Biometrics identification module and personal wearable electronics network based authentication and transaction processing are disclosed. According to one embodiment, a method for biometric authentication may include (1) a biometric identification device connecting to a plurality of sensing devices, each of the plurality of sensing devices receiving a user characteristic from a user; (2) the biometric identification device receiving the user characteristics from the sensing devices; (3) the biometric identification device communicating the received user characteristics to a server; (4) the biometric identification device receiving a biometric profile for the user; and (5) the biometric identification device storing the biometric profile.

Biometrics identification module and personal wearable electronics network based authentication and transaction processing

Systems and methods for prioritizing electronic messages in an electronic message repository are disclosed. According to one embodiment, a method may include (1) at least one computer processor determining an amount of message review time for a user; (2) the at least one computer processor estimating a number of electronic messages that the user can review in the message review time; (3) the at least one computer processor determining a priority level for a plurality of electronic messages in the user's electronic message repository; (4) the at least one computer processor selecting electronic messages from the user's electronic message repository based on the estimated number of electronic messages that the user can review and the priority level for the electronic messages.

Systems and methods for electronic message prioritization

INTRODUCTION BINOMIAL DATA Challenger Disaster Example Binomial Regression Model Inference Tolerance Distribution Interpreting Odds Prospective and Retrospective Sampling Choice of Link Function Estimation Problems Goodness of Fit Prediction and Effective Doses Overdispersion Matched Case-Control Studies COUNT REGRESSION Poisson Regression Rate Models Negative Binomial CONTINGENCY TABLES Two-by-Two Tables Larger Two-Way Tables Matched Pairs Three-Way Contingency Tables Ordinal Variables MULTINOMIAL DATA Multinomial Logit Model Hierarchical or Nested Responses Ordinal Multinomial Responses GENERALIZED LINEAR MODELS GLM Definition Fitting a GLM Hypothesis Tests GLM Diagnostics OTHER GLMS Gamma GLM Inverse Gaussian GLM Joint Modeling of the Mean and Dispersion Quasi-Likelihood RANDOM EFFECTS Estimation Inference Predicting Random Effects Blocks as Random Effects Split Plots Nested Effects Crossed Effects Multilevel Models REPEATED MEASURES AND LONGITUDINAL DATA Longitudinal Data Repeated Measures Multiple Response Multilevel Models MIXED EFFECT MODELS FOR NONNORMAL RESPONSES Generalized Linear Mixed Models Generalized Estimating Equations NONPARAMETRIC REGRESSION Kernel Estimators Splines Local Polynomials Wavelets Other Methods Comparison of Methods Multivariate Predictors ADDITIVE MODELS Additive Models Using the gam Package Additive Models Using mgcv Generalized Additive Models Alternating Conditional Expectations Additivity and Variance Stabilization Generalized Additive Mixed Models Multivariate Adaptive Regression Splines TREES Regression Trees Tree Pruning Classification Trees NEURAL NETWORKS Statistical Models as NNs Feed-Forward Neural Network with One Hidden Layer NN Application Conclusion APPENDICES Likelihood Theory R Information Bibliography Index

Extending the linear model with R : generalized linear, mixedeffects and nonparametric regression models

With the expeditious development of Internet, the security of communication is one of the most essential elements.Internet Key Exchange(IKE), resolves problems of building and updating key that is shared in the unsafe environment such as Internet.

Internet Key Exchange

Network virtualization has evolved as a key enabling technology for offering the next generation network services. Recently, it is being rolled out in data center networks as a means to provide bandwidth guarantees to cloud applications. With increasing deployments of virtual networks (VNs) in commercial-grade networks with commodity hardware, VNs need to tackle failures in the underlying substrate network. In this paper, we study the problem of recovering a batch of VNs affected by a substrate node failure. The combinatorial possibilities of alternate embeddings of the failed virtual nodes and links of the VNs make the task of finding the most efficient recovery both non-trivial and intractable. Furthermore, any recovery approach ideally should not cause any service disruption for the unaffected parts of the VNs. We take into account these issues to design a generalized recovery approach that can achieve customized objectives such as fair treatment on the failed VNs, partial treatment based on priority, and so on. We provide integer linear programming (ILP) formulations for two variants of our recovery scheme, namely, fair recovery model and priority-based recovery model. We also propose a fast and scalable heuristic algorithm to tackle the computational complexity of the ILP solution. Evaluation results demonstrate that our heuristic performs close to the optimal solution and outperforms the state-of-the-art algorithm.

Generalized Recovery From Node Failure in Virtual Network Embedding

Methods, devices, and systems are presented that facilitate pattern-based user authentication. In a first embodiment, a user may request registration from an authentication server. The authentication server may provide at least one image to the user, wherein the image may comprise a matrix of cells. The user may choose a sequence of cells in the matrix as his or her secret, and may provide a userid and this secret to the authentication server. The authentication server may then validate and store the userid and/or secret. After this registration step, the user may request authentication from the authentication server. The authentication server may provide another image of a matrix of cells to the user. The user may then enter a sequence of symbols associated the sequence of cells that comprise his or her secret. The authentication server may compare the entered sequence of cells to the sequence of cells represented by the stored secret. If the two sequences match, then the user may be authenticated.

