Analysis of the New Modules that Emotet Spreads

XIAOPENG ZHANG | March 11, 2019

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Just a few days ago, FortiGuard Labs published a research blog about a fresh variant of Emotet. When I wrote that blog, I had not yet detected any further malicious actions from its C&C server. However, I have continued to monitor its connections, and I finally received three new modules from its C&C server. I have now analyzed all of them, and I will now show you how they work on a victim’s system.

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OTHER ARTICLES

Artificial intelligence could help predict future diabetes cases

Article | March 31, 2020

A type of artificial intelligence called machine learning can help predict which patients will develop diabetes, according to an ENDO 2020 abstract that will be published in a special supplemental section of the Journal of the Endocrine Society. Diabetes is linked to increased risks of severe health problems, including heart disease and cancer. Preventing diabetes is essential to reduce the risk of illness and death. "Currently we do not have sufficient methods for predicting which generally healthy individuals will develop diabetes," said lead author Akihiro Nomura, M.D., Ph.D., of the Kanazawa University Graduate School of Medical Sciences in Kanazawa, Japan.

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Is investing in AI the highest ROI opportunity?

Article | December 8, 2020

This article explores why AI is the highest ROI opportunity. How revolutionary the technology is as Artificial Intelligence (AI) progresses with each passing day, its implementations are massive and almost every magazine and report has covered it. However, explaining its particular facets and how AI and its subsets of Machine Learning and Deep Learning can transform the way we view life has become imperative. Both businesses are or will be implementing AI in one way or another, the future of the corporate world. Investing in the right AI will deliver a really high ROI if you know what you’re doing. Entrepreneurs have nothing to do without their senses and the need for testing. Fortunately, the early stage of AI presents financial investors with a more advanced and profitable strategy and provides valuable strategic perspectives when building a new company. And small companies now generate reliable data from basic market fluctuations in stock to corporate announcements, and this is just the beginning. It is very difficult to select the important one when transmitting data. What do you intend to invest as a long-term investor? Any finance analysts have worked out how to deal with crucial data over time. At that point, they have stable tools that complement their portfolio of investments. AI can assess how early-stage start-ups perform for investors and capture the start-up opportunity for success by forecasting sales growth, market size, business expertise over all variables. It will evaluate the details in order to see if the statistics will actually make improvements. This means that investment-worthy startups can afford to start raising funds. Most investors use AI to make important investment choices. By integrating algorithms, data mining, and language processing, AI can create relationships and models to render proposals based on investor bends. As AI continuously absorbs new data, it will grow as it analyses new information and eventually becomes reliable and far-reaching. MotherBrain, the Machine Learning system developed by EQT Ventures to classify potential start-ups, applies its algorithm to historical data so as to potentially distinguish investment applicants. The platform uses details such as financial statistics, site rankings, device placement, and social media features that most businesses can physically test and evaluate. Surprisingly, if the invention of Motherbrain has already been accessed as it comes to seed and angel finance for businesses. Small investors, including angel investors, can also leverage the expertise and services accessible exclusively to historically significant firms. Another real downside for venture capitalists and angel investors is seeking pleasant investment targets before. This is a consistently strong and travel-intensive challenge. However, Machine Learning and Predictive Analytics are starting to shift the strategy. For other users, there are goods, such as Allegro, an intellectual algorithmic investment focused on AI that is absolutely free from human prejudice. This is a great investing product, but when the market is low on the promise, turn to an equity fund and a debt fund when the market is strong, meaning that the investments are safe. Indeed, finance managers who are compliant with the implications of the industry are often in a tough position where erroneous data exist or where market flaws occur. These defects may be rumors, financial theft, or innocent relationship slip-ups. Owing to the fact that financial markets are in touch with a constant flow of data, the vulnerability or interruption in the flow appears to be worse than the bad news. So, what is restricting the implementation of AI in conventional businesses following the pattern of hedge funds? The most important problems arise from massive financial and human capital investment. Probably the most commonly known inhibitor is the scarcity of available talent pools. As another field, there is a pool of detainees with expertise and experience in the field. The same happens to data scientists and AI practitioners, who usually expect a summary of observations into critical company behavior and goals. Pesa reports that more than 10,000 AI vacancies are available in the United States alone. Apart from a lack of expertise, investment companies need to respond to the priorities and desires of this unique pool of potential that binds the world of academics, academics, and Ph.D. students. 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AI has tremendous potential because it can go from engineering to tech in any field and can affect everything in between. Applications of AI are massive and it would not be possible to show only a few facets of it. But if you are an entrepreneur and you have a particular interest in getting to know the industry, then you can look at and evaluate it properly. Opportunities are massive, and technology is just going to grow because the world economies have been struck by a pandemic, one area that has exploded is technology.

