Best Folder Encryptor Has Updated to Version 16.97

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The professional file and folder encryption software – Best Folder Encryptor has been updated to version 16.97. The new version fixed bug that the control board cannot be closed after a Flash- and Hiding-encrypted folder is opened because of misjudgment, made some improvements and optimization, and several minor bug fixes. For more details about Best Folder Encryptor, please read the following content.

More about Best Folder Encryptor 16.97

File Name: Best Folder Encryptor

Version: 16.97

File Size: 10.04MB

Category: Folder Encryption, File Encryption

Language: English

License: Trial version

System Requirements: Win XP/vista/Win 7/Win 8/Win 10

Released on: Oct.08, 2017

Download Address: http://www.dogoodsoft.com/best-folder-encryptor/free-download.html

What’s New in This Version:

– Fixed bug the control board cannot be closed after a Flash- and Hiding-encrypted folder is opened because of misjudgment.

– Minor bug fixes.

* The new software interface.

* Some improvements and optimization.

* Better display of encryption records.

* The new disk mirroring.

– Fixed bug that the encrypted folder cannot be closed after it is opened in some cases.

– Fixed bug with disguise failure after opening a disguised folder.

– Fixed bug with wrong record after a folder is encrypted.

+ Added the drag-and-drop feature to encrypt.

– Fixed bug displayed in the software interface.

– Fixed bug with duplicate records when performing First Aid for Flash- and Hiding-encryted folders.

* Better dealing with the error files when decrypting a Full-encrypted folder.

* Security and usability improvements.

Best Folder Encryptor Has Updated to Version 16.97

Why Choose Best Folder Encryptor

Best Folder Encryptor is a professional file and folder encryption software. It features superfast with high security and confidentiality. With the internationally advanced encryption algorithms, encryption methods and file system drivers, the encrypted files and folders cannot be decrypted without the correct password, and are prevented from copy, deletion or removal.

It is convenient to open and edit the encrypted folder or file with the Open feature, and you don’t have to re-encrypt the folder or file after use.

Besides, it supports many powerful features such as data shredding (file/folder shredding), completely hiding hard disks, disabling USB storage devices or set them as read-only, etc. All these make Best Folder Encryptor undoubtedly a flawless encryption software and the best helper.

Three Defenses to Solve the Problem of Storing Password

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Three Defenses to Solve the Problem of Storing Password

One of the biggest concerns around managing the passwords of an organization’s employees lies in how to store those passwords on a computer.

Keeping every user’s password in a plain text file, for example, is too risky. Even if there are no bugs to recklessly leak the passwords to the console, there’s little to stop a disgruntled systems administrator taking a peek at the file for pleasure or profit. Another line of defense is needed.

Let’s hash it out

Back in the 1970s, Unix systems began to ‘hash’ passwords instead of keeping them in plain text. A hash function is used to calculate a value (like a number) for each password or phrase, in such a way that, while the calculation itself may be easy, carrying out ‘in reverse’ – to find the original password – is hard.

By way of illustration, suppose we take an English word, and assign each letter a value: i.e. A=1, B=2, C=3 and so on. Each adjacent pair of letters in the word is then multiplied together, and added up. The “hash” of the word is this total so, using this method, the word BEAD has a hash value of (BxE) (ExA) (AxD) = (2×5) (5×1) (1×4) = 19. FISH scores 377, LOWLY scores 1101, and so on.

Using this system, the password file would store a number for each user, rather than the password itself. Suppose, for example, the password file entry for me has the number 2017. When I log in, I type in my password, the computer carries out the calculation above and, if the result is 2017, it lets me in. If, however, the calculation results in another value, access is denied.

As all that’s stored in the password file is the value 2017, and not my actual password, it means that if a hacker steals the entire contents of the file, there is still a puzzle to solve before they can log in as me.

Verbal attack

Although hashed passwords may be more secure than plaintext, there still remains a problem. The aim of a dictionary attack is to obtain a list of all English words and calculate their hash values, one by one; if my word is in there, it will be found eventually. However, while this may sound like a painful amount of work, the point is that it won’t just crack my password – it will crack every password.

An index is created in such an attack, which is then sorted by hash value, with individual words added to the index as their hash values are calculated: BAP goes on page 18, for example, BUN goes on 336, and CAT on page 23. ‘Reversing’ the hash function is then just a matter of looking up the word in the index – simply turn to page 2017 and you’ll find my password.

During World War II, the cryptanalysts at Bletchley Park did literally that: they worked out every possible way in which the common German word ‘eins’ could be enciphered using the Enigma machine, and recorded the Enigma settings as they went. The results were then sorted alphabetically into the so-called ‘eins catalogue’ meaning that, if the codebreakers could guess which encrypted letters represented the plaintext ‘eins’, they were then able to simply rummage through a battered green filing cabinet and pull out the key.