Methods and devices for pattern-based user authentication

Network virtualization has evoked interest among researchers as a promising solution for developing flexible and manageable architectures for future Internet. One of the major challenges in network virtualization is the efficient allocation of substrate resources to the Virtual Networks (VNs) - a problem known as Virtual Network Embedding (VNE). Most of the past research on VNE has been focused on algorithms to allocate resources to VNs. The problem of reconfiguration, however, is relatively less explored. In this paper, we propose a simulated annealing algorithm for reconfiguring the VNs in order to balance the load across the substrate network, thereby reducing the peak node and link load on the substrate network. Through extensive simulations we evaluate the proposed reconfiguration algorithm and show that after reconfiguration there is a 20% reduction in maximum link load and 5% reduction in maximum node load. The average link load is reduced by 50% and the fraction of links having a load above 50% is reduced from 66% to 14%. We also show that periodic reconfiguration leads to a significant improvement in the acceptance ratio of VN requests.

Simulated annealing algorithm for virtual network reconfiguration

IPSec provides security solutions to various network based web applications through its protocol suite. Implementing IPSec in the network layer includes significant bandwidth and processing time overhead to application traffic. The upper layer protocols such as TCP and UDP behavior on network traffic is also influenced by these overheads. In our work, we have studied the impact of IPSec on the metrics: Number of Transactions, Transmission Time, Round Trip Time, Average Burst Size and Available Bandwidth for IPv4 and IPv6 network traffic. Authentication algorithm: Hashed Message Authentication Code - Message Digest 5(HMAC-MD5), encryption algorithm: Advanced Encryption Standard(AES) and compression algorithm deflate are considered for Authentication Header(AH), Encapsulated Security Payload(ESP) and IP Compression(IPComp) protocols of IPSec. Using the characterized metrics, computed overheads and user behavior on web page requests, we have analyzed the performance impact of IPSec on web application servers.

Impact of IPSec Overhead on Web Application Servers

At present Internet has emerged as a country's predominant and viable data communication infrastructure. The Autonomous System (AS) resources which are building blocks of the Internet are AS numbers, IPv4 and IPv6 Prefixes. AS number growth is one of Internet infrastructure development indicators. Hence understanding on long term trend and stochastic variation behaviour are essential to detect significant events during the growth. In this work, time series based approximation is considered for mathematical modelling and forecast the yearly AS growth. The AS data of five countries namely India, China, Japan, South Korea and Taiwan are extracted from APNIC archive. ARIMA models with different Auto Regressive and Moving Average parameters are identified for forecasting. Model validation, parameter estimation, point forecast and prediction intervals with 95 % confidence levels for the five countries are reported in the paper. The significant level change in variations, positive growth percentage in Inter Annual Absolute Variations (IAAV) and higher percentage of advertised ASes when compared to other countries indicate India's fast growth and wider global reachability of Internet infrastructure from 2007 onwards. The correlation between IAAV change point and GDP growth period indicates that service sector industry growth is the driving force behind significant yearly changes.

Forecasting and Event Detection in Internet Resource Dynamics using Time Series Models.

IPv6 communication protocol vulnerabilities are common security threats in Next Generation Networks. Distributed Denial of Service (DDoS) attacks generated by exploiting these vulnerabilities have performance impact on both victim as well as on other hosts sharing the communication path. Hence in order to protect the computational and bandwidth resources of the shared path, the anomalies caused by these attacks are to be detected and the attack traffic should be filtered out from the network elements. Under the context of flow state maintenance not deployed in the network elements, the bandwidth characterization of the attack traffic is essential to deploy the filtering rules in the equipments. In this work we have considered the network bandwidth characterization of a highly critical DDoS attack in the network: the distributed reflector attack through spoofed IPv6 flows. The generated spoofed IPv6 traffic from the attacker (slaves), the reflector attack traffic caused by the responses from the reflector and the victim, and the end-to-end path bandwidth characteristics of these flows over a 6to4 tunnel are reported in terms of flow rates and per flow packet count. The flow rate pattern of the spoofed flows is modeled at the attacker side using inter departure time and packet size. The impact of network scale factor on the flow rate pattern over the path is studied and reported. We also have quantified the reflector attack flow rate in the presence of the scale factor and multiple spoofed flow sources.

S. V. Raghavan

Papers

Methods and devices for pattern-based user authentication

Simulated annealing algorithm for virtual network reconfiguration

Impact of IPSec Overhead on Web Application Servers

Forecasting and Event Detection in Internet Resource Dynamics using Time Series Models.

A study on path behavior characteristics of IPv6 based reflector attacks