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best ethical hacking training in bangalore

3 Things You Can Do to Keep Your Website Safe from Danger!

Website security is extremely important if you want to keep your business running. Most small and midlevel firms do not do well in this department because they do not have a clue.

In this blog, we are going to give you 3 things you should do to keep your website safe.

Once you are able to establish a secure connection, leading your business from the front will become a lot easier. And if you think you do not need it, then imagine what you would do if someone breaches your website and holds your data at ransom.

So, now if you are ready, let us take a look:

1. Getting an SSL certificate

One of the primary steps you can take to protect your website is to get an SSL certificate for it. This will allow you to encrypt data end to end so that you do not get attacked and your data is safe from any sort of online aggression.

You could get in touch with your website developer and ask them to get it done for you. Having this work done will give your clients or website visitors the security you need.

2. Hire a ethical hacker

With top institutes carrying out ethical hacking training in Bangalore, finding a good match for your company will not be a big deal at all.

Ethical hackers are geared up with all kinds of network protection techniques that will help you keep your data and website outside the reach of phishing attacks and hackers.

The consulting ethical hacker for your company will be just the thing required to take your internet security to the next level.

top ethical hacking course in Bangalore

It will also give you cutting edge know-how, all of which will factor in when you offer your services to clients or customers!

3. Use enhanced authentication

Whenever you are granting access to your website for third party work, it would make sense to go for enhanced authentication to always maintain maximum security. If you do not have this ground rule laid out, then you might be looking at an enhanced authentication method.

To set this up, you need a trained personnel who has completed an ethical hacking course in Bangalore to get the job done.

Now that you have a fair idea of how you can keep your website away from danger, what are you waiting for? Get in touch with a ethical hacker today and set up your firm’s network security.

And if you are someone looking to start your career as an ethical hacker, then it is time to start now!


Best Cisco CCNA Training center in Kolkata

How to be Completely Prepared to Become a Network Manager!

Every company or enterprise has a network manager who works to keep the system running and help the firm to go about it their daily jobs. If you have always wanted this kind of a job, then you must ask yourself how you can be fully prepared for the job role.

In this blog, we are going to take a look at what it takes for you to be a network manager. If you want to find out what it is, then here’s a look at what you need to have! Let’s take a look:

1. Get a CCNA certification

One of the many things that you need to have if you want to become a network manager is a CCNA certification. To pass this composite exam, you need to get enrolled in a CCNA course in Kolkata.

Known as the Cisco Certified Network Associate Routing & Switching certification, this exam is designed to test your skill in installation, operation, and troubleshooting of a network.

Once you do have the right kind of education, getting through this certification will not be a problem at all.

2. Take an ethical hacking course

If you want to be a complete package for your company, then taking an ethical hacking course will increase your chances of proving to be a more valuable asset. Get into a cyber security course in Kolkata today and forge the necessary skills needed to make yourself the best.

CCNA Training in Kolkata

Ethical hacking is one of the up and coming fields in the corporate workforce and companies are always looking for candidates that give them the best of both worlds.

3. Handling real-time projects

Ethical hacking and CCNA are not things you can just understand theoretically. They need to practised under real circumstances so that you get the idea completely and are ready to face the challenges that are brought to you in your workplace.

This is one of the main reasons why you should always pick the real-time projects and the only way to do that during training is to make sure that your training institute has the means to provide you with it.

Now that you have a fair idea of the things you need to learn if you want to become a successful hacker, what are you waiting for? Get in touch with a top company with an elaborate course and training module today!

Once you are trained by the best, getting the edge in following your dreams will become an easy job!


ethical hacking course in bangalore

Ethical Hacking is NOT What Hollywood Portrays (It’s Even Better)

2007 might be the year! ‘Bourne Ultimatum’ and ‘Live Free or Die Hard’ hit the big screens, taking the cybercrime genre in Hollywood to newer heights and inspiring a large group of those in the 20s to take up ethical hacking as a legit career stream.

Since then, Hollywood has produced an awful lot of movies on cybersecurity, cementing the stature of hackers into this cool geek who can control the world from the basement of her/his home. Of course, made to sell, these movies do not necessarily portray ethical hacking in the right lights. Because while sure hackers are quite a genius bunch, they are more than just about saving the world from rogue bad guys. The reality edges the fictional portrayal. Ethical hacking is much more. It’s much better, recognized across the world among the white-collars. So, were you planning to opt it as your full-time career option, you couldn’t make a better choice. You’re in for a treat.

BIG Salary

Per a leading job portal, the average annual salary of a certified ethical hacker is $99,000. Even the new professionals, filling any entry-level post, can expect annual income as high as $95,000.

