Internet Security: Is There Such A Thing As An Unbreakable Code?

For centuries, people have been searching for ways to keep information from getting into the hands of the public. Cryptography gave them an answer to that. Cryptography has been used, both in its basic and sophisticated forms to hide sensitive information. Egyptian hieroglyphics contain the first known and verified example of ancient cryptography. In our age where internet is so rampant and people want to keep their personal information private, cryptography is gaining traction. But one cycle exists for all cryptography. First, someone finds a good code and starts using it, it becomes effective for some time and eventually someone somewhere breaks the code, rendering it ineffective. Because of this, people ask: Is there such a thing as an unbreakable code?

 

To help them answer this question and solve it, scientists came up with the concept of one-way functions. One-way functions are functions that are easy to compute on the given inputs but hard to invert. That is, you cannot get the inputs from the output when reversing it. One-way functions could make good candidates for code that cannot be easily broken. That is, it would be close to impossible to find an algorithm that would revert the output. Unfortunately, one-way functions are just a conjecture. But that conjecture has been behind much tools that have been built in cryptography, authentication, personal identification, and other data security applications.

Getting a one-way function that is feasible has huge ramifications in the internet age. It could solve the Internet security problem for good. Industries such as banking, telecommunications, and e-commerce would be in a hurry to apply it. Yes, it has been elusive but that is not to say that there have not been candidates.

One well known candidate for one-way functions involves the multiplication and factoring of prime numbers. To get the outputs, two prime numbers are given to a function and their product is computed. This function takes a quadratic time complexity. It is really hard to factor out the prime numbers given the output although it can be done in exponential time. Another candidate is the Rabin function which gave rise to the Rabin cryptosystem on the assumption that the Rabin function is one-way.

The two candidates above can be broken though if a really good mathematician knows how to write an efficient algorithm.

This problem was what Rafael Pass, Professor of computer science at Cornell Tech wanted to tackle. He believes that if he could find a really good and valid one-way function, then all internet security problem could be solved. Internet encryption would be safe for all. According to his postulate, a good one-way function is like lighting a match. After a match is lit, you cannot get back the sticks. They are now ashes. So, a good one-way function would be an encryption scheme in which the decryption would lie only in the hands of the person who encrypted it. To get a candidate, he looked to mathematics and to a field that is unrelated to cryptography – quantifying the amount of randomness in a string of numbers, or what is known as the Kolmogorov complexity.

The Kolmogorov complexity of an object is defined as the length of the shortest computer program that can generate that object as an output. The Kolmogorov complexity of a string that has a definite pattern to it, like ababababababab, which is writing ab 7 times, can easily be computed. But what if you have some random string? asdwer2345tgdhncjmckkjkd? How do you compute the Kolmogorov complexity in an efficient manner? It has been found that the Kolmogorov complexity for such random strings is computationally close to impossible. What makes it more infeasible is computing the time bounds of such an algorithm.

Taking from this idea, Professor Pass focused his research on whether an algorithm can solve the time-bounded Kolmogorov complexity. If such an algorithm exists, his research posits, then all cryptography can be broken. On the other hand, if no efficient algorithm exists for such a time-bound Kolmogorov complexity, then one-way functions do exist and they can be found.

His research has implications for encryption schemes that are widely used in the Internet. Popular social media platforms use encryption to make their platforms more secure, banks in e-banking platforms rely on encryption being more unbreakable, and overall, we depend on making sure our internet lives are kept free from the prying public. So, Professor Pass’ theory is of great interest and only time will tell when a really good algorithm can be found based on his research that would make sure our Internet security is compromised no matter what platform we are using.

Source for this article was from Cornell University.

The Big Advantage Of Understanding Python Regex methods

Regular expressions, or regex, in python is fun. It is a very fast way to search through a string for a given pattern. Whenever I have to search and I am dealing with a string, the first thing I do is to look for a solution in regex. If you know regular expressions, so many string operations will be easy. 

My earlier post, How To Find A Match When You Are Dating Floats, explains the basic syntax and use of regex. In this post, I will highlight two functions in using regex that could confuse anyone unless they understand how they work. I will also add a third method that serves as an extension to the two. 

So, what are the two methods? They involve searching for a pattern in a string and the two methods are re.search() and re.match(). They both do the same thing: search for a pattern in a string. 

How python re.match() works.

The syntax of python re.match() is re.match(pattern, string, flags=0). What it does is take a pattern, as the first argument and a string as the second argument and search for the pattern in the string. You could add in other flags if you want to like make it search multiline or ignore string case. 