Salt in the wound

The next layer of defense against a dictionary attack is to use what’s called salt. A random variation to the calculation is applied differently for each user’s password in a salted hash scheme. One user could have A=17, B=5, C=13, and so on, for example, and another could have A=4, B=22, C=17. The password file would then store the salt (the A, B, C values) and the hash result. The computer could still carry out a quick calculation to check the password, but the variation means that the same password would have a different hash value for a different user.

It would therefore be impossible to compile a single dictionary that could successfully reverse the hash for everyone.

Finally, the best modern systems use a so-called iterated hash. The idea of this is to make the hash function itself harder to calculate by re-hashing the data thousands of times. This does slow down the computer checking the passwords, but anyone trying to search for a password will also be slowed by the same factor. The end result is essentially a computing power arms race between system administrators and hackers although, if you’re Amazon or Microsoft, it’s a fight you’re well placed to win.

Protecting user passwords is critical to the security of an organization’s confidential files and information. It’s vital therefore that steps are taken to protect passwords, encrypting them to such a degree that even the most determined criminal will find it impossible to decipher.

Quantum Computing will not be able to crack Encryption Keys until the 2030s

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In September, Satya Nadella announced that Microsoft is working on a quantum computer (QC) architecture. Since then, Intel also has announced it is working on a QC architecture. Microsoft and Intel join Alibaba, Google, IBM, Tencent and a host of academic and national research labs (including China, the European Commission, Russia and the US) in a quest to build working QC hardware and software that can solve real-world problems.

What is quantum computing and why will it make a difference?

Quantum Computing is a practical application of quantum physics using individual subatomic particles at sub-Kelvin temperatures as compute elements. It presents many research and development challenges, but the potential payoff is orders-of-magnitude faster compute acceleration for specific types of problems.

QC is like computing with a graphics processing unit (GPU) accelerator, in that GPUs and QC systems must be connected to a traditional processor that can run an operating system and schedule programs to run on the accelerator.

QC has the potential to quickly solve problems that are impossible to calculate in useful timeframes (or even human lifetimes) today.

One of the marquee potential applications for QC is breaking cryptographic keys—in other words, compromising security encryption that protects sensitive data. While a lot has been written about that, it is unlikely QC will be capable of cracking encryption keys until the 2030s. Here’s why it will take so long.

Challenge 1: Programming QC

QC architecture is based on “qubits” instead of binary computer bits. I am not a quantum physicist, so I’m not going to tell you how or why a qubit works. The analogy I use to describe how a QC program works is that multiple qubits interact like the waves generated by throwing a handful of small floating balls into a pool of water.

Assume that the distances between balls and the timing of when each ball hits the water are purposeful: the relative position of each ball and the order in which they hit the water is the program. The intersecting wave fronts between the balls then changes the up/down position of each of the balls in interesting patterns. At some point the position of each ball is measured, and that collection of measurements is the result of a QC program.

My analogy is easy to visualize but far too simple. It doesn’t explain how to write a QC program, nor does it tell you how to interpret the results.

However, that lack of connection to real-world programming talent and domain experience is actually just like real QC architectures! I’m not joking. Look at IBM’s Quantum Experience Composer, as an example. It looks like a music staff. But I’m not a musician, or in this case I’m not a quantum physicist who understands IBM’s QC system. For a mainstream software professional, it’s difficult to understand how to use IBM’s composer and how it is useful in solving a real-world problem. Programmers can place notes on the staff, but those notes won’t make any sense. Even after reading the detailed instructions, programmers will not be able to translate a problem in their real-world domain into a program in the QC domain.

The challenge in finding a quantum physicist who understands how to program a specific QC architecture and who understands the problem you want to solve is much worse than finding a Masters- or PhD-level data scientist to analyze all that big data you’ve been hoarding. It would be like trying to find a needle in a thousand haystacks.

Because of this challenge, QC ecosystems will have to create application programming interfaces (APIs) and then create libraries of useful functions with those APIs to hide QC complexity and enable programmers to use QC systems without knowing how QC systems work or how to compose programs for QC. For example, IBM’s QISKit enables QC acceleration through Python language APIs. However, those APIs still depend on programmers understanding quantum physics. The next step is to create libraries of useful QC acceleration functions.

Challenge 2: Getting a stable result from a QC program

One of the key challenges for QC is to make sure that the qubits are all working properly when a program starts and that they continue to work correctly until each qubit’s end-of-program state has been observed.

