What is Brute Force Search?

In computer science, brute-force search or exhaustive search, also known as generate and test, is a very general problem-solvingtechnique and algorithmic paradigm that consists of systematically enumerating all possible candidates for the solution and checking whether each candidate satisfies the problem's statement.

A brute-force algorithm to find the divisors of a natural number n would enumerate all integers from 1 to n, and check whether each of them divides n without remainder. A brute-force approach for the eight queens puzzlewould examine all possible arrangements of 8 pieces on the 64-square chessboard, and, for each arrangement, check whether each (queen) piece can attack any other.

While a brute-force search is simple to implement, and will always find a solution if it exists, its cost is proportional to the number of candidate solutions – which in many practical problems tends to grow very quickly as the size of the problem increases (combinatorial explosion).^[1] Therefore, brute-force search is typically used when the problem size is limited, or when there are problem-specific heuristics that can be used to reduce the set of candidate solutions to a manageable size. The method is also used when the simplicity of implementation is more important than speed.

This is the case, for example, in critical applications where any errors in the algorithmwould have very serious consequences; or when using a computer to prove a mathematical theorem. Brute-force search is also useful as a baseline method when benchmarking other algorithms or metaheuristics. Indeed, brute-force search can be viewed as the simplest metaheuristic. Brute force search should not be confused with backtracking, where large sets of solutions can be discarded without being explicitly enumerated (as in the textbook computer solution to the eight queens problem above). The brute-force method for finding an item in a table – namely, check all entries of the latter, sequentially – is called linear search.

What is Dictionary Attack?

In cryptanalysis and computer security, a dictionary attack is a form of brute force attack technique for defeating a cipher or authentication mechanism by trying to determine its decryption key or passphrase by trying hundreds or sometimes millions of likely possibilities, such as words in a dictionary.

What is Information-theoretic security?

Information-theoretic security is a cryptosystem whose security derives purely from information theory; the system cannot be broken even if the adversary has unlimited computing power. The cryptosystem is considered cryptanalytically unbreakable if the adversary does not have enough information to break the encryption.

An encryption protocol with information-theoretic security does not depend for its effectiveness on unproven assumptions about computational hardness. Such a protocol is not vulnerable to future developments in computer power such as quantum computing. An example of an information-theoretically secure cryptosystem is the one-time pad. The concept of information-theoretically secure communication was introduced in 1949 by American mathematician Claude Shannon, the inventor of information theory, who used it to prove that the one-time pad system was secure.^[1] Information-theoretically secure cryptosystems have been used for the most sensitive governmental communications, such as diplomatic cables and high-level military communications, because of the great efforts enemy governments expend toward breaking them.

Perfect security is a special case. For an encryption algorithm, if there is ciphertextproduced that uses it, no information about the plaintext is provided without knowledge of the key. If E is a perfectly secure encryption function, for any fixed message m, there must be, for each ciphertext c, at least one key ksuch that ${\displaystyle c=E_{k}(m)}$. It has been proved that any cipher with the perfect secrecy property must use keys with effectively the same requirements as one-time pad keys.^[1]

It is common for a cryptosystem to leak some information but nevertheless maintain its security properties even against an adversary that has unlimited computational resources. Such a cryptosystem would have information theoretic but not perfect security. The exact definition of security would depend on the cryptosystem in question.

There are a variety of cryptographic tasks for which information-theoretic security is a meaningful and useful requirement. A few of these are:

1. Secret sharing schemes such as Shamir's are information-theoretically secure (and also perfectly secure) in that having less than the requisite number of shares of the secret provides no information about the secret.
2. More generally, secure multiparty computation protocols often have information-theoretic security.
3. Private information retrieval with multiple databases can be achieved with information-theoretic privacy for the user's query.
4. Reductions between cryptographic primitives or tasks can often be achieved information-theoretically. Such reductions are important from a theoretical perspective because they establish that primitive ${\displaystyle \Pi }$ can be realized if primitive ${\displaystyle \Pi '}$ can be realized.
5. Symmetric encryption can be constructed under an information-theoretic notion of security called entropic security, which assumes that the adversary knows almost nothing about the message being sent. The goal here is to hide all functions of the plaintext rather than all information about it.
6. Quantum cryptography is largely part of information-theoretic cryptography.

Neural Processing Unit (NPU)

Know About Neural Processing Unit (NPU)

How much do you know about NPU? Let's introduce you with NPU and it's benefits and use of NPU in the mobile phone. 