Now, the subtlety of re.match() is that it returns a match object only if the pattern is at the beginning of the string. Else, if it is not at the beginning of the string, it returns None. This is very important to remember because many unsuspecting pythonistas have found themselves thinking their pattern was wrong when their match returned None. 

Let me illustrate this with a little code. 

 

From the code above, I changed the patterns. The first pattern started from the beginning of the string, line 4, and it returned a match object when I printed the object. But the second pattern, line 10, did not start from the beginning of the string. When you ran the code, you would have noticed that it printed None for this case. 

So, always remember, re.match() searches for the pattern at the beginning of the string. 

How python re.search() works

Now, the second method for searching for patterns is re.search(). The syntax is similar to re.match() but different from re.match() because it searches for the pattern anywhere in the string. Even if the string is multiline, it would still return a match if the pattern exists in the string. But it does not return a match for all locations where the pattern can be found in the string. Rather, it returns only the first match for the pattern. 

 

If you run the code above, you can see that it both gets a match at the beginning of the string and in the middle of the string. It gets a match anywhere in the string but returns a match object that corresponds only to the first match. 

So, remember the difference between these two useful methods and don’t make the mistake of fighting your terminal trying to understand why a pattern you thought was well formed turned out not to be giving you a match object. 

The bonus python regex method. 

This is a bonus method because it is the one I use most often. It is quite different from the earlier two. Remember the earlier two only return a single match object or None where there is no match. The bonus method is python re.findall(). This method, re.findall(), will scan the string from left to right for matches and will return all the matched patterns as a list of strings. Not a match object, but a list of strings. That comes quite useful several times you might say. I just love this method. Here is some little code to illustrate this. 

 

Notice that I am using the same code but just changing the methods. 

So you can see how powerful re.findall() is. It gives you the ability to see all the matches in a list, something that re.match() and re.search() do not make possible. 

I limited this post to just the rudimentary functionalities of all three methods. You can experiment with them now that you know how they work. Make out your own code with various concepts. 

And don’t forget to subscribe to my blog so that you can get updated articles as I publish them daily. The submit textbox is at the topright.

A Look Into The Future Of Wireless Brain-Computer Interfaces.

 

Brain-computer interfaces (BCI) or what some call the mind-machine interface is a system of connecting a human brain through wires or wirelessly to a machine in order to generate signals from the brain, transmit them to a computer and through a bidirectional information flow mechanism allow the computer to control motor functions of the human brain.

The idea of a mind-machine interface was popular in the 1970s but it was not until the 1990s that prosthetic devices that were attached to the brain appeared to be viable. One of the concepts behind these mind-machine devices is to capture the electrical activity of the brain through electroencelography (EEG), transmit them to a machine and then the machine generates signals that are able to control the functioning of the brain. Professor Jacques Vidal of the University of California, Los Angeles (UCLA) is credited with inventing the first BCI machine. This concept has been applied in neuroprosthetics which is the use of artificial devices to replace the function of impaired nervous functions and brain related problems.

Thanks to this inventive and innovative approach, many persons who have lost their vision, motor movements, and other body functions such as in paralysis, can be able to live normal lives using these machines. A breakthrough in BCI devices and neuroprosthetics was accomplished in 2009 when Alex Blainey, an independent researcher living in the UK, was able to control a 5 axis robot arm using the Emotiv EPOC. These devices could help even someone who has lost control of their spinal cord through a disease or injury to regain full movement .

One drawback though was that not only do they require wires but they can generate energy in the brain of recipients. A wired BCI device can limit the movement of the person on whose brain it is implanted. They would not be free to move at ease. While a BCI device generating enormous energy could do harm to the person on whom it is implanted.

Now, these challenges could be a thing of the past as research has suggested that neural implants in the brain could be done wirelessly while generating just one-tenth of the power of existing devices.

A team of electrical engineers and neuroscientists from Stanford University successfully created a breakthrough device that could give recipients a wider range of movement while not exposing them to harm through the heat generated by the implanted device. To test their data, they tried out their experiment on three nonhuman primates and one human participant in a clinical trial. Then while the subjects performed several movements by communicating with the computer using their brains, the researchers took extensive measurements. The results of the research validated the hypothesis from the researchers that a wireless device for neuroprosthesis was possible and commercially viable while using less power.

Only time would tell when the actual device would be built that would actually achieve the goal of the research: a mind-machine device that was safe yet wireless. The future of wireless brain-computer interfaces is just within reach.