In India, Certified Ethical Hackers or CEHs make an annual average salary of around Rs 4,40,000. Versus the other traditional (and hyped) career paths, evidently, this stream promises financial rewards in abundance. To that, the salary also depends a lot on the organization and department you’re working with.

Top Organizations Are Looking For You

Per Accenture, the average cost of a malware attack is $2.4 million in money and 50 days in time. No wonder, even the small and medium-scale companies are investing extensively to secure their IT infrastructure. Then, of course, top brands, along with almost all government organizations around the world, are going big with their spending on cyber-security. This, collectively, have upshot the need and demand of ethical hackers at its all-time high right now. So, while on the macro level India is struggling with the 40-year high unemployment rate, with your skills and certification on ethical hacking, you can easily score high-paying jobs in renowned organizations.

ethical hacking training in bangalore

Less Competition

Yes, with technology (like IoT and VR) taking giant leaps in our lifestyle, cyber-security has the attention of all. However, still, the number of graduates exploring this niche as a legit career option is relatively low. Lack of awareness is a primary reason. The number of reputed institutes offering the right training is still in scarce. And then, admittedly, ethical hacking isn’t quite easy to learn. So, if you’re looking to become a professional ethical hacker, you wouldn’t have to deal with high competition, as is the case with the traditional courses, which can unlock you even better opportunities.

More Bad Guys, More Opportunities

Did you know 2,23,000 new malware samples are produced every day?

Not just that! More than 4,000 ransomware attacks occur every day which is expected to cost the world a whopping $11.5 billion by the end of 2019.

The number of opportunities in this market is only growing by the passing days. And it’s expected to continue growing in the coming years and decades. So, you can say goodbye to the idea of “career stagnation”. The career ladder here is quite long and less-crowded that you can climb at full pace.

Starting your professional life in a private company, you can quickly move to grab jobs in globally-recognized companies and government organizations. In short, while it sure is daunting to see the number of bad guys increasing, it also is good news for those who want to make a successful career in cybersecurity.

Enroll in Ethical Hacking Course in Bangalore

With benefits in aplenty, if you have a knack and interest in the cyber world, there’s no reason why you shouldn’t enroll in a good ethical hacking training Bangalore. Look around, do your research, and find a good institute. Learn, learn some more from top industry experts. Self-learn. Get certified. Become a certified ethical hacker. Get hired by the right employer. And expect an explosive career growth.


ceh course in bangalore

3 Ethical Hacking Misconceptions That You Need to Get Rid of!

Ethical hacking is becoming the front line of a possible cyber attack that all corporations are fearful of. These white hat computer professionals are dedicated to bust the loose ends and help you build a network that is truly safe for your workings.

However, there are still a lot of misconceptions about this profession. In this blog, we are going to take a look at what good CEH training in Bangalore can do to you. Want to find out? Let’s take a look now!

1. Ethical hacking only protects your data

This is one of the most dangerous myths about ethical hacking and should be busted immediately. Ethical hackers do a lot more than just protect your network data – they help you keep your funds safe.

Recently, an Indian minister who felt that Aadhar number security was not that important and tweeted it online, soon saw a Rupee 1 transaction from an unknown source to his bank account.

While this was to just a prove a point, it will not always be the case and the funds maybe a lot more!

2. The bad guys are better at this

One of the common misconceptions about ethical hacking is that a lot of people think that the bad guys are better at this. This is quite far from the truth and if you really want to know the truth – then many of the present white hat hackers were earlier rogues themselves.

best ceh course in bangalore

Ethical hacking is a way of understanding how to penetrate networks and keep yours safe. The knowledge required to make that happen is similar to the other end of the spectrum.

3. Always hire an ethical hacker from outside the company

A lot of people romanticise freelance ethical hackers because of how Hollywood movies treat them – as these alternative geniuses who do not care about the real world. However, having a full time ethical hacker for your company is important as well!

If you do it right, then the rest of things will fall into place for your company without a problem.

These are the 3 misconceptions that needed busting. Now that you have a better idea about the matter, get enrolled in a reputable CEH course in Bangalore and chase your dreams!


android penetration testing course in kolkata

What An Android Penetration Testing Course Teaches You!

Are you always wondering about how apps work and if it leaves your private information vulnerable? If these questions are on your mind and you like coding, then you should consider taking a course on it.

The android penetration testing training in Kolkata could be your doorway to making a fabulous entry in the industry of ethical mobile hacking. Want to know what these courses entail?

Let’s take a look now:

1.Decompiling code

This part of the training involves breaking down compiled codes in mobile applications to see if they pose any threat to your overall security.

Decompiling is an integral part of learning about android penetration and knowing it would make your understanding a lot more effective!

There are specialized trainers who can help you learn and understand decompiling as simply as possible. So, what are you still waiting for?