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Build The Truth Block By Block

Article | April 12, 2021

There is nothing new about fake news. It has been in existence for centuries, albeit without the scaffolding of support from social media. From housewives’ tales to gossip magazines, the Trojan horse to the misinformation around the D-Day landing site, fake news has been a rite of passage. The Russian military made this into a fine art with “maskirovka,” the doctrine gaining superiority through deception, denial and disinformation. However, it was the 2016 U.S. presidential election that branded it with a legit identity and with such alacrity that today, I find myself questioning everything I read or hear about, no matter the veracity of the source. Fake news is a contagion that has the potency to be as disruptive as the coronavirus and must be fought with equal urgency. If you cannot solve the problem, manage it. The power behind fake news is big data — the quantum of data generated and its velocity of distribution. 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While AI will help us identify fake news, we need a preventive measure that nips it in the bud — a vaccination rather than medication. If tech helps in creating an issue, should tech help solve it too? Based on my years of experience in implementing these solutions for large enterprises and developing next-gen blockchain offerings with startups, I believe blockchain may just be the remedy we are looking for. Most technologists, however, do not consider blockchain to be a relevant or credible technology, with the primary criticisms being its lack of widespread adoption and its esotericism. But I believe the contrary. The vision of grandma-proof blockchain is becoming real — to create an inclusive global, scalable blockchain solution that can cater to every human need. Blockchain should be our weapon to effectively reduce and ultimately eradicate fake news. In blockchain, no single individual or group holds the authority, but everyone needs to approve; therefore, it enables the highest degree of integrity, privacy and security Blockchain is nothing but a distributed ledger that helps build trust in decentralized networks and that runs on the computing power of its participants. No single individual or group holds the authority, but everyone needs to approve; therefore, it enables the highest degree of integrity, privacy and security. This is accomplished by consensus algorithms. Each blockchain has adopted some form of it, and some even claim to have consensus that can prevent obfuscation of the truth even when faced with over 90% malicious intent. Blockchain technology enables a "shared single version of truth" across multiple entities based on two fundamental characteristics: immutability and traceability. Immutability Immutability is when a blockchain ledger has the capability to remain unaltered, effectively ensuring that any data on the blockchain cannot be altered — only built upon. Each block created has a unique identity and timestamp attached to it that builds a fortress around the data. Innovative upcoming blockchains use crypto-biometric identity to further buttress the fort. For example, Mediachain, a decentralized independent music library, uses blockchain to protect the originator’s authenticity by providing information about the creator, producer and lyrics to listeners. Steemit is a decentralized social media site that rewards content creators who also interact with other users. Each content piece or interaction is recorded on the immutable record by blockchain. And if news companies were to adopt blockchain — and organizations like the New York Times are already working on this — this is what we might expect: Journalists could create a block (an entry in a distributed ledger) and upload news via text, image or video. Editors would then create another new block with an edited version of the news, leaving the original block unchanged. Publishers (news agencies) would then publish the news based on their block and any changes that they might make. Each one of the participants is authenticated on the blockchain with a simple touch of their finger while protecting the fidelity of the news. Remember, entries cannot be changed, only built upon, and therefore, each change is recorded and allocated to a specific entity. For someone to “fake” the news, they would have to alter the data at each level. Infiltrating the high-security protocols would require considerable time and resource allocations. Traceability As mentioned, each block that is created has a distinct identity attached, preferably a crypto-biometric for added security and individual control. So, if fake news is generated and circulated through social media using blockchain as the base, it becomes easier to pinpoint the culprit while establishing the real source of the news. This would ascribe true content ownership to credible creators. Fake news creators are using advanced tech stacks to create deepfakes for digital deception. Generative adversarial networks (GANs) can help them to create deepfakes of images and videos that can even counteract or deceive advanced AI/ML algorithms. Of course, GANs are also being used to detect fake news now. If technology has helped fake news become compelling and believable, let’s use intelligent and available technology like blockchain to at least control it, if not eradicate it. Then again, if blockchain had existed in the medieval ages, we would have been denied the entertaining antics of Cersei Lannister and the wonderful blockbuster series that kept most of us enthralled!

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Article | March 4, 2020

A Gartner prediction says 85% of our interactions will be handled by bots by the end of 2020 diminishing the use of human power. Nearly 50% of businesses are planning to invest in chatbots rather than developing mobile apps. Chatbots aren’t new technologies. It has been here since the 1960s and the 1970s. An AI psychotherapist chatbot Eliza that mimicked human suffering with schizophrenia is one of the biggest examples of bot existence. A robot that chats; “hi there, we are here to help you with whatever you need.” This is the kind of typical friendly chatbot you’ll find popping out a traveling site or another site that you’re seeking for information

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We are a company driven by inquisitive data scientists, having developed a pragmatic and interdisciplinary approach, which has evolved over the decades working with over 100 clients across multiple industries. Combining several Data Science techniques from statistics, machine learning, deep learning, decision science, cognitive science, and business intelligence, with our ecosystem of technology platforms, we have produced unprecedented solutions. Welcome to the Data Science Analytics team that can do it all, from architecture to algorithms.

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