Whats the Big Data

Etay Maor, IBM

Wired recently reported that hackers posted a “data dump, 9.7 gigabytes in size… to the dark web using an Onion address accessible only through the Tor browser.” The data included names, passwords, addresses, profile descriptions and several years of credit card data for 32 million users of Ashley Madison, a social network billing itself as the premier site for married individuals seeking partners for affairs.

“I want to show you the dark side of the net,” Etay Maor told me when we met last month at the IBM offices in Cambridge, Massachusetts. He then proceeded to give me a tour of the Internet’s underground, where cyber criminals and hackers exchange data, swap tips, and offer free and for-fee services. “Information sharing is a given on the dark side,” said Maor, “but for the good guys, it’s not that easy.”

Maor is a senior fraud prevention strategist at IBM and has watched the dark side of the Web at RSA, where he led the cyber threats research lab, and later at Trusteer, a cybersecurity startup which IBM has acquired in 2013 for a reported $1 billion. His focus is cybercrime intelligence, specifically malware—understanding how it is developed and the networks over which it is distributed. Maor is an expert on how cyber criminals think and act and shares his knowledge with IBM’s customers and also with the world at large by speaking at conferences and blogging at securityintelligence.com.

The Web is like an iceberg divided into three segments, each with its own cluster of hangouts for cyber criminals and their digital breadcrumbs. The tip of the iceberg is the “Clear Web” (also called the Surface Web), indexed by Google and other search engines. The very large body of the iceberg, submerged under the virtual water, is the “Deep Web”—anything on the Web that’s not accessible to the search engines (e.g., your bank account). Within the Deep Web lies the “Dark Web,” a region of the iceberg that is difficult to access and can be reached only via specialized networks.

Maor first demonstrated to me how much cybercrime-related information is available on the Clear Web. Simply by searching for spreadsheets with the word “password” in them, you can get the default password list for many types of devices and other things and places of interest to criminals. There is easily accessible information that may have been posted to the Web innocently or by mistake. But there is also a lot of compromised information (e.g., stolen email addresses and their passwords) available on legitimate websites that provide a Web location for dumping data.

Then there are forums for criminals, some masquerading as a benign “hacking community” or “security research forum,” promoting themselves like any other business and/or community, including a Facebook page, and covering their costs or even making some money by displaying ads. One such forum had 1,200 other people accessing it when Maor showed it to me, demonstrating how, with a few clicks of the mouse, you can find lists of stolen credit card numbers including all the requisite information about the card holder.

Maor proceeded to introduce me to Tor, the most popular specialized network providing anonymity for its users, including participants in the underground economy of the Dark Web.  It was developed in the 1990s with the purpose of protecting U.S. intelligence communications online by researchers at the US Naval Research Lab which released the code in 2004 under a free license. It has 2.5 million daily users, some with legitimate reasons to protect their identities, and others who are engaged in criminal activities.

Tor is based on Onion routing, where messages are encapsulated in layers of encryption. The encrypted data is transmitted through a series of network nodes called onion routers, each of which “peels” away a single layer, uncovering the data’s next destination. The sender remains anonymous because each intermediary knows only the location of the immediately preceding and following nodes. The final node in the chain, the “exit node,” decrypts the final layer and delivers the message to the recipient.

While Tor is used by people with legitimate reasons to hide their identity, it (and similar networks) also facilitates a thriving underground economy. This is where you can buy firearms, drugs, fake documents, prescription drugs or engage in pedophilia networks, human trafficking, and organ trafficking. Maor paraphrases Oscar Wilde: “Give a man a mask and he will show his true face.”

Tor is also home to rapidly growing “startups,” offering fraud-as-a-service. A decade ago, says Maor, cybercrime “was one-man operation.  Today, it’s teamwork.”  Furthermore, the whole process, from coding the malware to distributing it to working with money mules, can be easily outsourced.  Everything a cybercriminal might need is now available on the underground forums, some components of the process as a free download, others as a for-fee service, including cloud-based services with guaranteed service level agreements (SLAs). The menu of cybercrime options has grown beyond financial fraud tools, to include advanced targeting tools, Remote Access Tools (RATs), and health care and insurance fraud tools and services.

The explosion of data about us, our lives and our workplaces on the Clear Web has helped the denizens of the Dark Web circumvent traditional online defenses such as passwords. “Fifteen years ago,” says Maor, “it took a lot of work to breach a company. Today, I can go on Linkedin and find out exactly what is the structure of the company I’m interested in.” Knowledge of the reporting structure of a specific company helps criminals’ “social engineering” efforts, manipulating people into performing certain compromising actions or divulging confidential information. Once criminals get to know their targets (e.g., by connecting on Linkedin), the victims may open an email or attachment that will infect their computer and provide the desired access to the company’s IT infrastructure.

