Category Archives: Uncategorized

Good Bye

Well, Almost over year I wrote here.

Now I have found a new place.

Whatever and however bad I write.. it would now be published here :

Had a great time !

All the blogs from this place have been shifted to the new place.

Happy Living ..


IBM loses tapes with employee data

The News article is very disturbing indeed.

Big Blue did not have a backup ??

Very disappointing to see.

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google analytics

_uacct = “UA-1642796-2”;

Cool Tool !

Have you used Hyperwords ? You don’t know yet ?

Go use it

Very useful .. Have a look at the translating feature..! IT IS COOL

Try out all the features atleast once .

One more reason why you would want to use FIREFOX !

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The problem with random number generators

It is a commonly accepted fact that computers by themselves cannot generate
truly random numbers, and so most software relies on pseudo random numbers.his means that encryption and other applied uses of"random" numbers may not be as secure as users think. However, it ispossible to expand the boundaries of generating random numbers using acomputer. The most common way to do that is to use indirect input, suchas the system clock. Other methods rely on direct human input.Google provides an interesting approach to generating random numbers through indirect input. Since the Internet isconstantly changing, with Web pages and domains being continuously created,modified, and deleted, databases such as Google provide an extremely
large dataset from which to seed a random number generator. In this context, a seed is a number input as a starting point for the generator's algorithms.Many patterns in the data
could be used to generate a seed, but theymust vary enough to produce true random numbers and the generation must besimple. Since Google's GUI is too uniform (the best seed is
constantlychanging), it is preferable to find a common denominator within thepage results that the search engine returns, from which to generate theseed. Every page of Google query results is different, as Google filters outduplicate pages, thereby [1]providing a dataset of unique elements.Most Web pages contain text, and this text differs from page to page, sopages returned by Google should be an excellent source for extracting seeds.If this assumption is incorrect, then stepping outside of the algorithmwould provide an even more random seed. One numeric pattern found intext is how many words there are. By executing a word count on the text ofeach page
resulting from a Google search, you can theoretically producea random seed.However, Google does not return randomly chosen result pages, butinstead produces search results based on its Page Rank equation. If the samequery were to be submitted
twice, it would most likely produce the sameorder of pages, which would make our generated seeds too predictable. Abetter algorithm might look at the lowest page of results and/or
searchfor different terms on each execution.To further avoid predictability, the algorithm should only make uniquequeries,
which would require a queue of search terms. Extracting oneword from each of the result pages and appending it to a word list easilycreates this. There are several problems with this method. First, more commonly usedwords will populate the list in larger numbers and are likely to beabout the same topics. Second,storing the queue on the computer would makeit simpler to calculate what number will be generated next (a largeimplementation flaw). Third, dependency on the Internet would preventnon-connected devices from generating random numbers, and the speedwith which connected devices could generate results would be dependent ontheir Internet connections (to compensate for slow page hosts, atimeout mechanism could be employed). These flaws mean that implementation is more of a neat idea than afeasible tool.
The [2]Google Random Number Generator that I wroteprovides a simple example of this method of generating random numbers.User input sers have to type to interact with most computers. Typing provides aconsistent medium from which to generate seeds, if the seed generatorwere to calculate the time difference between keystrokes and store itas the seed. Since every user must log
into the system, logins provide aperfect choke point to generate seeds.The process could easily recalculate a seed each time a user logs on(by replacing the old seed, adding the two seeds, or some other method).This would also allow the
seed to be generated before the random numbergenerator requires it. Similar systems are [3]already in use, thoughthey often combine other pseudo random sources such as the system
clock. Then what?
Once you've generated a seed, by whatever means, you must store itsomewhere on the system
so that it can be called upon to initiate therandom number generator (seeds are not generated at the same timerandom numbers are). It would not be sound to store the seed on any datastorage device, including removable media, as other
users could access theseed, allowing them to predict the random number that is generated.Therefore, the seed should be stored in protected memory.In order to access the protected memory and write the seed to it, aseed generator must
run with system level access, which is easily done bywriting a Linux or BSD system kernel module. Once the kernel has storedthe seed, it's a simple matter for a client program to
request the seedfrom the kernel and then pass it to the random number generator, whichwill run the seed through its algorithm.
If one cannot use a kernel module due to insufficient access or theinability to write a module, one could do the same job with aconstantly running process (service) that acts like a server, whose sole purposeis storing and returning the seed when it is called by another program.While running with a UID of 0, the client would use interprocesscommunication mechanisms to request the seed from the seed service.Theseed service could be started at system boot, most likely through[4]init.Final thoughts Pseudo random numbers may be good enough for some purposes, butapplications that need to be secure, like SSH or [5]GnuPG, must havetruly random seeds.It would be a simple matter to employ one of the above algorithms, orsome other one,
to generate truly random seeds in the operating system.Even establishing a standard hardware device to assist in thegeneration of random numbers would be preferable
to the pseudo random mechanismsin place today. While a hardware approach would likely be lesscost-effective for both the computer manufacturer and consumer,most ofthe computer friendly user market would likely accept the tradeoff.

Hope i continue it from here..

always i try to continue posting on this regularly but some how i cannot ! !

too lazy… i guess.. or not too committed to writing…
anyway.. i think i will certainly try to be more regular on this stuff !

Cheers !!

The Common Man-

Saw an intresting movie “DOMBIVALI FAST”

Director: Nishikant Kamat
Language: Marathi.

A story of a common man who loses his sanity in the everyday rut of life.
The story of Madhav Apte, the film’s protagonist who travels by the Dombivli fast everyday, is a tale which a common man can easily identify with.
An honest middle-class banker, Apte, disgusted with the system, loses his sanity and takes it upon himself to set things right, resorting to violent ways, thereby causing tension and strife to his wife and kids.
Great acting skills being portrayed again by none other than Sandeep Kulkarni (Dr.Sane in Shwaas) and all the other co-actors.
A hard but true view of the way the common man lives his life ..
watch the movie and you can understand it better..
Though the hero ( common-man ) in the film, is forced to take action against the system in a voilent way, ultimately to be remembered only in the police records..
is there no way that one can change the ongoing things..?

yes yes yes.. individuals need to change themselves ..

Let’s begin..

atleast give it a try once..