Archive for the ‘Quantum Computer’ Category

Cracking Dictionaries: What You Need to Know – Security Boulevard

Passwords are the standard authentication factor across sites and systems, but how we deal with passwords has changed over time. Today, password hashing is a critical security measure organizations should leverage to protect passwords. Because many organizations leverage password hashing to protect passwords, cracking dictionaries have evolved to crack those password hashes.

Here is a quick overview.

Cracking dictionaries are large lists of data, often cleartext strings, that can be used to crack passwords. These lists can include words in the form of dictionary words, common passwords, iterations of common passwords, and exposed passwords. They can also contain passwords that used to be hashed but have been subsequently cracked because they were stored in a weak password hashing algorithm.

As data breaches and password exposure increases year-over-year, more-and-more dictionaries of reverse-engineered hashed passwords are emerging. A password-cracking dictionary will often end up on the dark web for cybercriminals to exploit for various types of account takeover, paving the way for even more successful data breaches. They can also be used for cybersecurity research on user password habits.

There are plenty of methods a black hat hacker can choose to access user credentials. For example, they can use a form of social engineering to coax someone to hand over their credentials, like in a sophisticated phishing attack. But the easiest way is to use a cracking dictionary to gain access to an account. It is an easier and faster attack vector for account takeover.

Passwords have been a common feature of the internet landscape since its inception, and until recently, they were the only thing protecting your data. Cybersecurity experts recommend multi-factor account protection with things like biometrics, authenticators, and two-factor authentication, but many people still do not turn on MFA if it is optional because it takes longer to access their account. MFA is still not a standard for many websites and many internal systems. Passwords are still the standard authentication factor because no other method has proven to be easier yet, while also being more secure.

How we deal with passwords has also changed over time. Ten or fifteen years ago, it wouldnt have been unusual to walk past a colleagues computer and see a post-it note with their password scribbled on it stuck to their screen. Such a huge security mishap may seem shocking today, but it was common in a time when data breaches were rare and cybersecurity awareness was lacking. In the digital age, as major data breaches are happening almost daily, cybercriminals can get access to more passwords and are able to crack password hashes faster as technology advances.

This is where cracking dictionaries can offer a benefit. Bad actors can use entire databases of pre-cracked passwords, common passwords, leaked passwords, and standard dictionary words to try and hack into an account, without the time and complexity of a social engineering attack. This type of attack is quick so the victim often wont know of the unauthorized access until its already too late.

Over the years cybercriminals have developed a good understanding of what a typical password looks like, and they conduct their attacks based on this information. With a cracking dictionary, attackers apply the list of cracked passwords against a system and try to gain access.

But these dictionaries can also be useful for standard brute force attacks and password spraying attacks.

However, its not just hackers who use cracking dictionaries, legitimate security professionals do as well. Ethical hackers can also use this data to break hashing algorithms and conduct controlled data breaches to demonstrate how insecure a system is. This often happens in a professional setting, but there are also hash cracking websites available online where you can put in a hashed version of a password, and it will crack it, telling you the password.

Putting this hash into the website CrackStation, it returned the password almost instantly.

These websites use huge dictionaries of hashed data, some of this data is hashed common passwords, some is dictionary words, some is entire Wikipedia articles, and so on.

According to Forbes, just the first half of 2019 saw 3,800 publicly disclosed data breaches, amounting to 4.1 billion exposed records. What makes these figures even more alarming is that the number of breaches in 2019 increased by 54% compared to the previous year. The problem is, with each additional breach, more valuable data goes into the hands of these bad actors.

When a large company has their login credentials stolen, cybercriminals now have a huge set of data that provides insights, such as which passwords are the most popular, for example, which sports team names become common passwords in that area, and so on. These passwords get added to dictionaries. This data is still extremely valuable even when the password has been hashed.

Password hashing has long been considered a secure way of storing passwords. Hashing involves taking the native password, for example, Yellow3, and converting it into a string of numbers and letters of a fixed length. Hashing algorithms are designed to be difficult to crack and difficult to reverse engineer. All hashing algorithms are deterministic, which means if you input the same value, youll always get the same hashed output. However, they are also designed so that changing a single character the resulting hash will look completely different. This element of their design makes them considerably more difficult to reverse engineer, but the only thing standing in an attackers way is a large set of data and a powerful computer.

This is largely why data breaches are becoming so prevalent and increasing each year. Powerful computers and computer components are becoming increasingly affordable and as more hashed passwords are exposed, hackers get better at reverse-engineering these passwords. When quantum computing becomes more mainstream, it will become even easier to reverse engineer hashes.

One way to protect your password is to make it more difficult to crack.