NPU stands for Neural Network Processing Unit. "Neural network" may sound a bit confusing, but it seems to be more familiar with "Artificial Intelligence". NPU is the hardware on the phone that specialises in deep learning of artificial intelligence. Reading this, many of us may think of the first NPE on the Qualcomm Snapdragon 820. Indeed, NPE and NPU have similarities. NPE stands for “Neural Processing Engine”. Both NPE and NPU can handle similar tasks. But NPE is the software layer and NPU is the hardware level. If we choose a computer as an example, the graphics card is its image processor, which is hardware and frost, illusion, EGO, etc. are all game engines still software. Of course, Qualcomm's NPE is still done with the help of CPU and GPU. Because neural network algorithms and machine learning need to involve a huge amount of information processing, and current CPU / GPU cannot achieve such efficient processing capabilities, it is necessary to have a separate processing chip to do this.




ARM released the Cortex-A75 and A55 CPUs and the Mali-G72 GPU design earlier this year, all with more advanced machine learning algorithms, but not through the NPU. The key to ARM's ability to enhance SoC machine learning is the Computer Library, which includes a full set of capabilities for imaging and visual projects, as well as machine learning frameworks such as Google TensorFlow, which developers can use to recompile their needs. version. 
In addition to ARM, Qualcomm also has its own Hexagon SDK, which also includes a general matrix algorithm for machine learning, which enables more efficient DSP operation efficiency. In addition, the Qualcomm Symphony System Manager SDK provides an API that optimises computer vision, image and data processing, and low-level algorithms, as well as the common processing needs of smartphones.

Benefits -

The NPU can help the phone to recognise the shooting scene more accurately and quickly. Let the phone choose the most appropriate image processing algorithm, make the phone more accurate to the edge blur when the double camera background is blurred, and the recently very hot AR camera. NPU can significantly improve the speed of rendering and reduce power consumption. For example, with the NPU the mobile phone can transfer part of the voice and semantic recognition work to the mobile phone local, improve the performance of voice and semantic recognition and also improve the experience of voice interaction applications (such as voice input method, intelligent voice assistant etc) in mobile phones.

NPU Usually Used in Samrtphones for -

User Behaviour Learning: Analyse the user's usage habits by knowing where users are often doing things, in order to automatically implement certain functions for users in certain scenarios after a period of learning. Thereby optimising the memory storage of the mobile phone and making system resource optimization in time.
Image recognition: Image recognition is perhaps a term that has often been heard recently. In the past, our mobile phone couldn't know what was in the picture, except for our face. Now, with the help of NPU, the phone can know where you took a photo? After a long period of learning the habit of taking pictures, the mobile phone can analyse the shooting scene in real time during the shooting process, and set the camera parameters for different scenes, so as to achieve good photos.

What Is Brute Force Attack?

A brute-force attack is a cryptanalytic attack that can, in theory, be used to attempt to decrypt any encrypted data (except for data encrypted in an information-theoretically secure manner). Such an attack might be used when it is not possible to take advantage of other weaknesses in an encryption system (if any exist) that would make the task easier.

When password-guessing, this method is very fast when used to check all short passwords, but for longer passwords other methods such as the dictionary attack are used because a brute-force search takes too long. Longer passwords, passphrases and keys have more possible values, making them exponentially more difficult to crack than shorter ones.

Brute-force attacks can be made less effective by obfuscating the data to be encoded making it more difficult for an attacker to recognize when the code has been cracked or by making the attacker do more work to test each guess. One of the measures of the strength of an encryption system is how long it would theoretically take an attacker to mount a successful brute-force attack against it.

Brute-force attacks are an application of brute-force search, the general problem-solving technique of enumerating all candidates and checking each one.

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What is Certified Ethical Hacker?

Certified Ethical Hacker (CEH) is a qualification obtained by demonstrating knowledge of assessing the security of computer systems by looking for weaknesses and vulnerabilities in target systems, using the same knowledge and tools as a malicious hacker, but in a lawful and legitimate manner to assess the security posture of a target system. This knowledge is assessed by answering multiple choice questions regarding various ethical hacking techniques and tools. The code for the C|EH exam is 312-50. This certification has now been made a baseline with a progression to the C|EH (Practical), launched in March 2018, a test of penetration testing skills in a lab environment where the candidate must demonstrate the ability to apply techniques and use penetration testing tools to compromise various simulated systems within a virtual environment.
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