2.Analyzing mobile application real time

To understand the safety of a mobile application, analysis plays a huge part in the process. Whether the apps are running on the background, or the foreground, real time security threat analysis will give you a new point of view when dealing with applications.

Learning how to do the job perfectly however requires intricate training in app analysis and to know more about it, it is imperative for you to enrol for a android penetration testing course in Kolkata.

3.Learning how to spot the flaws

Untrustworthy apps can have loads of problems – from unnecessary permissions to insecure logging, content leak, data collection, and more. Learning how to spot them and deal with it accordingly is very important for a mobile application ethical hacker!

If you want to learn and understand the concept of how android apps work and figure out the way to fix them for your clients, then you need to take a course on the matter. There are many minute details in code and processes that make all the difference.

In today’s day and age, applications hold a lot of power when it comes to people’s information. Often users do not even see for themselves what kind of permissions are being asked for and whether they are even relevant to the particular app.

Being an android environment ethical hacker, you will be able to resolve all of these issues for your client and create the best situation for them – which is worth a lot!


ethical hacking course in kolkata

Why Your Company Needs Network Penetration Testing To Stay Secure Today!

The world is virtual today – from sensitive information to financial assets, everything is just a click way. And while that is an improvement from the earlier generations of communication, it definitely does not make you a fortress.

Security is one of the prime concerns, especially in the Indian market for most businesses. Mid and small size companies do not even consider the possibility of an attack to their system – and that remains a problematic understanding of the subject.

To get rid of such notions and provide cold hard assessments of real value, getting your network penetration testing done is a good idea.

What is network penetration testing?

A part of any good ethical hacking training in Kolkata, network penetration testing is a simulated attack on your system that is aimed at understanding the loopholes in your system and giving you an assessment that will help correct it.

But why would your company need one in the first place?

In this blog, we have listed out why getting a net pen testing or intrusion detection is in your best interest. Let’s take a look:

  1. To protect sensitive data

If your company handles sensitive data of clients in its systems and server, then a net pen testing in regular intervals is very important. It is within your list of responsibilities to ensure that all the data that is consentingly collected by you, remains within your organization and agreed third parties (if any).

  1. To understand your security loopholes

Whether it is your system security or app security, coding often entails loopholes that are to be tested if you want to evolve it further. If you do not challenge your security system enough, it will eventually become obsolete and leave you vulnerable to attack – something you should definitely look to avoid.

  1. To ensure best practises

Every digital environment has some best practices, and yours is no different. If your security is not compliant with these policies that you might end up in legal trouble from your clients – in case something goes wrong.

A net pen test will give you a clear insight into the matter and ensure that you are 100% within your boundaries where security is concerned.

Why is it better to get net pen testing done manually?

While there are software applications that do vulnerability analysis for your network, you cannot replace the instinct of a human brain. These professionals are highly trained in ethical hacking course in Kolkata and unlike software, it is not template driven.

There is real human choice to identify possible loophole areas and check out the weakest link. As the saying goes:

You are only as strong as your weakest link.

So, if you are business, get in touch with a net pen testing company today and find out your network strength. And for individuals who want to take up ethical hacking as profession, now is the time to get trained by the very best – look online to find out!


Artificial Intelligence

Category : Uncategorized

     Artifical Intelligence 

 Introduction:

Artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. In computer science AI research is defined as the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving.
The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring “intelligence” are often removed from the definition, a phenomenon known as the AI effect, leading to the quip in Tesler’s Theorem, “AI is whatever hasn’t been done yet.” For instance, optical character recognition is frequently excluded from “artificial intelligence”, having become a routine technology. Modern machine capabilities generally classified as AI include successfully understanding human speech, competing at the highest level in strategic game systems (such as chess and Go),autonomously operating cars, and intelligent routing in content delivery networks and military simulations.

artificial intelligence
History:

Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism, followed by disappointment and the loss of funding (known as an “AI winter”), followed by new approaches, success and renewed funding. For most of its history, AI research has been divided into subfields that often fail to communicate with each other. These sub-fields are based on technical considerations, such as particular goals (e.g. “robotics” or “machine learning”), the use of particular tools (“logic” or artificial neural networks), or deep philosophical differences.Subfields have also been based on social factors (particular institutions or the work of particular researchers).
The study of mechanical or “formal” reasoning began with philosophers and mathematicians in antiquity. The study of mathematical logic led directly to Alan Turing’s theory of computation, which suggested that a machine, by shuffling symbols as simple as “0” and “1”, could simulate any conceivable act of mathematical deduction. This insight, that digital computers can simulate any process of formal reasoning, is known as the Church–Turing thesis.[26] Along with concurrent discoveries in neurobiology, information theory and cybernetics, this led researchers to consider the possibility of building an electronic brain. Turing proposed that “if a human could not distinguish between responses from a machine and a human, the machine could be considered “intelligent”.[27] The first work that is now generally recognized as AI was McCullouch and Pitts’ 1943 formal design for Turing-complete “artificial neurons”
The field of AI research was born at a workshop at Dartmouth College in 1956. Attendees Allen Newell (CMU), Herbert Simon (CMU), John McCarthy (MIT), Marvin Minsky (MIT) and Arthur Samuel (IBM) became the founders and leaders of AI research. They and their students produced programs that the press described as “astonishing”computers were learning checkers strategies (c. 1954) (and by 1959 were reportedly playing better than the average human), solving word problems in algebra, proving logical theorems (Logic Theorist, first run c. 1956) and speaking English. By the middle of the 1960s, research in the U.S. was heavily funded by the Department of Defense and laboratories had been established around the world. AI’s founders were optimistic about the future: Herbert Simon predicted, “machines will be capable, within twenty years, of doing any work a man can do”. Marvin Minsky agreed, writing, “within a generation … the problem of creating ‘artificial intelligence’ will substantially be solved”.artificial itelligene

Basics

A typical AI perceives its environment and takes actions that maximize its chance of successfully achieving its goals.An AI’s intended goal function can be simple (“1 if the AI wins a game of Go, 0 otherwise”) or complex (“Do actions mathematically similar to the actions that got you rewards in the past”). Goals can be explicitly defined, or can be induced.
AI often revolves around the use of algorithms. An algorithm is a set of unambiguous instructions that a mechanical computer can execute.[b] A complex algorithm is often built on top of other, simpler, algorithms. A simple example of an algorithm is the following recipe for optimal play at tic-tac-toe:
If someone has a “threat” (that is, two in a row), take the remaining square. Otherwise,
if a move “forks” to create two threats at once, play that move. Otherwise,
take the center square if it is free. Otherwise,
if your opponent has played in a corner, take the opposite corner. Otherwise,
take an empty corner if one exists. Otherwise,
take any empty square.
Many AI algorithms are capable of learning from data; they can enhance themselves by learning new heuristics (strategies, or “rules of thumb”, that have worked well in the past), or can themselves write other algorithms. Some of the “learners” described below, including Bayesian networks, decision trees, and nearest-neighbor, could theoretically, if given infinite data, time, and memory, learn to approximate any function, including whatever combination of mathematical functions would best describe the entire world. These learners could therefore, in theory, derive all possible knowledge, by considering every possible hypothesis and matching it against the data. In practice, it is almost never possible to consider every possibility, because of the phenomenon of “combinatorial explosion”, where the amount of time needed to solve a problem grows exponentially. Much of AI research involves figuring out how to identify and avoid considering broad swaths of possibilities that are unlikely to be fruitful.[58][59] For example, when viewing a map and looking for the shortest driving route from Denver to New York in the East, one can in most cases skip looking at any path through San Francisco or other areas far to the West; thus, an AI wielding an pathfinding algorithm like A* can avoid the combinatorial explosion that would ensue if every possible route had to be ponderously considered in turn.


Problems

The overall research goal of artificial intelligence is to create technology that allows computers and machines to function in an intelligent manner. The general problem of simulating (or creating) intelligence has been broken down into sub-problems. These consist of particular traits or capabilities that researchers expect an intelligent system to display. The traits described below have received the most attention.
Reasoning, problem solving

Early researchers developed algorithms that imitated step-by-step reasoning that humans use when they solve puzzles or make logical deductions.By the late 1980s and 1990s, AI research had developed methods for dealing with uncertain or incomplete information, employing concepts from probability and economics.
Knowledge representation

Knowledge representation and knowledge engineering are central to classical AI research. Some “expert systems” attempt to gather together explicit knowledge possessed by experts in some narrow domain. In addition, some projects attempt to gather the “commonsense knowledge” known to the average person into a database containing extensive knowledge about the world. Among the things a comprehensive commonsense knowledge base would contain are: objects, properties, categories and relations between objects; situations, events, states and time;causes and effects;knowledge about knowledge (what we know about what other people know); and many other, less well researched domains. A representation of “what exists” is an ontology: the set of objects, relations, concepts, and properties formally described so that software agents can interpret them.

artificial intelligence
Planning

A hierarchical control system is a form of control system in which a set of devices and governing software is arranged in a hierarchy.
Intelligent agents must be able to set goals and achieve them. They need a way to visualize the future—a representation of the state of the world and be able to make predictions about how their actions will change it—and be able to make choices that maximize the utility (or “value”) of available choices.artificial intelligence
Learning

