In this paper, we analyze the impact of different frame types on self-similarity and burstiness characteristics of the aggregated frame traffic from a real 802.11 wireless local area network. We find that characteristics of aggregated frame traffic are affected by both mean frame size and the proportion of specified frame types. Based on this new knowledge, an adaptative frame size optimization (AFSO) mechanism is proposed to improve the transmission efficiency by adaptively adjusting data frame size according to the proportions of different frame types. Simulation results show that our proposed mechanism can effectively regulate the burstiness of aggregated frame traffic and improve the successful delivery rate of data frames when a fixed throughput target is set for 802.11 wireless networks.

Data routing in wireless sensor networks must be energy-efficient because tiny sensor nodes have limited power. A cluster-based hierarchical routing is known to be more efficient than a flat routing because only cluster-heads communicate with a sink node. Existing hierarchical routings, however, assume unrealistically large radio transmission ranges for sensor nodes so they cannot be employed in real environments. In this paper, by considering the practical transmission ranges of the sensor nodes, we propose a clustering and routing method for hierarchical sensor networks: First, we provide the optimal ratio of cluster-heads for the clustering. Second, we propose a d-hop clustering scheme. It expands the range of clusters to d-hops calculated by the ratio of cluster-heads. Third, we present an intra-cluster routing in which sensor nodes reach their cluster-heads within d-hops. Finally, an inter-clustering routing is presented to route data from cluster-heads to a sink node using multiple hops because cluster-heads cannot communicate with a sink node directly. The efficiency of the proposed clustering and routing method is validated through extensive simulations.

Rapid developments in wireless sensor networks have extended many applications, hence, many studies have developed wireless sensor network positioning systems for indoor environments. Among those systems, the Global Position System (GPS) is unsuitable for indoor environments due to Line-Of-Sight (LOS) limitations, while the wireless sensor network is more suitable, given its advantages of low cost, easy installation, and low energy consumption. Due to the complex settings of indoor environments and the high demands for precision, the implementation of an indoor positioning system is difficult to construct. This study adopts a low-cost positioning method that does not require additional hardware, and uses the received signal strength (RSS) values from the receiver node to estimate the distance between the test objects. Since many objects in indoor environments would attenuate the radio signals and cause errors in estimation distances, knowing the path loss exponent (PLE) in an environment is crucial. However, most studies preset a fixed PLE, and then substitute it into a radio propagation loss model to estimate the distance between the test points; such method would lead to serious errors. To address this problem, this study proposes a Path Loss Exponent Estimation Algorithm, which uses only four beacon nodes to construct a radio propagation loss model for an indoor environment, and is able to provide enhanced positioning precision, accurate positioning services, low cost, and high efficiency.

The low-rate (LR) UWB is a promising technology for the ubiquitous sensor network (USN) due to its extremely low power consumption and simple transceiver implementation. However the limited communication range is a bottleneck for its widespread use. This paper deals with a new frame structure of class 4 active RFID multi-hop relay system based on ISO/IEC 18000-7 standard integrating with IEEE 802.15.4a LR-UWB PHY layer specification, which sets up a connection to USN. As a result of the vital importance of the coverage and throughput in the application of USN, further we analyze the performance of the proposed system considered both impulse radio UWB (IR-UWB) and chirp spread spectrum (CSS). Our simulation results show that the coverage and throughput are remarkably increased.

In this paper, we propose a cooperative multi-relay scheme for a secondary system to achieve spectrum access along with a primary system. In the primary network, a primary transmitter (PT) transmits the primary signal to a primary receiver (PR). In the secondary network, N secondary transmitter-receiver pairs (ST-SR) selected by a centralized control unit (CCU) are ready to assist the primary network. In particular, in the first time slot, PT broadcasts the primary signal to PR, which is also received by STs and SRs. At STs, the primary signal is regenerated and linearly combined with the secondary signal by assigning fractions of the available power to the primary and secondary signals respectively. The combined signal is then broadcasted by STs in a predetermined order. In order to achieve diversity gain, STs, SRs and PT will combine received replicas of the primary signal, using selection combining technique (SC). We derive the exact outage probability for the primary network as well as the secondary network. The simulation results are presented to verify the theoretical analyses.

This paper proposes a novel scheme for cooperative spectrum sensing on distributed cognitive radio networks. A fuzzy logic rule - based inference system is proposed to estimate the presence possibility of the licensed user's signal based on the observed energy at each cognitive radio terminal. The estimated results are aggregated to make the final sensing decision at the fusion center. Simulation results show that significant improvement of the spectrum sensing accuracy is achieved by our schemes.

This paper proposes an efficient and yet powerful local descriptor called phase-space partition based descriptor (PPD). This descriptor is designed for the mobile image matching and retrieval. PPD, which is inspired from SIFT, also encodes the salient aspects of the image gradient in the neighborhood around an interest point. However, without employing SIFT's smoothed gradient orientation histogram, we apply the region based gradient statistics in phase space to the construction of a feature representation, which allows to reduce much computation requirements. The feature matching experiments demonstrate that PPD achieves favorable performance close to that of SIFT and faster building and matching. We also present results showing that the use of PPD descriptors in a mobile image retrieval application results in a comparable performance to SIFT.

Video streaming service over wireless networks is a challenging task because of the changes in the wireless channel conditions that can occur due to interference, fading, and station mobility. To provide an efficient wireless video streaming service, the rate adaptation scheme should improve wireless node performance and channel utilization. Moreover, the quality adaptation scheme should be considered at the streaming application. To meet these requirements, we propose a new cross-layer design for video streaming over wireless networks. This design includes the rate and quality adaptation schemes. The rate adaptation scheme selects the optimal transmission mode and resolves the performance anomaly problem. Based on performance improvement by the proposed rate adaptation scheme, our quality adaptation scheme improves the quality of video streaming. Through performance evaluations, we prove that our cross-layer design improves the wireless channel utilization and the quality of video streaming.