Cyber criminals are taking advantage of the abundance of data on the Web and its success at connecting and networking over 2 billion people around the world. 80% of cyber attacks are driven by highly organized crime rings in which data, tools and expertise are widely shared, according to a UN study on organized crime, generating $445 billion in illegal profits and brokering one billion-plus pieces of personally identifiable information annually.

Data and networking—aren’t they also great tools in the fight against cybercrime? Not so much. Corporations and security firms have been reluctant to share cybersecurity intelligence. Only 15% of respondents to a recent survey said that “participating in knowledge sharing” is a spending priority.

There have been some efforts to change that, such as the establishment of industry-specific Information Sharing and Analysis Centers (ISACs) and the cross-industry National Council of ISACs.  The Department of Homeland Security and other government agencies are working to promote specific, standardized message and communication formats to facilitate the sharing of cyber intelligence in real time. The Cybersecurity Information Sharing Act (CISA), a bill creating a framework for companies and federal agencies to coordinate against cyberattacks, is being debated in Congress.

Alejandro Mayorkas, the Deputy Secretary of Homeland Security recently said: “Today’s threats require the engagement of our entire society. This shared responsibility means that we have to work with each other in ways that are often new for the government and the private sector. This means that we also have to trust each other and share information.”

IBM has taken a big step towards greater engagement and information sharing when it launched in April the IBM X-Force Exchange. It is a threat intelligence sharing platform where registered users can mine IBM’s data to research security threats, aggregate cyber intelligence, and collaborate with their peers. IBM says the exchange has quickly grown to 7,500 registered users, identifying in real-time sophisticated cybercrime campaigns. “I’m a fan,” security guru Bruce Schneier responded when I asked him about X-Force Exchange.

“The security industry must share information, all the time, in real time,” says Maor. “It’s a change of mindset, but it has to be done if we want to have some sort of edge against the criminals.”

Originally published on Forbes.com

Source: DOMO

Everywhere you turn nowadays, you hear about the imminent triumph of intelligent machines over humans. They will take our jobs, they will make their own decisions, they will be even more intelligent than humans, they pose a threat to humanity (per Stephen Hawking, Bill Gates, and Elon Musk). Marc Andreesen recently summed up on Twitter the increased hubbub about the dangers of Artificial Intelligence: “From ‘It’s so horrible how little progress has been made’ to ‘It’s so horrible how much progress has been made’ in one step.”

Don’t worry. The machines will never take over, no matter how much progress will be made in artificial intelligence . It will forever remain artificial, devoid of what makes us human (and intelligent in the full sense of the word), and what accounts for our unlimited creativity, the fountainhead of ideas that will always keep us at least a few steps ahead of the machines.

In a word, intelligent machines will never have culture, our unique way of transmitting meanings and context over time, our continuously invented and re-invented inner and external realities.

When you stop to think about culture—the content of our thinking—it is amazing that it has been missing from the thinking of the people creating “thinking machines” and/or debating how much they will impact our lives for as long as this work and conversation has been going on. No matter what position they take in the debate and/or what path they follow in developing robots and/or artificial intelligence, they have collectively made a conscious or unconscious decision to reduce the incredible bounty and open-endedness of our thinking to computation, an exchange of information between billions of neurons, which they either hope or are afraid that we will eventually replicate in a similar exchange between increasingly powerful computers. It’s all about quantity and we know that Moore’s Law takes care of that.

Almost all the people participating in the debate about the rise of the machines have subscribed to the Turing Paradigm which basically says “let’s not talk about what we cannot define or investigate and simply equate thinking with computation.”

The dominant thinking about thinking machines, whether of the artificial or the human kind, has not changed since Edward C. Berkeley wrote in Giant Brains or Machines that Think, his 1949 book about the recently invented computers: “These machines are similar to what a brain would be if it were made of hardware and wire instead of flesh and nerves… A machine can handle information; it can calculate, conclude, and choose; it can perform reasonable operations with information. A machine, therefore, can think.” Thirty years later, MIT’s Marvin Minsky famously stated: “The human brain is just a computer that happens to be made out of meat.” Today, Harvard geneticist George Church goes further (reports Joichi Ito), suggesting that we should make brains as smart as computers, and not the other way around.