Machine learning, a fundamental concept of AI research since the field’s inception is the study of computer algorithms that improve automatically through experience.
Unsupervised learning is the ability to find patterns in a stream of input, without requiring a human to label the inputs first. Supervised learning includes both classification and numerical regression, which requires a human to label the input data first. Classification is used to determine what category something belongs in, after seeing a number of examples of things from several categories. Regression is the attempt to produce a function that describes the relationship between inputs and outputs and predicts how the outputs should change as the inputs change.
In reinforcement learning the agent is rewarded for good responses and punished for bad ones. The agent uses this sequence of rewards and punishments to form a strategy for operating in its problem space.

artificial  intelligence
Natural language processing

Natural language processing (NLP) gives machines the ability to read and understand human language. A sufficiently powerful natural language processing system would enable natural-language user interfaces and the acquisition of knowledge directly from human-written sources, such as newswire texts. Some straightforward applications of natural language processing include information retrieval, text mining, question answering and machine translation. Many current approaches use word co-occurrence frequencies to construct syntactic representations of text. Modern statistical NLP approaches can combine all these strategies as well as others, and often achieve acceptable accuracy at the page or paragraph level, but continue to lack the semantic understanding required to classify isolated sentences well. Besides the usual difficulties with encoding semantic commonsense knowledge, existing semantic NLP sometimes scales too poorly to be viable in business applications. Beyond semantic NLP, the ultimate goal of “narrative” NLP is to embody a full understanding of commonsense reasoning.

artificial intelligence
Perception

Machine perception is the ability to use input from sensors (such as cameras (visible spectrum or infrared), microphones, wireless signals, and active lidar, sonar, radar, and tactile sensors) to deduce aspects of the world. Applications include speech recognition,[115] facial recognition, and object recognition.[116] Computer vision is the ability to analyze visual input.
Requiring the AI to judge the relative likelihood and reasonableness of different interpretations, for example by using its “object model” to assess that fifty-meter pedestrians do not exist.

artifciial intelligence
Social intelligence

Moravec’s paradox can be extended to many forms of social intelligence. Distributed multi-agent coordination of autonomous vehicles remains a difficult problem. Affective computing is an interdisciplinary umbrella that comprises systems which recognize, interpret, process, or simulate human affects. Moderate successes related to affective computing include textual sentiment analysis and, more recently, multimodal affect analysis (see multimodal sentiment analysis), wherein AI classifies the affects displayed by a videotaped subject.In the long run, social skills and an understanding of human emotion and game theory would be valuable to a social agent.Similarly, some virtual assistants are programmed to speak conversationally or even to banter humorously; this tends to give naïve users an unrealistic conception of how intelligent existing computer agents actually are.

artificial intelligence
General intelligence

Many of the problems in this article may also require general intelligence, if machines are to solve the problems as well as people do. For example, even specific straightforward tasks, like machine translation, require that a machine read and write in both languages (NLP), follow the author’s argument (reason), know what is being talked about (knowledge), and faithfully reproduce the author’s original intent (social intelligence). A problem like machine translation is considered “AI-complete”, because all of these problems need to be solved simultaneously in order to reach human-level machine performance.
Embodied intelligence

This includes embodied, situated, behavior-based, and nouvelle AI. Researchers from the related field of robotics, such as Rodney Brooks, rejected symbolic AI and focused on the basic engineering problems that would allow robots to move and survive. Their work revived the non-symbolic viewpoint of the early cybernetics researchers of the 1950s and reintroduced the use of control theory in AI. This coincided with the development of the embodied mind thesis in the related field of cognitive science: the idea that aspects of the body (such as movement, perception and visualization) are required for higher intelligence.

artificial intelligence
Intelligent agent paradigm

An intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success. The simplest intelligent agents are programs that solve specific problems. More complicated agents include human beings and organizations of human beings (such as firms). The paradigm allows researchers to directly compare or even combine different approaches to isolated problems, by asking which agent is best at maximizing a given “goal function”The paradigm also gives researchers a common language to communicate with other fields—such as decision theory and economics—that also use concepts of abstract agents.

artificial intelligence
Artificial neural networks

Neural networks, or neural nets, were inspired by the architecture of neurons in the human brain. A simple “neuron” N accepts input from multiple other neurons, each of which, when activated (or “fired”), cast a weighted “vote” for or against whether neuron N should itself activate. Learning requires an algorithm to adjust these weights based on the training data; one simple algorithm (dubbed “fire together, wire together”) is to increase the weight between two connected neurons when the activation of one triggers the successful activation of another. The net forms “concepts” that are distributed among a subnetwork of shared[j] neurons that tend to fire together; a concept meaning “leg” might be coupled with a subnetwork meaning “foot” that includes the sound for “foot”. Neurons have a continuous spectrum of activation; in addition, neurons can process inputs in a nonlinear way rather than weighing straightforward votes. Modern neural nets can learn both continuous functions and, surprisingly, digital logical operations. Neural networks’ early successes included predicting the stock market and (in 1995) a mostly self-driving car. In the 2010s, advances in neural networks using deep learning thrust AI into widespread public consciousness and contributed to an enormous upshift in corporate AI spending; for example, AI-related M&A in 2017 was over 25 times as large as in 2015.
Today, neural networks are often trained by the backpropagation algorithm, which had been around since 1970 as the reverse mode of automatic differentiation published by Seppo Linnainmaa,and was introduced to neural networks by Paul Werbos.

