Caret R Package - classification and regression training

Caret R Package - classification and regression training
(http://topepo.github.io/caret/index.html)

The caret package (short for classification and regression training) contains functions to streamline the model training process for complex regression and classification problems. The caret package is a set of functions that attempt to streamline the process for creating predictive models. The package contains tools for:

• data splitting
• pre-processing
• feature selection
• model tuning using resampling
• variable importance estimation

Following are the steps to install caret package (it has many dependencies).

Install "‘minqa’, ‘RcppEigen’, ‘scales’, ‘lme4’, ‘ggplot2’, ‘reshape2’, ‘BradleyTerry2’" one by one.

Step 1: install.packages (“minqa”)

Step 2: install.packages (“RcppEigen”)

Step 3: install.packages(“lme4”)

Step 4: install.packages(“ggplot2”)

Step 5: install.packages(“reshape2”)

Step 6: install.packages(“BradleyTerry2”)

Step 7:  install.packages("caret", dependencies = c("Depends", "Suggests"))

Example of predicting using “glm” method:

library(caret)

library(kernlab)

data(spam)

inTrain <- createDataParition(y=spam$type,p=0.75,list=FALSE)   #partition 75% training and 25% testing

training <- spam[inTrain, ]

testing <- spam[-inTrain, ]

> dim(training) [1] 3451   58 > dim(testing) [1] 1150   58

>

> set.seed(1234) > fit<-train(type~., data=training, method="glm") Loading required namespace: e1071 There were 26 warnings (use warnings() to see them) > fit Generalized Linear Model 3451 samples   57 predictor    2 classes: 'nonspam', 'spam' No pre-processing Resampling: Bootstrapped (25 reps) Summary of sample sizes: 3451, 3451, 3451, 3451, 3451, 3451, ... Resampling results   Accuracy   Kappa      Accuracy SD  Kappa SD    0.9207482  0.8330317  0.008444636  0.01755059

>

> fit$finalModel

Call:  NULL

Coefficients:

      (Intercept)               make  

       -1.515e+00         -3.393e-01  

          address                all  

       -1.482e-01          9.183e-02  

            num3d                our  

        2.531e+00          5.661e-01  

             over             remove  

        4.999e-01          2.612e+00  

         internet              order  

        5.661e-01          8.957e-01  

             mail            receive  

        9.189e-02         -2.957e-01  

             will             people  

       -1.321e-01         -2.583e-01  

           report          addresses  

        1.068e-01          1.121e+00  

             free           business  

        9.468e-01          1.080e+00  

            email                you  

        1.910e-02          8.164e-02  

           credit               your  

        1.387e+00          2.326e-01  

             font             num000  

        3.465e-01          3.525e+00  

            money                 hp  

        1.376e+00         -1.982e+00  

              hpl             george  

       -1.369e+00         -9.258e+00  

           num650                lab  

        9.965e-01         -2.143e+00  

             labs             telnet  

       -6.141e-01         -1.234e-01  

           num857               data  

        2.369e+00         -9.245e-01  

           num415              num85  

        1.111e+00         -2.231e+00  

       technology            num1999  

        7.566e-01          8.572e-02  

            parts                 pm  

       -5.501e-01         -1.005e+00  

           direct                 cs  

       -2.563e-01         -4.692e+01  

          meeting           original  

       -2.173e+00         -9.787e-01  

          project                 re  

       -1.610e+00         -7.536e-01  

              edu              table  

       -1.483e+00         -3.167e+00  

       conference      charSemicolon  

       -4.491e+00         -1.623e+00  

 charRoundbracket  charSquarebracket  

        1.356e-01         -6.342e-01  

  charExclamation         charDollar  

        2.497e-01          5.745e+00  

         charHash         capitalAve  

        2.223e+00         -1.661e-03  

      capitalLong       capitalTotal  

        8.800e-03          7.263e-04  

Degrees of Freedom: 3450 Total (i.e. Null);  3393 Residual

Null Deviance:     4628 

Residual Deviance: 1297        AIC: 1413

PREDICTIONS:

> predictions<- predict(fit, newdata=testing)

