Symmetric or asymmetric encryption, that is the question!

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With the emergence of breaches and vulnerabilities, the need for hardware security has never been so paramount.

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Confidentiality — one of the three foundational pillars of security, along with data integrity and authenticity — is created in a digital system via encryption and decryption. Encryption, of course, is scrambling a message in a certain way that only the intended party can descramble (i.e. decrypt) it and read it.

Throughout time, there have been a number of ways to encrypt and decrypt messages. Encryption was, in fact, used extensively by Julius Caesar, which led to the classic type of encryption aptly named, Caesar Cipher. The ancient Greeks beat Caesar to the punch, however. They used a device called a “Scytale,” which was a ribbon of leather or parchment that was wrapped around a rod of a diameter, of which only the sender and receiver were aware. The message was written on the wrapping and unfurled, then sent to the receiver who wrapped on on the rod of the same diameter in order to read it.

 

Modern Encryption

Modern encryption is based on published and vetted digital algorithms, such as Advanced Encryption System (AES), Secure Hashing Algorithms (SHA) and Elliptic Curve Cryptography (ECC), among many others. Given that these algorithms are public and known to everyone, the security must come from something else — that thing is a secret cryptographic “key.” This fundamental principal was articulated in the 19th century by  Auguste Kerckhoffs, a Dutch linguist, cryptographer and professor.

Kerckhoffs’ principle states that a cryptosystem should be secure even if everything about the system, except the key, is public knowledge. In other words: “The key to encryption is the key.” Note that Kirchoffs advocated what is now commonly referred to as “open-source” for the algorithm. Point being, this open-source method is more secure than trying to keep an algorithm itself obscured (sometimes called security by obscurity). Because the algorithms are known, managing the secret keys becomes the most important task of a cryptographer. Now, let’s look at that.

Symmetric and Asymmetric

Managing the key during the encryption-decryption process can be done in two basic ways: symmetric and asymmetric. Symmetric encryption uses the identical key to both encrypt and decrypt the data. Symmetric key algorithms are much faster computationally than asymmetric algorithms because the encryption process is less complicated. That’s because there is less processing involved.

The length of the key size directly determines the strength of the security. The longer the key, the more computation it will take to crack the code given a particular algorithm. The table below highlights the NIST guidelines for key length for different algorithms with equivalent security levels.  You can see that Elliptic Curve Cryptography (ECC) is a very compact algorithm. It has a small software footprint, low hardware implementation costs, low bandwidth requirements, and high device performance. That is one of the main reasons that ECC-based asymmetric cryptographic processes, such as ECDSA and  ECDH, are now being widely adopted. The strength of the sophisticated mathematics of ECC are a great ally of all three pillars of security, especially encryption.

Not only is symmetric faster and simpler; furthermore, a shorter key length can be used since the keys are never made public as is the case with asymmetric (i.e. Public Key Infrastructure) encryption. The challenge, of course, with symmetric is that the keys must be kept secret on both the sender and receiver sides. So, distributing a shared key to both sides is a major security risk. Mechanisms that maintain the secrecy of the shared key are paramount. One method for doing this is called Symmetric Session Key Exchange.

Asymmetric encryption is different in that it uses two mathematically related keys (a public and private key pair) for data encryption and decryption.  That takes away the security risk of key sharing. However, asymmetric requires much more processing power. Unlike the public key, the private key is never exposed. A message that is encrypted by using a public key can only be decrypted by applying the same algorithm and using the matching private key.

A message that is encrypted by using the private key can only be decrypted by using the matching public key. This is sort of like mathematical magic. Some of the  trade offs of symmetric and asymmetric are summarized below.

Symmetric

• Keys must be distributed in secret
• If a key is compromised the attacker can decrypt any message and/or impersonate one of the parties
• A network requires a large number of keys

Asymmetric

• Around 1000 times slower than symmetric
• Vulnerability to a “man-in-the-middle” attack, where the public key is intercepted and altered

Due to the time length associated with asymmetric, many real-world systems utilize combination of the two, where the secret key used in the symmetric encryption is itself encrypted with asymmetric encryption, and sent over an insecure channel.Then, the rest of the data is encrypted using symmetric encryption and sent over the insecure channel in the encrypted format. The receiver gets the asymmetrically encrypted key and decrypts it with his private key. Once the receiver has the symmetric key, it can be used to decrypt the symmetrically encrypted message. This is a type of key exchange.

Note that the man in the middle vulnerability can be easily addressed by employing the other pillar of security; namely authentication. Crypto engine devices with hardware key storage, most notably Atmel’s CrypotoAuthentication, have been designed specifically to address all three pillars of security in an easy to design and cost-effective manner. Ready to secure your next design? Get started here.

What is Ambient Security?