artificial  intelligence
Applications

AI is relevant to any intellectual task. Modern artificial intelligence techniques are pervasive and are too numerous to list here. Frequently, when a technique reaches mainstream use, it is no longer considered artificial intelligence; this phenomenon is described as the AI effect.artificial intelligence

Healthcare

AI is being applied to the high cost problem of dosage issues—where findings suggested that AI could save $16 billion. In 2016, a ground breaking study in California found that a mathematical formula developed with the help of AI correctly determined the accurate dose of immunosuppressant drugs to give to organ patients.
X-ray of a hand, with automatic calculation of bone age by computer software
Artificial intelligence is breaking into the healthcare industry by assisting doctors. According to Bloomberg Technology, Microsoft has developed AI to help doctors find the right treatments for cancer. There is a great amount of research and drugs developed relating to cancer. In detail, there are more than 800 medicines and vaccines to treat cancer. This negatively affects the doctors, because there are too many options to choose from, making it more difficult to choose the right drugs for the patients. Microsoft is working on a project to develop a machine called “Hanover”.

artificial intelligence
Finance and economics

Financial institutions have long used artificial neural network systems to detect charges or claims outside of the norm, flagging these for human investigation. The use of AI in banking can be traced back to 1987 when Security Pacific National Bank in US set-up a Fraud Prevention Task force to counter the unauthorised use of debit cards. Programs like Kasisto and Moneystream are using AI in financial services.
Banks use artificial intelligence systems today to organize operations, maintain book-keeping, invest in stocks, and manage properties. AI can react to changes overnight or when business is not taking place. In August 2001, robots beat humans in a simulated financial trading competition.AI has also reduced fraud and financial crimes by monitoring behavioral patterns of users for any abnormal changes or anomalies.

artificial intelligence
Video games

In video games, artificial intelligence is routinely used to generate dynamic purposeful behavior in non-player characters (NPCs). In addition, well-understood AI techniques are routinely used for pathfinding. Some researchers consider NPC AI in games to be a “solved problem” for most production tasks. Games with more atypical AI include the AI director of Left 4 Dead (2008) and the neuroevolutionary training of platoons in Supreme Commander 2 (2010).artificial intelligence
Audit

For financial statements audit, AI makes continuous audit possible. AI tools could analyze many sets of different information immediately. The potential benefit would be the overall audit risk will be reduced, the level of assurance will be increased and the time duration of audit will be reduced.
Superintelligence

Are there limits to how intelligent machines – or human-machine hybrids – can be? A superintelligence, hyperintelligence, or superhuman intelligence is a hypothetical agent that would possess intelligence far surpassing that of the brightest and most gifted human mind. ‘’Superintelligence’’ may also refer to the form or degree of intelligence possessed by such an agent.
Technological singularity

If research into Strong AI produced sufficiently intelligent software, it might be able to reprogram and improve itself. The improved software would be even better at improving itself, leading to recursive self-improvement.[358] The new intelligence could thus increase exponentially and dramatically surpass humans. Science fiction writer Vernor Vinge named this scenario “singularity”.Technological singularity is when accelerating progress in technologies will cause a runaway effect wherein artificial intelligence will exceed human intellectual capacity and control, thus radically changing or even ending civilization. Because the capabilities of such an intelligence may be impossible to comprehend, the technological singularity is an occurrence beyond which events are unpredictable or even unfathomable.
Ray Kurzweil has used Moore’s law (which describes the relentless exponential improvement in digital technology) to calculate that desktop computers will have the same processing power as human brains by the year 2029, and predicts that the singularity will occur in 2045.

artificial intelligence
In fiction

The word “robot” itself was coined by Karel Čapek in his 1921 play R.U.R., the title standing for “Rossum’s Universal Robots”
Thought-capable artificial beings appeared as storytelling devices since antiquity,and have been a persistent theme in science fiction.
A common trope in these works began with Mary Shelley’s Frankenstein, where a human creation becomes a threat to its masters. This includes such works as Arthur C. Clarke’s and Stanley Kubrick’s 2001: A Space Odyssey (both 1968), with HAL 9000, the murderous computer in charge of the Discovery One spaceship, as well as The Terminator (1984) and The Matrix (1999). In contrast, the rare loyal robots such as Gort from The Day the Earth Stood Still (1951) and Bishop from Aliens (1986) are less prominent in popular culture.
Isaac Asimov introduce the Three Laws of Robotics in many books and stories, most notably the “Multivac” series about a super-intelligent computer of the same name.