> predictions

   [1] spam    spam    spam    spam    spam   

   [6] spam    nonspam spam    spam    spam   

  [11] spam    spam    spam    spam    spam   

  [16] spam    nonspam spam    spam    spam   

  [21] spam    spam    spam    spam    spam   

  [26] nonspam spam    spam    spam    spam   

  [31] nonspam spam    spam    spam    spam   

  [36] spam    spam    spam    spam    spam   

  [41] spam    spam    spam    spam    spam   

  [46] spam    spam    spam    spam    spam   

  [51] spam    spam    spam    nonspam spam   

  [56] spam    spam    spam    spam    spam   

  [61] spam    spam    spam    spam    spam   

  [66] spam    spam    spam    spam    spam   

  [71] spam    spam    spam    spam    nonspam

> confusionMatrix(predictions,testing$type) Confusion Matrix and Statistics           Reference Prediction nonspam spam    nonspam     659   50    spam         38  403                                                          Accuracy : 0.9235                           95% CI : (0.9066, 0.9382)     No Information Rate : 0.6061               P-Value [Acc > NIR] : <2e-16                                                                      Kappa : 0.839            Mcnemar's Test P-Value : 0.241                                                                 Sensitivity : 0.9455                       Specificity : 0.8896                   Pos Pred Value : 0.9295                   Neg Pred Value : 0.9138                       Prevalence : 0.6061                   Detection Rate : 0.5730             Detection Prevalence : 0.6165                 Balanced Accuracy : 0.9176                                                           'Positive' Class : nonspam

>

BLUETOOTH SECURITY

BLUETOOTH SECURITY

(Written By: Sandeep Sinha, PGDM PT 2012-2015)

Bluetooth defines three security modes. Security Mode 1 provides no security enforcement, meaning that the device is effectively taking no steps to protect itself. Security Mode 2 enforces security at the service level. In this mode, a particular application might be relatively safe but no additional device protection has been added. Security Mode 3 is the highest level of security, employing link level enforced security mechanisms. Security Mode 3 protects the device from certain intrusions and, therefore, all services and applications

All Bluetooth services have a default set level of security. Within the service level security, there are also three levels of security. Some services that require authorization and authentication in order to be used, some require authentication only, and some are open to all devices. Bluetooth devices themselves have two levels of security when describing other devices, namely trusted devices and untrusted devices.

TYPES OF ATTACKS

There are a variety of attacks that can be employed against Bluetooth devices, many with colorful names such as blue bugging, blue bumping, blue dumping, blue jacking, blue smacking, blue sniffing, blue spoofing, blue stabbing, blue toothing, and car whisperer. All take advantage of weaknesses in Bluetooth that allow an attacker unauthorized access to a victim's phone. It is imperative to note that while Bluetooth is commonly associated with networks limited in scope to 100 m, attacks on Bluetooth devices have been documented at ranges in excess of 1,500 m. using Bluetooone.

One common approach to hacking Bluetooth devices is to employ malformed objects, which are legal files exchanged between BT devices that contain invalid information, thus causing unexpected results. When a Bluetooth device receives a malformed object, such as a vCard or vCal file, the device may become unstable or fail completely. Alternatively, an attacker might also use a vCard or vCal file to inject commands allowing the attacker to take control of the device. This kind of an attack can be very harmful to a phone.

Some of the common attacks on Bluetooth devices include:

•     Bluebugging: An extraordinarily powerful attack mechanism, bluebugging allows an attacker to take control of a victim's phone using the AT command parser. Bluebug allows an attacker to access a victim's phone in order to make phone calls, send short message service (SMS) messages, read SMS messages stored on the phone, read and write contact list entries, alter phone service parameters, connect to the Internet, set call forwarding, and more.

•     Bluejacking: The sending of unsolicited messages to open Bluetooth devices by sending a vCard with a message in the name field and exploiting the OBEX protocol.

•     Bluesmack: A Bluetooth analog of the Ping-of-Death denial-of-service attack. This is a buffer overflow attack using L2CAP echo messages.

•     Bluesnarf and Bluesnarf++: Attacks allowing for the theft of information from a Bluetooth device using the OBEX Push Profile. The attacker needs only find a phone that has Bluetooth in discoverable mode. Bluesnarf works by a connection to most of the Object Push Profile services and the attacker retrieves the file names of known files from the Infrared Mobile Communications (IrMC) list instead of sending vCard information as expected. With these attacks the hacker can retrieve items such as the phonebook, calendar, and other personal information. With Bluesnarf++, the attacker has full read and write access to the file system of the phone. When an attacker is connected via the OBEX Push Profile, he/she has full access to the victim's phone without having to pair the two devices. The biggest risk with this function is that an attacker can delete crucial file system files, rendering the victim's device useless. In addition, the attacker can access any memory cards that are attached to the device.

•     Helomoto: Helomoto is functionally similar to the Bluebug attack but takes advantage of poor implementations of "trusted device" handling on some phones. As in bluebug attacks, the attacker pretends to send a vCard to an unauthenticated OBEX Push Profile on the victim's phone. Once started, the attacker interrupts the transfer process and the victim then lists the attacker’s phone as a trusted device. The attacker can then connect to the victim's phone and take control of the device by issuing AT commands. This attack is so-named because it was first discovered on Motorola phones.

These attacks are only a few that can be launched against Bluetooth interfaces in phones, laptops, and even automobiles. E-Stealth and Laurie et al. offer information about a wide range of attacks that can be launched via Bluetooth vulnerabilities.