposes a protocol, called the Mobility Monitoring Based Advance Reservation Protocol (M²BARP), which aims to reduce the bandwidth overhead of making advance reservations. The protocol makes use of information about a Mobile Node's (MN) mobility to make a single advance reservation when the MN is about to hand-over. Unlike previous work, M²BARP takes advantage of overlapping cells to help to provide a more seamless QoS by reducing the number of calls dropped at hand-over
13044783
A New Time-domain Detection Approach with Blind Separation Based on Neural Network
In this paper a new technique is proposed for time-domain detection in energy detection. The proposed scheme is based on a independent-component analysis (ICA): blind separation of unknown source signals. This method not only improves the nicety of time-domain detection for narrow band signal and the sinusoidal signal but also reduces the power of the whole detection system.
42027884
New Approximation for Minimum-Weight Routing Backbone in Wireless Sensor Network
Our problem formulation is as follows. Given a weighted disk graph Gwhere the weight of edge represents the transmission energy consumption, we wish to determine a dominating tree Tof Gsuch that the total weight of edges in Tis minimized. To the best of our knowledge, this problem have not been addressed in the literature. Solving the dominating tree problem can yield a routing backbone for broadcast protocols since: (1) each node does not have to construct their own broadcast tree, (2) utilize the virtual backbone to reduce the message overhead, and (3) the weight of backbone is minimized. 
 
Our contributions to this problem is multi-fold: First, the paper is the first to study this problem, prove the hardness of this problem and propose an approximation framework. Second, we present a heuristic to approximate the solution with low time complexity. Third, a distributed algorithm is provided for practical implementation. Finally, we verify the effectiveness of our proposal through simulation.
8279850
Analysis and Simulation Protocols Based on Slotted ALOHA for Plastic Optical Fiber Network
In this paper a novel multipriority reservation protocols for plastic optical fiber network is proposed. In conventional OCDMA system only allows finite units to transmit and access simultaneously according to the number of channels which be restricted by BER. To resolve this problem, a novel protocol based on slotted ALOHA is proposed in this paper. By using the reservation scheme and a distributed arbitration algorithm, channel collision and destination conflict can be avoided. The protocol can efficiently support the transmission of multimedia messages that require the different time-delay. The network throughput and average delay has been investigated by numerical analysis and simulation experiments. It is showed that the multipriority reservation protocol in this POF network is valid and efficient.
15693719
Context-based Arithmetic Coding Reexamined for DCT Video Compression
This paper presents a new context modeling technique for arithmetic coding of DCT coefficients in video compression. A key feature of the new technique is the inclusion of all previously coded coefficient magnitudes in a DCT block in context modeling. This enables adaptive arithmetic coding to exploit the redundancy of the high-order Markov process in the DCT domain with a few conditioning states. In addition, a context weighting technique is used to further improve the coding efficiency. The complexity of the new arithmetic coding scheme is slightly lower than that of context-based adaptive binary arithmetic coding (CABAC) of H.264. Moreover, the scheme is made compatible to the AVS baseline profile. It achieves on average 13% improvement in compression ratio over context-based two dimension variable length coding (C2DVLC) designed for the DCT domain, and a similar coding efficiency as the CABAC technique in H.264.
9464715
Assisting seller pricing strategy selection for electronic auctions
This research examines sellers' pricing strategy oriented to bidders' risk preferences, within the context of an electronic auction. A business model is then proposed to predict the probability of potential bidders' risk preference, which sellers can consider to set pricing strategy to maximize their profits. A tailored intelligent auction registry engine is constructed based upon an initial version of our business model. Because the extensible markup language (XML)-based simple object access protocol (SOAP) is utilized to support interactions with other resources, our engine is decoupled from the underlying technology choices; therefore, it can be deployed to different platforms.
36918365
C3: A New Learning Scheme to Improve Classification of Rare Category Emails
This paper proposes C3, a new learning scheme to improve classification performance of rare category emails in the early stage of incremental learning. C3 consists of three components: the chief-learner, the co-learners and the combiner. The chief-learner is an ordinary learning model with an incremental learning capability. The chief-learner performs well on categories trained with sufficient samples but badly on rare categories trained with insufficient samples. The co-learners that are focused on the rare categories are used to compensate for the weakness of the chief-learner in classifying new samples of the rare categories. The combiner combines the outputs of both the chief-learner and the co-learner to make a finial classification. The chief-learner is updated incrementally with all the new samples overtime and the co-learners are updated with new samples from rare categories only. After the chief-learner has gained sufficient knowledge about the rare categories, the co-learners become unnecessary and are removed. The experiments on customer emails from an e-commerce company have shown that the C3 model outperformed the Naive Bayes model on classifying the emails of rare categories in the early stage of incremental learning.
15131459
An Ant Colony Optimization Algorithm for Learning Classification Rules
Ant colony optimization (ACO) algorithm has been applied to data mining recently. Aiming at Ant Miner, a classification rule learning algorithm based on ACO, this paper presents an enhanced Ant Miner, which includes two main contributions. Firstly, a rule punishing operator is employed to reduce the number of rules and the number of conditions. Secondly, an adaptive state transition rule and a mutation operator are applied to the algorithm to speed up the convergence rate. The results of experiments on some data sets demonstrate that the enhanced Ant-Miner can quickly discover better classification rules which have roughly competitive predicative accuracy and short rules