artificial intelligence
Conclution

In short, most neural networks use some form of gradient descent on a hand-created neural topology. However, some research groups, such as Uber, argue that simple neuroevolution to mutate new neural network topologies and weights may be competitive with sophisticated gradient descent approaches. One advantage of neuroevolution is that it may be less prone to get caught in “dead ends”.

artificial intelligence


Monero

Monero Currently in Circulation Has Been Mined Using Malware

Category : Blog

Monero Currently in Circulation Has Been Mined Using Malware

Monero cryptocurrency currently in circulation has been mined using malware, and about 2% of the total daily hashrate comes from devices infected with cryptocurrency-mining malware. These numbers are the results of in-depth research of the coin-mining malware scene by security researchers from Palo Alto Networks.

The report, released June 11, has analyzed 629,126 malware samples that have been detected as part of coin-mining operations. The research didn’t analyze in-browser miners (cryptojackers), but only traditional malware families that infected desktops and servers since June last year, when there was a significant spike in coin-mining operations.

The research team at Palo Alto discovered because malware needs to be built directly into the source code of cryptocurrency mining pool. The malware also requires a Monero address under which it operates and handles any illegal funds generated from mining the cryptocurrency.

 

Monero

 

 

Monero is the most popular cryptocoin

According to researchers, 84% of all malware samples they’ve detected were focused on mining for the Monero cryptocurrency, by far the most popular coin among malware groups.

Because Monero-based coin-mining malware must embed in its source code the mining pool and Monero address through which the malware operates and collects ill-gotten funds, researchers have been able to track most of the money these groups generated on infected devices.

By querying nine mining pools (which allow third-parties to query their payment stats) with the 2,341 Monero addresses researchers found embedded in the 531,6663 malware samples that focused on mining Monero, they were able to determine the amount of funds these groups have made in the past year.

 

coin-mining

 

Malware groups made over $108 million worth of Monero

According to Palo Alto Networks researchers, criminal groups have mined an approximate total of 798,613.33 Monero coins (XMR) using malware on infected devices.

That’s over $108 million in US currency, just from coin-mining operations alone. This sum also represents around 5% of all the Monero currently in circulation —15,962,350 XMR.

Furthermore, since mining pools also reveal a miner’s hash rate —the speed at which a miner completes an operation— researchers were also able to determine the amount of Monero coin-mining botnets have been generating per day.

Researchers say that during the past year, infected devices were responsible for 19,503,823.54 hashes/second, which is roughly 2% of the entire hashing power of the Monero network.

 

Malware

 

 

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Ethereum

Ethereum “Giveaway” Scammers Have Tricked People Out of $4.3 Million

Category : Blog

Ethereum “Giveaway” Scammers Have Tricked People Out of $4.3 Million

Ethereum is a distributed public blockchain network. the Ethereum blockchain focuses on running the programming code of any decentralized application.

In the Ethereum blockchain, instead of mining for bitcoin, miners work to earn Ether, a type of crypto token that fuels the network.

Online crooks promoting fake “giveaways” have tricked people out of 8,148 Ether, currently worth around $4.3 million, according to statistical data compiled in EtherScamDB.

The EtherScamDB website was created by the team behind the MyCrypto wallet service for the purpose of tracking various types of online scams centering around the Ethereum platform and associated cryptocurrencies and assets.

For the past few months, the website has been inventorying various types of Ethereum scams, such as classic phishing sites that imitate legitimate apps and wallets, trust-trading sites that push inaccurate advice or recommendations, but also online giveaways scams that promise to multiply Ether funds if victims transfer crooks a small sum of money.

 

Ethereum

 

Twitter’s “Ether giveaway” scam problem

The latter category has recently become rampant on Twitter, and on a daily basis, the social network’s most popular tweets are often inundated by these “Ether giveaway” scams.

More precisely, this particular trend caught fire with crooks this past February after Bleeping Computer first reported that one particular scammer made $5,000 in one night just by posing as Elon Musk, John McAfee, and a few other celebrities on Twitter.

Soon after our report, scams of these types started to flood Twitter left and right, with crooks registering Twitter accounts with names similar to legitimate ones, and then posting misleading messages, asking users to donate funds to an Ethereum address to receive a multiplied sum as part of a limited offer giveaway.

 

scams

 

EtherScanDB tracks hundreds of fake giveway addresses

Some of these scams and the Ether addresses where crooks have been collecting “donations” for the fake giveaways have been tracked in the EtherScamDB.