A strong password policy can help organizations create harder-to-crack passwords. There are many different policies and recommendations around what makes a strong and safe password, but here are some common features of a strong organizational password policy:

Lastly, password monitoring can help organizations determine whether you have a strong password or not. Password screening software will scan your password and compare it to known common passwords, or passwords that have been exposed previously. If password monitoring tools indicate that a password has been exposed in a previous data breach, is a known password, or appears on password blacklists; then you should assume that hackers will try that password, and have potentially already cracked the hash for it.

The post Cracking Dictionaries: What You Need to Know appeared first on Enzoic.

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Cracking Dictionaries: What You Need to Know - Security Boulevard

Hypercash (HC) formerly (HCASH) Dual Chain Ecosystem on Quantum Computers and Disrupting Technology – The Cryptocurrency Analytics

H.Cash tweeted: HCash LIVE Seminar, Featuring Adam and Andrew, CEO & COO Join this awesome LIVE seminar and learn about quantum computers and how HCash is building industry-disrupting technology. When: March 28th, 9pm HKT, 1pm GMT, 2pm CET, 9am EST.

Andrew Wasylewicz, COO, of HCash in the past month, tweeted: The dangers of quantum hacking are very real and already available.

This might be one reason for why Wasylewicz seems to be excited about Europes first quantum computer to be built by IBM in Germany.

Adam Geri, CEO of HCash tweeted: Cardano Creator Charles Hoskinson Says Pandemic Will Pass, New Age of Tech Advancements Will Uplift Humanity.

The HCASH (HC)ecosystem has two chains, which consists of the HyperCash (HC) main chain and the Hyper Exchange (HX) chain derived from the main chain. The HyperExchange (HX) will work towards bridging communications between blockchains consisting of BTC and ETH as well as other blockchains like the DAGs.

The two chains run laterally. This dual ecosystem is structured to be interlinked, bifocal dual token. This dual-chain ecosystem can be used to solve interconnection, privacy, and security issues, which are prevalent in the current blockchain ecosystem.

Sydney Ifergan, the crypto expert, tweeted: Andrew Wasylewicz, when talking about exciting developments, stated that HCASH is here building and changing tech in the industry and universities around the world. The well-kept spirit indeed, despite the current crisis.

The Hcash (HC)is designed to provide for the exchange of information between the blockchains and non-blockchain networks. It is a highly secure network featuring quantum-resistant signature technology.

Hcash (HC)provides for a new standard of value by featuring post-quantum, signature technology. It has a PoW + PoS hybrid consensus. The community voting module is function ready.

Hcash can help create a new platform that will be able to be connected to different blockchains, thus permitting value and information to circulate freely between the networks, thus redefining the value of a blockchain.

The autonomous governance model is community-driven and therefore ensures efficient decision making, thereby creating a sustainable and inclusive development environment. The post-quantum lattice RingCT protocols helps in improving and optimizing ZK-snarks. Thus, clients have effective options to safeguard privacy.

The HCash Wallet is used to store funds in hot and cold multi-signature addresses on their original chain. It is accessible only by the user. It is managed by the RPPOM consensus mechanism.

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Hypercash (HC) formerly (HCASH) Dual Chain Ecosystem on Quantum Computers and Disrupting Technology - The Cryptocurrency Analytics

Quantum computing is right around the corner, but cooling is a problem. What are the options? – Diginomica

(Shutterstock.com)

Why would you be thinking about quantum computing? Yes, it may be two years or more before quantum computing will be widely available, but there are already quite a few organizations that are pressing ahead. I'll get into those use cases, but first - Lets start with the basics:

Classical computers require built-in fans and other ways to dissipate heat, and quantum computers are no different. Instead of working with bits of information that can be either 0 or 1, as in a classical machine, a quantum computer relies on "qubits," which can be in both states simultaneously called a superposition thanks to the quirks of quantum mechanics. Those qubits must be shielded from all external noise, since the slightest interference will destroy the superposition, resulting in calculation errors. Well-isolated qubits heat up quickly, so keeping them cool is a challenge.

The current operating temperature of quantum computers is 0.015 Kelvin or -273C or -460F. That is the only way to slow down the movement of atoms, so a "qubit" can hold a value.

There have been some creative solutions proposed for this problem, such as the nanofridge," which builds a circuit with an energy gap dividing two channels: a superconducting fast lane, where electrons can zip along with zero resistance, and a slow resistive (non-superconducting) lane. Only electrons with sufficient energy to jump across that gap can get to the superconductor highway; the rest are stuck in the slow lane. This has a cooling effect.