Forward Error Correction (FEC) techniques have been adopted to overcome packet losses and to improve the quality of video delivery. The efficiency of the FEC has been significantly compromised, however, due to the characteristics of the wireless channel such as burst packet loss, channel fluctuation and lack of Quality of Service (QoS) support. We propose herein an Adaptive Cross-layer FEC mechanism (ACFEC) to enhance the quality of video streaming over 802.11 WLANs. Under the conventional approaches, FEC functions are implemented on the application layer, and required feedback information to calculate redundancy rates. Our proposed ACFEC mechanism, however, leverages the functionalities of different network layers. The Automatic Repeat reQuest (ARQ) function on the Media Access Control (MAC) layer can detect packet losses. Through cooperation with the User Datagram Protocol (UDP), the redundancy rates are adaptively controlled based on the packet loss information. The experiment results demonstrate that the ACFEC mechanism is able to adaptively adjust and control the redundancy rates and, thereby, to overcome both of temporary and persistent channel fluctuations. Consequently, the proposed mechanism, under various network conditions, performs better in recovery than the conventional methods, while generating a much less volume of redundant traffic.

Multiple object association is an important capability in visual surveillance system with multiple cameras. In this paper, we introduce locally initiating line-based object association with the parallel projection camera model, which can be applicable to the situation without the common (ground) plane. The parallel projection camera model supports the camera movement (i.e. panning, tilting and zooming) by using the simple table based compensation for non-ideal camera parameters. We propose the threshold distance based homographic line generation algorithm. This takes account of uncertain parameters such as transformation error, height uncertainty of objects and synchronization issue between cameras. Thus, the proposed algorithm associates multiple objects on demand in the surveillance system where the camera movement dynamically changes. We verify the proposed method with actual image frames. Finally, we discuss the strategy to improve the association performance by using the temporal and spatial redundancy.

In this paper, we present a new class of attacks against an anonymous communication protocol, originally presented in ACNS 2008. The protocol itself was proposed as an improved version of ModOnions, which exploits universal re-encryption in order to avoid replay attacks. However, ModOnions allowed the detour attack, introduced by Danezis to re-route ModOnions to attackers in such a way that the entire path is revealed. The ACNS 2008 proposal addressed this by using a more complicated key management scheme. The revised protocol is immune to detour attacks. We show, however, that the ModOnion construction is highly malleable and this property can be exploited in order to redirect ModOnions. Our attacks require detailed probing and are less efficient than the detour attack, but they can nevertheless recover the full onion path while avoiding detection and investigation. Motivated by this, we present modifications to the ModOnion protocol that dramatically reduce the malleability of the encryption primitive. It addresses the class of attacks we present and it makes other attacks difficult to formulate.

In an identity-based threshold broadcast encryption (IDTHBE) scheme, a broadcaster chooses a set of n recipients and a threshold value t, and the plaintext can be recovered only if at least t receivers cooperate. IDTHBE scheme is different from the standard threshold public key encryption schemes, where the set of receivers and the threshold value are decided from the beginning. This kind of scheme has wide applications in ad hoc networks. Previously proposed IDTHBE schemes have ciphertexts which contain at least n elements. In addition, the security of theses schemes relies on the random oracles. In this paper, we introduce two new constructions of IDTHBE for ad hoc networks. Our first scheme achieves S-size private keys while the modified scheme achieves constant size private keys. Both schemes achieve approximately (n-t)-size ciphertexts. Furthermore, we also show that they are provablesecurity under the decision bilinear Diffie-Hellman Exponent (BDHE) assumption in the standard model.

Data sharing is an essential process for collaborative works particularly in the banking, finance and healthcare industries. These industries require many collaborative works with their internal and external parties such as branches, clients, and service providers. When data are shared among collaborators, security and privacy concerns becoming crucial issues and cannot be avoided. Privacy is an important issue that is frequently discussed during the development of collaborative systems. It is closely related with the security issues because each of them can affect the other. The tradeoff between privacy and security is an interesting topic that we are going to address in this paper. In view of the practical problems in the existing approaches, we propose a collaborative framework which can be used to facilitate concurrent operations, single point failure problem, and overcome constraints for two-party computation. Two secure computation protocols will be discussed to demonstrate our collaborative framework.

Traffic matrix-based anomaly detection and DDoS attacks detection in networks are research focus in the network security and traffic measurement community. In this paper, firstly, a new type of unidirectional flow called IF flow is proposed. Merits and features of IF flows are analyzed in detail and then two efficient methods are introduced in our DDoS attacks detection and evaluation scheme. The first method uses residual variance ratio to detect DDoS attacks after Recursive Least Square (RLS) filter is applied to predict IF flows. The second method uses generalized likelihood ratio (GLR) statistical test to detect DDoS attacks after a Kalman filter is applied to estimate IF flows. Based on the two complementary methods, an evaluation formula is proposed to assess the seriousness of current DDoS attacks on router ports. Furthermore, the sensitivity of three types of traffic (IF flow, input link and output link) to DDoS attacks is analyzed and compared. Experiments show that IF flow has more power to expose anomaly than the other two types of traffic. Finally, two proposed methods are compared in terms of detection rate, processing speed, etc., and also compared in detail with Principal Component Analysis (PCA) and Cumulative Sum (CUSUM) methods. The results demonstrate that adaptive filter methods have higher detection rate, lower false alarm rate and smaller detection lag time.