New technology and business buzzwords pop up constantly. Hardly a day goes by that you don’t see or hear words such as “cloud”, “IoT,” or “big data.” Let’s add one more to the list: “Ambient security.”

You’ll notice that big data, the cloud, and the IoT are all connected, literally and figuratively, and that is the point. Billions of things will communicate with each other without human intervention, mainly through the cloud, and will be used to collect phenomenal and unprecedented amounts of data that will ultimately change the universe.

As everything gets connected, each and every thing will also need to be secure. Without security, there is no way to trust that the things are who they say they are (i.e. authentic), and that the data has not been altered (i.e. data integrity). Due to the drive for bigger data, the cloud and smart communicating things are becoming ambient; and, because those things all require security, security itself is becoming ambient as well.  Fortunately, there is a method to easily spread strong security to all the nodes. (Hint: Atmel CryptoAuthentication.)

Big Data

At the moment, big data can be described as the use of inductive statistics and nonlinear system analysis on large amounts of low density (or quickly changing) data to determine correlations, regressions, and causal effects that were not previously possible. Increases in network size, bandwidth, and computing power are among the things enabling this data to get bigger — and this is happening at an exponential rate.

Big data became possible when the PC browser-based Internet first appeared, which paved the way for data being transferred around the globe. The sharp rise in data traffic was driven to a large extent by social media and companies’ desire to track purchasing and browsing habits to find ways to micro-target purchasers. This is the digitally-profiled world that Google, Amazon, Facebook, and other super-disruptors foisted upon us.  Like it or not, we are all being profiled, all the time, and are each complicit in that process. The march to bigger data continues despite the loss of privacy and is, in fact, driving a downfall in privacy. (Yet that’s a topic for another article.)

Biggering

The smart mobile revolution created the next stage of “biggering” (in the parlance of Dr. Seuss). Cell phones metamorphosed from a hybrid of old-fashioned wired telephones and walkie-talkies into full blown hand-held computers, thus releasing herds of new data into the wild. Big data hunters can thank Apple and the Android army for fueling that, with help from the artists formerly known as Nokia, Blackberry, and Motorola. Mobile data has been exploding due to its incredible convenience, utility, and of course, enjoyment factors. Now, the drive for bigger data is continuing beyond humans and into the autonomous realm with the advent of the Internet of Things (IoT).

Bigger Data, Little Things

IoT is clearly looking like the next big thing, which means the next big thing will be literally little things. Those things will be billions of communicating sensors spread across the world like smart dust — dust that talks to the “cloud.”

More Data

The availability of endless data and the capability to effectively process it is creating a snowball effect where big data companies want to collect more data about more things, ad infinitum. You can almost hear chanting in the background: “More data… more data… more data…”

More data means many more potential correlations, and thus more insight to help make profits and propel the missions of non-profit organizations, governments, and other institutions. Big data creates its own appetite, and the data to satisfy that growing appetite will derive from literally everywhere via sensors tied to the Internet. This has already started.

Sensors manufacture data. That is their sole purpose. But, they need a life support system including smarts (i.e. controllers) and communications (such as Wi-Fi, Bluetooth and others). There is one more critical part of that: Security.

No Trust? No IoT! 

There’s no way to create a useful communicating sensor network without node security. To put it a different way, the value of the IoT depends directly on whether those nodes can be trusted. No trust. No IoT.  Without security, the Internet of Things is just a toy.

What exactly is security? It can best be defined by using the three-pillar model, which (ironically) can be referred to as “C.I.A:” Confidentiality, Integrity and Authenticity.

CIA

Confidentiality is ensuring that no one can read the message except its intended receiver. This is typically accomplished through encryption and decryption, which hides the message from all parties but the sender and receiver.

Integrity, which is also known as data integrity, is assuring that the received message was not altered. This is done using cryptographic functions. For symmetric, this is typically done by hashing the data with a secret key and sending the resulting MAC with the data to the other side which does the same functions to create the MAC and compare. Sign-verify is the way that asymmetric mechanisms ensure integrity.

Authenticity refers to verification that the sender of a message is who they say they are — in other words, ensuring that the sender is real. Symmetric authentication mechanisms are usually done with a challenge (often a random number) that are sent to the other side, which is hashed with a secret key to create a MAC response, before getting sent back to run the same calculations. These are then compared to the response MACs from both sides.

(Sometimes people add non-repudiation to the list of pillars, which is preventing the sender from later denying that they sent the message in the first place.)

The pillars of security can be  implemented with devices such as Atmel CryptoAuthentication crypto engines with secure key storage. These tiny devices are designed to make it easy to add robust security to lots of little things – -and big things, too.

So, don’t ever lose sight of the fact that big data, little things and cloud-based IoT are not even possible without ambient security. Creating ambient security is what CryptoAuthentication is all about.