Just one problem though: The inventor, MikkoMttnen, is confident enough in the eventual success that he has applied for a patent for the device. However, "Maybe in 10 to 15 years, this might be commercially useful, he said. Its going to take some time, but Im pretty sure well get there."

Ten to fifteen years? It may be two years or more before quantum computing will be widely available, but there are already quite a few organizations that are pressing ahead in the following sectors:

An excellent, detailed report on the quantum computing ecosystem is: The Next Decade in Quantum Computingand How to Play.

But the cooling problem must get sorted. It may be diamonds that finally solve some of the commercial and operational/cost issues in quantum computing: synthetic, also known as lab-grown diamonds.

The first synthetic diamond was grown by GE in 1954. It was an ugly little brown thing. By the '70s, GE and others were growing up to 1-carat off-color diamonds for industrial use. By the '90s, a company called Gemesis (renamed Pure Grown Diamonds) successfully created one-carat flawless diamonds graded ILA, meaning perfect. Today designer diamonds come in all sizes and colors: adding Boron to make them pink or nitrogen to make them yellow.

Diamonds have unique properties. They have high thermal conductivity (meaning they don't melt like silicon). The thermal conductivity of a pure diamond is the highest of any known solid. They are also an excellent electrical insulator. In its center, it has an impurity called an N-V center, where a carbon atom is replaced by a nitrogen atom leaving a gap where an unpaired electron circles the nitrogen gap and can be excited or polarized by a laser. When excited, the electron gives off a single photon leaving it in a reduced energy state. Somehow, and I admit I dont completely understand this, the particle is placed into a quantum superposition. In quantum-speak, that means it can be two things, two values, two places at once, where it has both spin up and spin down. That is the essence of quantum computing, the creation of a "qubit," something that can be both 0 and 1 at the same time.

If that isnt weird enough, there is the issue of entanglement. A microwave pulse can be directed at a pair of qubits, placing them both in the same state. But you can "entangle" them so that they are always in the same state. In other words, if you change the state of one of them, the other also changes, even if great distances separate them, a phenomenon Einstein dubbed, spooky action at a distance. Entangled photons don't need bulky equipment to keep them in their quantum state, and they can transmit quantum information across long distances.

At least in the theory of the predictive nature of entanglement, adding qubits explodes a quantum computer's computing power. In telecommunications, for example, entangled photons that span the traditional telecommunications spectrum have enormous potential for multi-channel quantum communication.

News Flash: Physicists have just demonstrated a 3-particle entanglement. This increases the capacity of quantum computing geometrically.

The cooling of qubits is the stumbling block. Diamonds seem to offer a solution, one that could quantum computing into the mainstream. The impurities in synthetic diamonds can be manipulated, and the state of od qubit can held at room temperature, unlike other potential quantum computing systems, and NV-center qubits (described above) are long-lived. There are still many issues to unravel to make quantum computers feasible, but today, unless you have a refrigerator at home that can operate at near absolute-zero, hang on to that laptop.

But doesnt diamonds in computers sound expensive, flagrant, excessive? It begs the question, What is anything worth? Synthetic diamonds for jewelry are not as expensive as mined gems, but the price one pays at retail s burdened by the effect of monopoly, and so many intermediaries, distributors, jewelry companies, and retailers.

A recent book explored the value of fine things and explains the perceived value which only has a psychological basis.In the 1930s, De Beers, which had a monopoly on the world diamond market and too many for the weak demand, engaged the N. W. Ayers advertising agency realizing that diamonds were only sold to the very rich, while everyone else was buying cars and appliances. They created a market for diamond engagement rings and introduced the idea that a man should spend at least three months salary on a diamond for his betrothed.

And in classic selling of an idea, not a brand, they used their earworm taglines like diamonds are forever. These four iconic words have appeared in every single De Beers advertisement since 1948, and AdAge named it the #1 slogan of the century in 1999. Incidentally, diamonds arent forever. That diamond on your finger is slowly evaporating.

The worldwide outrage over the Blood Diamond scandal is increasing supply and demand for fine jewelry applications of synthetic diamonds. If quantum computers take off, and a diamond-based architecture becomes a standard, it will spawn a synthetic diamond production boom, increasing supply and drastically lowering the cost, making it feasible.

Many thanks to my daughter, Aja Raden, an author, jeweler, and behavioral economist for her insights about the diamond trade.