According to a recent tweet by John Backus, founder of Bloom and Cognito, two blockchain-powered apps, crooks promoting these giveaway scams have made 8,148 Ether ($4.3 million) just from the Ether funds sent to the 468 Ethereum addresses tracked by the site.

This sum is obviously larger, since the website does not track all giveaway scams, but even so, this small statistics shows how big this problem is today.

 

blockchain

 

Twitter’s been slow to react

Twitter, in particular, has been slow to respond to users reporting ake accounts, sometimes taking days or weeks to suspend obvious clones. Nevertheless, with a limited support staff, and with all the hate speech and terrorist propaganda happening on the platform, it is somewhat understandable why Twitter has been slow to react.

In the meantime, spreading the word about this scam is probably the best way to educate users and remind them to pay attention to the Twitter handle from which these offers are being made.

But while some might think the consensus advice is to tell users to “pay attention to the Twitter handle pushing an Ethereum giveaway,” the actual sensible advice is to “not participate in giveaways” to begin with, since most of these are just plain ol’ scams.

 

Twitter

 

 

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Weight Watchers

Weight Watchers IT Infrastructure Exposed via No-Password Kubernetes Server

Category : Blog

Weight Watchers suffered a small Security Breach

Weight Watchers is the registered trademark of Weight Watchers International, Inc.

Just like many companies before it, weight loss program Weight Watchers suffered a small security breach after security researchers found a crucial server exposed on the Internet that was holding the configuration info for some of the company’s IT infrastructure.

The exposed server was a Kubernetes instance, a type of software for managing large IT networks and easily deploying app containers across multiple servers, usually on a cloud infrastructure.

Dozens of servers containing Weight Watcher’s data were left exposed after the company failed to password protect software used for managing application containers, according to German cybersecurity firm Kromtech.

An Amazon cloud infrastructure used by Weight Watchers was left vulnerable—46 Amazon S3 buckets in total—including logs, passwords, and private encryption keys, Kromtech found.

 

Weight Watchers

 

Weight Watchers ran a no-password Kubernetes instance

Researchers from German cyber-security firm Kromtech discovered that Weight Watchers forgot to set a password for the administration console of one of its Kubernetes instances.

This granted anyone knowing where to look (port 10250) access to this servers, without the need to enter a username and password.

All in all, the Kubernetes instances exposed an administrator’s root credentials, access keys for 102 of their domains, and 31 IAM users including users with administrative credentials and applications with programmatic access.

Weight Watchers added that its internal team and a third-party forensics company investigated the incident and that “each has independently confirmed that there was no indication that any personally identifiable information was exposed,” a spokesperson said.

The exposure was the result of a misconfigured Kubernetes instance, Kromtech said. Kubernates is a tool developed by Google for managing large numbers of applications. Notably, a Kubernetes instance on Telsa’s cloud infrastructure was hacked earlier this year, and then used by the perpetrators to mine cryptocurrency.

 

Kubernetes

 

Unclear what data was exposed

It is unclear if someone else besides the Kromtech team discovered this Kubernetes instance, but an attacker with access to this server would have been able to access a large part of Weight Watchers’ network.

It is also unclear what kind of data (user details?) these servers were storing, as the Kromtech team could not go wandering off inside Weight Watchers’ network without violating a slew of laws.

Diachenko and the Kromtech team said they reported the exposed server to Weight Watchers, who quickly remediated the issue, thanking the researchers.

 

Unclear Data

 

Weight Watchers claims it was a non-production network

“We really appreciate the community working to make us all safer,” a Weight Watchers spokesperson said in its response to Kromtech.

“We have confirmed the issue – a security group for a test cluster in our non-production account was misconfigured during testing. The issue should be resolved and keys should be revoked. We’ve also implemented some safeguards to protect against this issue from recurrence.”

But Kromtech disputes Weight Watchers’ explanation that this was a non-production account. Nonetheless, today, a Weight Watchers spokesperson stood by its initial statement.

“Last week, Weight Watchers received a report from security researchers related to the exposure of credentials in one non-production AWS account,” a company spokesperson told Bleeping Computer via email. “The account was in a testing environment clearly labeled ‘nonprod’ and is used only to test new services and features.”

“To be able to test and innovate securely, we keep test environments completely separate from production environments. Our internal team and a reputable third-party security forensics team have investigated the exposed account key scope and activity, and each has independently confirmed that there was no indication that any personally identifiable information was exposed,” the spokesperson told us.

Weight Watchers is certainly not the first company to have to deal with a leaky or non-protected server. Other companies that suffered a similar fate include Tesla, Honda, Universal, and Bezop, just to name a few.

 

Kromtech

 

 

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