This is a lot harder than it sounds.

First, it requires freezing the qubits to nearly “absolute zero” just to have a fighting chance of keeping them in proper working order until a calculation is finished. Absolute zero (0°Kelvin / -459.67°Fahrenheit / -273.15°Celsius) is an ideal absence of any heat or movement at all; it is impossible to achieve in our universe, due to fundamental laws of thermodynamics. Qubits require 0.01°K / -459.65°F / -273.14°C, vanishingly close to absolute zero. That is a lot colder than deep space and expensive to achieve.

Because it is so difficult to get qubits to behave properly for long enough to finish a program, even at these low temperatures, QC architectures need to design error detection and correction into each qubit. Qubits with error detection and correction are interchangeably called a “fault-tolerant” qubits or “logical” qubits.

Directly observing a qubit ends a program. QC architectures must entangle extra qubits with a computing qubit, so a QC program can infer the state of a computing qubit without directly observing it (and thereby stopping a calculation). If an error is observed, then the erroneous qubit state can be corrected and the QC calculation completed.

Today, a lot of extra physical qubits are needed to create a logical qubit, on the order of 10s to thousands of extra physical qubits depending on the architecture. A single physical qubit is possible, if the structure of the qubit itself is fault-tolerant. Microsoft is claiming a breakthrough in materials-based fault-tolerant qubit design called “topological” qubits. Microsoft’s topological qubit contains only one physical qubit, based on a pair of Majorana fermion particles, but that breakthrough has not yet been confirmed by outside labs.

Challenge 3: Assembling and programing qubits as a QC accelerator

Today’s state-of-the-art is that no one has publicly shown even a single functional logical qubit. All demonstrations to-date have only used physical qubits. Public demonstrations are getting more complex as labs learn to orchestrate the manipulation and measurement of tens of physical qubits. For example, a Russian team implementing 51 physical qubits now leads the field.

Solving useful real-world problems, such as breaking 128-bit encryption keys, will require assembling and orchestrating thousands of logical qubits at near absolute zero temperatures. It will also require learning how to write complex programs for QC architectures. There are QC algorithmic frameworks for writing programs that can help speed up cracking encryption keys, such as Shor’s and Grover’s algorithms, but QC researchers still don’t understand how to frame those algorithms as an expression of qubit interactions (intersecting wave fronts in my example above).

Researchers are learning to build QC systems that can reliably orchestrate thousands of logical qubits. And they are learning how to usefully program those qubits. Then they must build a software ecosystem to commercialize their QC systems. Of course, it also requires building thousands of qubits.

Using graphics processing units (GPUs) compute as a model, QC must implement layers of software abstraction and easy to use development environments, so average programmers can use QC systems as compute accelerators without having to understand how to program any specific QC system.

Caution: QC objects through the looking glass are farther than they appear

There are some near-term applications for physical qubits: mostly solving optimization and quantum chemistry problems. Many of these problems can be solved using hundreds to thousands of physical qubits.

A raft of companies that are heavily invested in deep learning are also counting on physical qubits to accelerate deep learning training. Alibaba, Google, IBM, Microsoft and Tencent are all focused here. Integrating QC into the deep learning model creation process would be a neat way of side-stepping challenge #1 (programming), because QC programming would be hidden from human programmers by deep learning abstraction layers.

Many of the companies investing in physical qubits are striving to commercialize their QC architectures within the next five to ten years. This seems doable, given the level of investment by some of the larger competitors but still relies on several research breakthroughs, and breakthroughs cannot be scheduled.

All the QC researchers I have talked with say that shipping a commercial QC accelerator based on logical qubits is still at least 15 years away, pointing to commercialization in the early 2030s at the soonest. There is still a lot of fundamental science left to be done. Commercializing that science will take time. So too will building a programming ecosystem to make QC accelerators accessible to a wide range of programmers.

Breaking the code on quantum cryptography futures

The US National Institute of Standards and Technology (NIST) is working on detailed recommendations for a post-QC cryptography world. NIST issued a formal call for proposals last December; November 30, 2017 is the deadline for submissions. NIST’s intent is to issue draft standards on post-quantum cryptography in the 2023-2025 timeframe, about halfway through an industry consensus minimum 15-year QC development and commercialization period.

NIST has quantum physicists on staff. Many of its customers build and deploy systems that will spend decades in the field. Between now and NIST’s draft post-quantum cryptography standards, NIST published a concise summary of interim cryptographic safety measures.

QC will not break encryption keys this decade. Without massive research and development breakthroughs, the QC researchers I have talked with do not believe that QC will break encryption keys during the next decade, either.

