If you still want more there is another fine tutorial on this subject, which complements the first one with some more examples and scripts that you may want to have a look at. check it in advanced bash scripting guide by Mendel Cooper.

When we think of security and privacy and proctet data information we always think on disk encryption , well that’s true but we shouldn’t  leave our data at everyone disposal, just because we believe the data is encrypted ergo secure.

Normally the most succefull attacks are not on cracking the data, by some brute force or mathematical algorithm, but instead we attack the user which can be misleading in a simple maner to give us the password for decrypting the data.

“Security is not something that you can buy, but is a process that you must ensure”, this not only applies for computer security but also for personel defense.

I just want to minimize the risk of beeing compromized, you can do so by putting this on the configurations file:

<users>
     <!-- dont use this for root user, use it only for user BOB -->
     <user id="BOB">
       <!-- Disable debug output for user "scox" -->
       <option name="debug">false</option>
</users>
<services>
     <service id="su">
       <!-- Disable pam_usb for "su" ("su" will ask for a password as usual) -->
       <option name="enable">false<option>
     </service>
     <service id="sudo">
       <option name="enable">false<option>
     </service>
</services>

Thanks to pamusb.org

This article will point out some tricks to improve the security of your linux server, that you may have at work on the datacenter at your desk or even in your home.
As all of you know (linux geeks, and semi-geeks) whenever you have a problem with your computer and cannot login with the usual username password you can reboot the PC and in the GRUB level you may choose to boot in Single User mode. This boot mode is for maintenance only and give root access to that machine without even ask for a password, well at least in the default configuration.
Because the default configuration is never secure we will improve it a bit by setting a password

~~:S:wait:/sbin/sulogin

Now whenever you try to boot in this mode you are asked for the root password, so no more fun for the in house hackers

After a carefull threat assesment we found out that the users in our company were smart enough to bypass this issue just by using a live cd or USB disk and then chroot and again add access to the complete system.
We will block this issue by simply put a password in the PC BIOS, and in he boot devices put the hardrive as the first option and disable all the other options.

We should have in mind that the user doesn’t have the capability, due to measures implemented by the company security team, to open up the case of the server and reset the bios. To overcome this issue we could also flash the bios with our specific options and passwords embbebed, thus avoiding this threat. But If the attacker wanted to he could always change the BIOS chip, or even simpler steell the hardrive.
So as you can see we cannot be 100% secure, but we can improve the security measures to dificult the attacker success.

Thanks to Bruce Schneier in “Secrets and Lies”, a very nice and pragmatic book about security in general, and threat accessement in computer security. A very intelligent book that all SysADmins should read.

Thanks to Vivek Gite post .

Attention to the GridBagLayout!
http://madbean.com/anim/totallygridbag/

The JarWars
http://madbean.com/anim/jarwars/

First step: create a java hello world class

file: HelloWorld.java

class HelloWorld {
public void doStuff(void){
out.println("Hello World!");
}
}

Then you need to compile the code:

keep in mind that you need to compile the source code with the matlab jre, otherwise it may not work.

javac -cp %CLASSPATH:/path/to/matlab/jre HelloWorld.java

Second step:

After compiling you get HelloWorld.class file, and then you need to create a .jar file with that class, therefore:

jar -cvf  library.jar HelloWorld.class

Third step:

Now you need to include the jar file to the matlab environment and then use the methods inside of the library. Such as :

file : dummy2.m

clear all;
javaaddpath(/path/to/library.jar);
(...)
HelloWorld.doStuff
(...)

All the code above tries to show the logic behind the difficult job of making Matlab and Java working together. The show code present is an aggregation of several web posts, foruns and some official documentation from Mathworks, but each one for itself is not enough, and i spend lot of time to achieve this knowledge, and therefore i’m sharing it with you.

Another tool that i used a lot was Matlab – MAthWorks, which in the last version (2008) allows us to write code in a object oriented way. And because is built on top of a Java Virtual Machine, it now allows to use java objects on their .m files.

The code snippets that i will show is to use the WEKA library on Matlab files, but it can be used to link any kind of java library.

file dummy.m:

//include jar libraries to matlab environment
javaaddpath('/opt/weka-3-5-7/weka.jar');
javaaddpath('/opt/weka/libsvm.jar');
//imports java like
import weka.classifiers.*;
import weka.classifiers.Classifier.*;
import weka.classifiers.bayes.BayesNet.*;
import weka.classifiers.Evaluation.*;
//Arff files
ARFFtrainfile = "/path/to/arfftrainfile.arff";
ARFFtestfile = "/path/to/arfftestfile.arff";
//Settings for the classifier
v(1) = java.lang.String('-t');
v(2) = java.lang.String(ARFFtrainfile);
v(3) = java.lang.String('-T');
v(4) = java.lang.String(ARFFtestfile);
v(5) = java.lang.String('-S 0 -K 2 -D 3 -G 0.0010 -R 0.0 -N 0.5 -M 40.0 -C 10.0 -E 0.0010 -P 0.1');
//concatenate the settings in a string
prm = cat(1,v(1:end));
//create classifier instance, and perform the evaluation
classifier = javaObject('weka.classifiers.functions.LibSVM');
weka.classifiers.Evaluation.evaluateModel(classifier,prm)
//open trainset<span style="background-color: #ffffff;"> </span>
reader = javaObject('java.io.FileReader', ARFFTrainfile);
dataset = javaObject('weka.core.Instances', reader);
dataset.setClassIndex(dataset.numAttributes() - 1);
//build classifier model
classifier.buildClassifier(dataset);
...
while (true) {
instance = javaObject('weka.core.Instance', length(attributes_Dataset));
predicted = classifier.classifyInstance(instance);
//predict the class from the instance
class = dataset.attribute(dataset.numAttributes() -1).value(predicted))
}
...

In the code above the part inside the while is for predict the class of each instance; each instance can be any vector but need to have the same number of attributes as the ones in the dataset , in the arff files.

Writing good software engineering research papers: minitutorial (from ieee)

Using Eclipse to develop for Embedded Linux on a Window Host