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Quantum computing is right around the corner, but cooling is a problem. What are the options? - Diginomica

Global Quantum Computing Market (2020 to 2025) – Investment in R&D of Technology and Development is Strategically Important – ResearchAndMarkets.com -…

DUBLIN--(BUSINESS WIRE)--The "Global Quantum Computing Market: Analysis By Solution Type (Hardware, Software, Full Stack), Application (Optimization, Simulation, Sampling, Machine learning), End User, By Region, By Country (2020 Edition): Market Insight, Competition and Forecast (2020-2025)" report has been added to ResearchAndMarkets.com's offering.

The Global Quantum Computing Market, valued at USD 101.12 Million in the year 2019 has been witnessing unprecedented growth in the last few years on the back of need for secure communication and digitization.

Quantum Computing is the use of quantum-mechanical phenomena and it promises to address problems that conventional computing solutions cannot handle. Increasing need for secure communication and digitization and race to make Quantum computer commercially feasible among the leading countries is one of the major reasons behind the increasing Quantum Computing market globally. Additionally, emergence of advance applications, need for secure communication and digitization is likely to supplement the Quantum Computing market value in the near future.

Among the solution type in the Quantum Computing market (Hardware, Software and Full Stack), all the three are gaining popularity globally and is expected to keep growing in the forecast period. Companies are likely to make major investment in hardware and software individually than on full stack.

Among Application (Optimization, Simulation, Sampling, Machine learning), optimization will be the mostly used application in Quantum computing and is expected to keep grow in future. And Machine learning will also show rapid growth. Among End User (Aerospace & Defense, BFSI, R&D, Healthcare, and Others), Aerospace and defense is leading the end user of quantum computing, and in future we can expect BFSI to use Quantum computing more. All the end-user sectors users are expected to use more of QC in the near future.

The North American market is expected to lead the global market in the forecast period because of intensive investment on research and development of Quantum computers. Additionally, support by government and race for quantum supremacy is expected to infuse market growth tremendously. Additionally, the major involvement of technology leaders such as IBM Corporation, Google, and Intel will be fuelling the growth of Quantum computing market.

Key Target Audience

Key Topics Covered:

1. Report Scope and Methodology

2. Strategic Recommendations

2.1 Focus should be on very strong technical team

2.2 Investment in R&D of technology and development.

3. Quantum Computing: Product Overview

4. Global Quantum Computing Market: Sizing and Forecast

4.1 Market Size, By Value, Year 2015-2019

4.2 Market Size, By Value, Year 2020-2025

4.3 Global Economic & Industrial Outlook

5. Global Quantum Computing Market Segmentation, By Solution Type

5.1 Global Quantum Computing Market: By solution type

5.2 Competitive Scenario of Global Quantum Computing Market: By solution type (2019 2025)

5.3 By Hardware - Market Size and Forecast (2015-2025)

5.4 By Software- Market Size and Forecast (2015-2025)

5.5 By Full Stack - Market Size and Forecast (2015-2025)

6. Global Quantum Computing Market Segmentation, By Application

6.1 Competitive Scenario of Global Quantum Computing Market: By Application (2019 & 2025)

6.2 By Optimization- Market Size and Forecast (2015-2025)

6.3 By Simulation - Market Size and Forecast (2015-2025)

6.4 By Sampling - Market Size and Forecast (2015-2025)

6.5 By Machine learning- Market Size and Forecast (2015-2025)

7. Global Quantum Computing Market Segmentation, By End User

7.1 Competitive Scenario of Global Quantum Computing Market: By End User (2019 & 2025)

7.2 By Aerospace and Defense- Market Size and Forecast (2015-2025)

7.3 By BFSI - Market Size and Forecast (2015-2025)

7.4 By R&D - Market Size and Forecast (2015-2025)

7.5 By Healthcare- Market Size and Forecast (2015-2025)

7.6 By others- Market Size and Forecast (2015-2025)

8. Global Quantum Computing Market: Regional Analysis

8.1 Competitive Scenario of Global Quantum Computing Market: By Region (2019 & 2025)

9. North Americas Quantum Computing Market: An Analysis

10. Europe Quantum Computing Market: An Analysis

11. Asia Pacific Quantum Computing Market: An Analysis

12. Rest of World Quantum Computing Market

13. Global Quantum Computing Market Dynamics

13.1 Global Quantum Computing Market Drivers

13.2 Global Quantum Computing Market Restraints

13.3 Global Quantum Computing Market Trends

14. Market Attractiveness

14.1 Market Attractiveness Chart of Global Quantum Computing Market - By Solution Type (Year 2025)

14.2 Market Attractiveness Chart of Global Quantum Computing Market - By Application (Year 2025)

14.3 Market Attractiveness Chart of Global Quantum Computing Market - By End User, Year-2025)

14.4 Market Attractiveness Chart of Global Quantum Computing Market - By Region, Year-2025)

15. Competitive Landscape

15.1 Market Share Analysis

15.2 Competitive Positioning (Leaders, Challengers, Followers, Niche Players)

16. Company Profiles (Business Description, Financial Analysis, Business Strategy)

16.1 Microsoft

16.2 Google

16.3 IBM

16.4 Intel

16.5 D-wave systems

For more information about this report visit https://www.researchandmarkets.com/r/raio0z

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Global Quantum Computing Market (2020 to 2025) - Investment in R&D of Technology and Development is Strategically Important - ResearchAndMarkets.com -...