It will happen at some point, but there are reasonable steps that can be taken now to keep data safe for at least a couple of decades. In a few years NIST, and presumably sibling governmental organizations across the globe, will publish stronger recommendations that will directly address post-quantum computing cryptographic safety.

Still confused? You are in good company. A key fact to remember is that QC is still at the beginning of a very long road to commercialization.

FBI couldn’t retrieve data from nearly 7000 mobile phones due to encryption

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FBI couldn't retrieve data from nearly 7000 mobile phones due to encryption

The head of the FBI has reignited the debate about technology companies continuing to protect customer privacy despite law enforcement having a search warrant.

The FBI says it hasn’t been able to retrieve data from nearly 7000 mobile phones in less than one year, as the US agency turns up the heat on the ongoing debate between tech companies and law enforcement officials.

FBI Director Christopher Wray says in the first 11 months of the fiscal year, US federal agents were blocked from accessing the content of 6900 mobile phones.

“To put it mildly, this is a huge, huge problem,” Wray said in a speech on Sunday at the International Association of Chiefs of Police conference in Philadelphia.

“It impacts investigations across the board – narcotics, human trafficking, counterterrorism, counterintelligence, gangs, organised crime, child exploitation.”

The FBI and other law enforcement officials have long complained about being unable to unlock and recover evidence from mobile phones and other devices seized from suspects even if they have a warrant. Tech firms maintain they must protect their customers’ privacy.

In 2016 the debate was on show when the Justice Department tried to force Apple to unlock an encrypted mobile phone used by a gunman in a terrorist attack in San Bernardino, California. The department eventually relented after the FBI said it paid an unidentified vendor who provided a tool to unlock the phone and no longer needed Apple’s assistance, avoiding a court showdown.

The Justice Department under US President Donald Trump has suggested it will be aggressive in seeking access to encrypted information from technology companies. But in a recent speech, Deputy Attorney General Rod Rosenstein stopped short of saying exactly what action it might take.

Wi-Fi’s Most Popular Encryption May Have Been Cracked

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Wi-Fi's Most Popular Encryption May Have Been Cracked

Your home Wi-Fi might not be as secure as you think. WPA2 — the de facto standard for Wi-Fi password security worldwide — may have been compromised, with huge ramifications for almost all of the Wi-Fi networks in our homes and businesses as well as for the networking companies that build them. Details are still sketchy as the story develops, but it’s looking like a new method called KRACK — for Key Reinstallation AttaCK — is responsible.

WPA stands for Wi-Fi Protected Access, but it might not be as protected as we’ve all been assuming. It looks like security researcher Mathy Vanhoef will present the (potentially) revelatory findings at around 10PM AEST Monday — although it’s been worked on for some time; Vanhoef first teased the revelations 49 days ago.

In the source code of a dormant website called Krack Attacks apparently belonging to Vanhoef, a description reads: “This website presents the Key Reinstallation Attack (KRACK). It breaks the WPA2 protocol by forcing nonce reuse in encryption algorithms used by Wi-Fi.” Vanhoef’s website also lists a paper to be released at CCS 2017 detailing the method for key reinstallation attacks, co-authored with security researcher Frank Piessens.

Part of the potential flaw in WPA could be that, the researchers have previously suggested in a 2016 paper, the random number generation used to create ‘group keys’ — the pre-shared encryption key shared on non-enterprise WPA/WPA2 wireless networks — isn’t random enough, and can be predicted.

With that prediction of not-so-random numbers in place, the researchers have demonstrated the ability to flood a network with authentication handshakes and determine a 128-bit WPA2 key through sheer volume of random number collection. Though it’s not yet clear, the re-use of a non-random key could allow an attacker to piggyback their way into a wireless network and then snoop on the data being transmitted within.

However, it may not be the apocalypse that some are suggesting. Given that the publication of this vulnerability has been withheld, a fix may already be in the works — or already completed — from major wireless vendors.

Most home and business wireless routers currently using WPA2 should be relatively easy to upgrade to address the potential security issue, but the millions of Internet of Things wireless devices already in the world will be hardest hit — devices that are un-upgradeable, but will still need to connect to insecure networks or using soon-to-be-deprecated methods. This could get messy.

Back in the day, the original Wired Equivalent Privacy (WEP) encryption standard was cracked to the point of off-the-shelf tools breaking it in as little as a minute.

If you go war-driving today around your city or town, it’s still likely you’ll find wireless networks ‘protected’ by WEP, because end users still don’t know that it’s unsafe. It was superseded by WPA and WPA2 in later years, but we might be on the search for a new Wi-Fi encryption method in the years to come: KRACK may mean that the fundamental privacy we expect of a network protected by WPA2 is no more.