Still, from time to time we do hear new and original challenges to the dominant paradigm. In “Computers Versus Humanity: Do We Compete?” Liah Greenfeld and Mark Simes bring culture and the mind into the debate over artificial intelligence, concepts that do not exist in the prevailing thinking about thinking. They define culture as the symbolic process by which humans transmit their ways of life. It is a historical process, i.e., it occurs in time, and it operates on both the collective and individual levels simultaneously.

The mind, defined as “culture in the brain,” is a process representing an individualization of the collective symbolic environment. It is supported by the brain and, in turn, it organizes the connective complexity of the brain.  Greenfeld and Simes argue that “mapping and explaining the organization and biological processes in the human brain will only be complete when such symbolic, and therefore non-material, environment is taken into account.”

They conclude that what distinguishes humanity from all other forms of life “is its endless, unpredictable creativity. It does not process information: It creates. It creates information, misinformation, forms of knowledge that cannot be called information at all, and myriads of other phenomena that do not belong to the category of knowledge. Minds do not do computer-like things, ergo computers cannot outcompete us all.”

The mind, the continuous and dynamic creative process by which we live our conscious lives, is missing from the debates over the promise and perils of artificial intelligence. A recent example is a special section on robots in the July/August issue of Foreign Affairs, in which the editors brought together a number of authors with divergent opinions about the race against the machines. All of them, however, do not question the assumption that we are in a race:

• A roboticist, MIT’s Daniela Rus, writes about the “significant gaps” that have to be closed in order to make robots our little helpers and makes the case for robots and humans augmenting and complementing each other’s skills (in “The Robots Are Coming”).
• Another roboticist, Carnegie Mellon’s Illah Reza Nourbakhsh, highlights robots’ “potential to produce dystopian outcomes” and laments the lack of required training in ethics, human rights, privacy, or security at the academic engineering programs that grant degrees in robotics (in “The Coming Robot Dystopia”).
• The authors of The Second Machine Age, MIT’s Erik Brynjolfsson and Andrew McAfee, predict that human labor will not disappear anytime soon because “we humans are a deeply social species, and the desire for human connection carries over to our economic lives.” But the prediction is limited to “within the next decade,” after which “there is a real possibility… that human labor will, in aggregate, decline in relevance because of technological progress, just as horse labor did earlier” (in “Will Humans Go the Way of Horses?”).
• The chief economics commentator at the Financial Times, Martin Wolf, dismisses the predictions regarding the imminent “breakthroughs in information technology, robotics, and artificial intelligence that will dwarf what has been achieved in the past two centuries” and the emergence of machines that are “supremely intelligent and even self-creating.” While also hedging his bets about the future, he states categorically “what we know for the moment is that there is nothing extraordinary in the changes we are now experiencing. We have been here before and on a much larger scale” (in “Same as It Ever Was: Why the Techno-optimists Are Wrong”).

Same as it ever was, indeed. A lively debate and lots of good arguments: Robots will help us, robots could harm us, robots may or may not take our jobs, robots—for the moment—are nothing special.  Beneath the superficial disagreement lies a fundamental shared acceptance of the general premise that we are not different from computers, only have the temporary and fleeting advantage of greater computing power.

No wonder that the editor of Foreign Affairs, Gideon Rose, concludes that “something is clearly happening here, but we don’t know what it means. And by the time we do, authors and editors might well have been replaced by algorithms along with everybody else.”

Let me make a bold prediction. Algorithms will not create on their own a competitor to Foreign Affairs. No matter how intelligent machines will become (and they will be much smarter than they are today), they will not create science or literature or any of the other components of our culture that we have created over the course of millennia and will continue to create, in some cases aided by technologies that we create and control.

And by “we,” I don’t mean only Einstein and Shakespeare. I mean the entire human race, engaged in creating, absorbing, manipulating, processing, communicating the symbols that make our culture, making sense of our reality. I doubt that we will ever have a machine creating Twitter on its own, not even the hashtag.

I’m sure we will have smart machines that could perform special tasks, augmenting our capabilities and improving our lives. That many jobs will be taken over by algorithms and robots, and many others will be created because of them, as we have seen over the last half-century. And that bad people will use these intelligent machines to harm other people and that we will make many mistakes relying too much on them and not thinking about all the consequences of what we are developing.

But intelligent machines will not have a mind of their own. Intelligent machines will not have our imagination, our creativity, our unique human culture. Intelligent machines will not take over because they will never be human.

Originally published on Forbes.com