3 AI ETFs Changing The World – Investorplace.com

A cornerstone of the technology that is shifting the way we go about our lives is artificial intelligence (AI). Also known as machine intelligence or machine learning, AI is the development of computer-driven technology used to perform functions and tasks that previously required human intelligence. That said, AI ETFs are reaping the benefits.

Within the sprawling AI universe, there are four pillars: reactive machines, limited memory, theory of mind and self-awareness. An example of reactive machines would be the famous Deep Blue chess-playing supercomputer from IBM (NYSE:IBM) while autonomous and self-driving vehicles would be examples of technologies in the limited memory category.

Everyday applications of AI include Apples (NASDAQ:AAPL) SIRI, Alphabet (NASDAQ:GOOG, NASDAQ:GOOGL) search algorithim and Amazons (NASDAQ:AMZN) Alexa.

Those are basic forms of AI, but they serve as evidence of the markets growth and utility. Investors can harness those trends and more by taking advantage of the opportunities in AI ETFs.

That said, lets take a look at a few.

Source: Shutterstock

Expense Ratio: 0.75% per year, or $75 on a $10,000 investment

For investors looking for disruptive technology exposure, the actively managed ARK Innovation ETF (NYSEARCA:ARKK) fits the bill. The fund has a wide reach that encompasses not just pure AI, but industries using this next generation technology.

ARKK companies run the gamut of genomic firms, fintech providers, next generation internet (shared work and related infrastructure) and industrial innovation, among others. Like some other ARK funds, ARKK is know for its large weight to Tesla (NASDAQ:TSLA), which is more than 10%. However, it features plenty of other high fliers with dominant positioning in their respective markets, including Square (NYSE:SQ) and Illumina (NASDAQ:ILMN).

Moreover, some of ARKKs allure as an AI ETF is realized through its exposure to the deep-learning market a truly compelling long-term trend.

In fact, ARK believes that deep learning will be more impactful than the Internet:

The Internet created roughly $10 trillion in global equity market capitalization in 20 years. We believe that deep learning will have 3x that impact, adding $30 trillion to global equity markets over the next two decades.

Source: Shutterstock

Expense Ratio: 0.68% per year

The Global X Robotics & Artificial Intelligence ETF (NASDAQ:BOTZ) is an established giant in the world of AI ETFs with over $1 billion in assets under management and a track record spanning nearly four years.

The fund holds 38 stocks and its top holding is Nvidia (NASDAQ:NVDA), a name with deep AI credibility. That stock accounts for the bulk of the semiconductor exposure in BOTZ. Underscoring this funds diversity, BOTZ features allocations to 14 industry groups, including chip makers.

Importantly, BOTZ provides exposure to increasing efficiencies in the AI universe. In turn, these are widely viewed as a vital long-term driver of AI investment outcomes.

In the past, training robotics was laborious and required time, capital, and engineering expertise, but AI simulators are becoming increasingly accurate at transferring learning to real world applications, according to Global X research. These simulators can run thousands of iterative processes in seconds, creating vast amounts of training data.

Source: Shutterstock

Expense Ratio: 0.40%

The Defiance Quantum ETF (NYSEARCA:QTUM) is one of the premier AI ETFs when it comes to accessing the deep and machine learning themes. The funds underlying benchmark the BlueStar Quantum Computing and Machine Learning Index provides robust exposure to those markets.

Home to 60 stocks, QTUMs index gives the fund a deeper bench than many competing AI ETFs. QTUM itself has 84 holdings.

QTUM components are involved in quantum computing, which data indicates QTUMs exposure to this burgeoning theme could be a positive long-term driver.

The global commercial quantum computing market is expected to reach $1.3 billion by 2027 at a compound annual growth rate (CAGR) of 52.9% from 2022 to 2027 and $161 million by 2022 from $33.0 million in 2017 at a CAGR of 37.3% for the period 2017-2022, notes BCC Research.

Todd Shriber has been an InvestorPlace contributor since 2014. As of this writing, he did not hold a position in any of the aforementioned securities.

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3 AI ETFs Changing The World - Investorplace.com