Delay Tolerant networks (DTN) generally lack end-to-end connectivity and multiple message copies routing protocols are often used to improve the efficiency that messages are delivered successfully, but network load is...
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Integrity measurement is just one of the most important features in a trusted computing platform to provide evidence of platform configuration and behavior. Each set of software instructions(binary code) is measured a...
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Integrity measurement is just one of the most important features in a trusted computing platform to provide evidence of platform configuration and behavior. Each set of software instructions(binary code) is measured and recorded before it is executed. Especially, all of boot components which be recorded in pre-boot stage can't be re-measured until the platform is rebooted. However, the reality is that many components belong to pre-boot stage, such as BIOS, Boot Loader and MBR, are easily modified or updated in runtime environment. If these updated results of components are treated as configuration requirements for a remote server-side to verify the access request, the remote network access connection will fail. It must restart the host to re-measure there components, and the result of the new measure is not guaranteed right absolutely. We solve this problem by embedding Integrity Measurement Agency Component(IMAC) which has the capability of monitoring transformation, verifying credibility, updating Platform Configuration Registers and recording integrity measurement logs in Linux kernel. The result of performance analysis demonstrates that the method is feasible and credible.
Authentication has received increasing attention in the literatures of Internet of Things. At the same time, numerous concerns have been raised about the issue of anonymity due to users' awareness of their privacy...
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Authentication has received increasing attention in the literatures of Internet of Things. At the same time, numerous concerns have been raised about the issue of anonymity due to users' awareness of their privacy nowadays. How to achieve trade-off between anonymity and certification simultaneously? In this paper, we propose a security architecture to ensure anonymity and certification for Internet of Things. We use pseudonym and threshold secret sharing approach to resolve conflict between anonymity and certification. Moreover, the implementation of Bloom filter offers security authentication for remote command. Security analysis shows that the proposed mechanism can perfectly achieve tradeoff between anonymity, certification, and also resist impersonation, tamper as well as compromise attacks.
A lot of attention has been paid to anonymity due to the users' privacy protection. While peer-topeer (P2P) networks need anonymity capacity, the authority also requires partner traceability to prevent anonymous a...
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A lot of attention has been paid to anonymity due to the users' privacy protection. While peer-topeer (P2P) networks need anonymity capacity, the authority also requires partner traceability to prevent anonymous abuse. So there is a challenge to harmonize the dilemma between the anonymity and authentication in P2P networks. Few P2P protocol provides complete anonymity as well as traceability. In this paper, we propose a security mechanism to ensure anonymity for honest peers and traceability for misbehaving peers in P2P systems. We utilize superposition watermarking based anonymity trace scheme to resolve the conflicts between traceability and anonymity. This scheme uses information processing technology similar to CDMA to superpose path information. Security analysis and simulation result show that the superposition watermarking based P2P anonymity trace scheme (SWP2P) can attain tradeoff between anonymity and traceability perfectly.
Cloud computing is a novel computing pattern, and it can provide underlying hardware resource for cloud users on demand. Virtualization is the key technology of cloud computing, and it provides the technical support f...
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Cloud computing is a novel computing pattern, and it can provide underlying hardware resource for cloud users on demand. Virtualization is the key technology of cloud computing, and it provides the technical support for cloud computing. In cloud platform, power management is an indispensable function of cloud system administration. Based on genetic algorithm, this paper proposes a power management method based on virtual cluster. The experiments on Xen platform prove the effectiveness of our method.
In wireless networks, the cross-layer design of joint medium access control and network coding can avoid destructive interferences among concurrent transmissions. Wireless network codes in conjunction with conflict-fr...
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In wireless networks, the cross-layer design of joint medium access control and network coding can avoid destructive interferences among concurrent transmissions. Wireless network codes in conjunction with conflict-free network realizations are designed by Sagduyu. Then, this paper proposed a new conflict-free transmission schedule based on network coding to achieve better network performance. We construct sub tree graphs by sub tree decomposition, and based on the achieved sub tree graphs, time slots are assigned from the first sub tree. Nodes of the latter sub trees can be chosen to combine with the front time slots according to whether there exist conflicts or not. Finally, network codes allocation method for network with two sources is presented, which adopts the theory of graph coloring.
In Database-as-a-Service (DBaaS), a large number of tenants share DBaaS resources (CPU, I/O and Memory). While the DBaaS provider runs DBaaS to "share" resources across the entire tenant population to maximi...
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In Database-as-a-Service (DBaaS), a large number of tenants share DBaaS resources (CPU, I/O and Memory). While the DBaaS provider runs DBaaS to "share" resources across the entire tenant population to maximize resource utilization and minimize cost, the tenants subscribe to DBaaS at a low price point while still having resources conceptually "isolated" according to service level agreements (SLAs). To optimize this dichotomy of goals, we propose a dynamic resource allocation framework that periodically re-allocates resources to tenants to maximize resource utilization while tolerating a low risk of SLA violations. We model the resource allocation problem as a modified unbounded knapsack problem. The model introduces an additional fairness constraint to assign residual resources to active tenants, while avoiding that few tenants consume all residual resources. Performed experiments demonstrate the effectiveness and efficiency of the proposed allocation algorithm for a synthetic workload with burstiness and predicted tenant behavior.
Microarray data are highly redundant and noisy, and most genes are believed to be uninformative with respect to studied classes, as only a fraction of genes may present distinct profiles for different classes of sampl...
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Microarray data are highly redundant and noisy, and most genes are believed to be uninformative with respect to studied classes, as only a fraction of genes may present distinct profiles for different classes of samples. This paper proposed a novel hybrid framework (NHF) for the classification of high dimensional microarray data, which combined information gain(IG), F-score, genetic algorithm(GA), particle swarm optimization(PSO) and support vector machines(SVM). In order to identify a subset of informative genes embedded out of a large dataset which is contaminated with high dimensional noise, the proposed method is divided into three stages. In the first stage, IG is used to construct a ranking list of features, and only 10% features of the ranking list are provided for the second stage. In the second stage, PSO performs the feature selection task combining SVM. F-score is considered as a part of the objective function of PSO. The feature subsets are filtered according to the ranking list from the first stage, and then the results of it are supplied to the initialization of GA. Both the SVM parameter optimization and the feature selection are dynamically executed by PSO. In the third stage, GA initializes the individual of population from the results of the second stage, and an optimal result of feature selection is gained using GA integrating SVM. Both the SVM parameter optimization and the feature selection are dynamically performed by GA. The performance of the proposed method was compared with that of the PSO based, GA based, Ant colony optimization (ACO) based and simulated annealing (SA) based methods on five benchmark data sets, leukemia, colon, breast cancer, lung carcinoma and brain cancer. The numerical results and statistical analysis show that the proposed approach is capable of selecting a subset of predictive genes from a large noisy data set, and can capture the correlated structure in the data. In addition, NHF performs significantly better than th
In this paper, we develop a new subspace based multiuser carrier frequency offset (CFO) estimation scheme for multi-input multi- output (MIMO) orthogonal frequency division multiple access (OFDMA) uplink transmission....
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In this paper, we develop a new subspace based multiuser carrier frequency offset (CFO) estimation scheme for multi-input multi- output (MIMO) orthogonal frequency division multiple access (OFDMA) uplink transmission. We exploit the rank reduction approach by equipping multiple antennas at the receiver, in which the CFO of each user is derived blindly using one dimension (1-D) search individually. The proposed scheme supports the generalized subcarrier assignment scheme and full loaded transmission with all subcarriers being allocated to users. Numerical results are provided to corroborate the proposed studies.
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