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      "body": "Technology is value-neutral. While often conceived as a driver of purposeful human action, it poses unparalleled dangers when in the wrong hands. Beyond AI narratives emphasizing robot armies taking over or machine learning revolutionizing entire industries, there’s a story often untold: the story of hackers silently pretending to be you.\n\nTechnological development has commoditized real time data analytics at scale, changing the name of the game across industries. Security is no exception. Armed with user data and affordable computational power, both security departments and hackers have evolved to a more agile state.\n\n### Users are the weakest link\nAs organizations became more effective in detecting traditional threats and malware, shifting fraudsters’ focus to perform “man-in-the-app” attacks and credential theft. Following the money trail, cybercriminals are increasing the sophistication of social engineering attacks, making account takeover fraud [an 8B problem](http://www.digitaltransactions.net/news/story/The-_8-Billion-Problem).\n\nA multiplicative system is only as strong as its weakest link. No matter how secure computer systems are to external attacks if users are voluntarily giving away their login credentials by walking into increasingly sophisticated traps all over the Internet.\n\nIn the realm of agile enemies and slow regulations, only [adaptive security solutions](https://www.threatmark.com/cognitive) can secure users at scale. Authentication methods that take into account what we do, rather than merely what we know, will soon be widespread. Then the question becomes: can fraudsters use AI to mimic user behavior such that it goes unnoticed by security departments’ AI systems?\n\n### The catalogue of ships\nLet’s dig a bit deeper to understand the opposing sides of the battle. On the one hand, AI-armed cyber-attackers have:\n- a larger attack surface (from the growing number of devices)\n- legitimate login credentials often straight from the user\n- physical insiders at organizations\n\nAnd on the cyber-defense side there is:\n- lots of historical user data\n- user-level behavior biometrics\n- ability to learn from previous attacks at other organizations\n\n### Data is the deciding factor\nWhile the strategic agenda of the attackers have shifted, changing the scale of the operation and the coordination of the attacks, organizations still have the biggest benefit: user data. Understanding and [detecting patterns in user behavior](https://medium.com/@5u2ie/intelligence-is-context-awareness-934fdfa34ffa#.6eeek9eoc) to such degree that no illegitimate entity can pose as the user could turn the tide of the ongoing battle against cybercrime.\n\nWhile organizations like [OpenAI](https://openai.com/about/) will hopefully ensure that no single organization alone will benefit from developing superintelligence, the emphasis will shift from having good algorithms to having proprietary data. I make a more elaborate case on that [here](https://medium.com/@5u2ie/beyond-machine-learning-the-3-pillars-of-cognitive-business-a7a96fcde202#.jdfaerg9d).\n\n------------------------------------------------------------------\nComment and share to discuss.\n[Get in touch](https://www.vyte.in/5u2ie) to talk about personalization and user modeling.\nFollow to learn more about everything cognitive, data and startups.\n[Refer](https://www.vyte.in/5u2ie)  apps who need real-time fraud detection / user authentication.",
      "json_metadata": "{\"tags\":[\"cybersecurity\",\"fraud\",\"ai\",\"data\",\"frauddetection\"],\"links\":[\"http://www.digitaltransactions.net/news/story/The-_8-Billion-Problem\",\"https://www.threatmark.com/cognitive\",\"https://medium.com/@5u2ie/intelligence-is-context-awareness-934fdfa34ffa#.6eeek9eoc\",\"https://openai.com/about/\",\"https://medium.com/@5u2ie/beyond-machine-learning-the-3-pillars-of-cognitive-business-a7a96fcde202#.jdfaerg9d\",\"https://www.vyte.in/5u2ie\"],\"app\":\"steemit/0.1\",\"format\":\"markdown\"}",
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      "title": "Fight AI with AI: The Data Warfare"
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      "author": "whimz",
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      "body": "![context awareness.jpeg](https://steemitimages.com/DQmYn59H9rHwpvLwxd2nHaXTPsPuxHdASeSFqhHaYDJkXt9/contextpic.jpeg)\n\n[Charlie Munger](https://www.farnamstreetblog.com/a-lesson-on-worldly-wisdom/)'s first rule of wisdom states:\n>“The first rule is you can’t really know anything if you just remember isolated facts and try and bang ’em back. If the facts don’t hang together in a latticework of theory, you don’t have them in usable form.”\n\nExperts. After years of hard work they internalize mental models of their respective fields; they understand both the fundamental principles and the in-depth intricacies of how concepts interrelate. They also grasp new ideas a whole lot quicker than others. Apparently that’s how Elon learns about new fields effectively.\n\nMental models are useful, but it’s pretty hard to build them. While the data gold rush has been well on its way since ~2012, to date it’s a non-trivial problem to interpret the terabytes of raw data some companies had piled up. And while there’s legitimate excitement about actionable insights and roadmap-shifting discoveries, let’s calm down and take a step back. The interpretation layer is missing. That latticework of theory.\n\n## Context is the key to personalization\nIn the realm of intelligent applications, that latticework is a general user model that serves as a basis to differentiate individual users from. Obsessed with engagement metrics, consumer-facing applications strive to optimize customer touch points that make for a good overall user experience. While general improvements like simplifying sign-up forms almost always lead to better conversion rates, it’s understanding the nuances of each user action in the context of the individual that makes a product stand out.\n\nThat requires building sophisticated models to explain what makes each individual different from the norm. Illuminated by the amount of raw user data one is gathering, it’s tempting to jump on the big data train. However, understanding the nuance in user behavior does not come from the size but rather the variance and the quality of the data set. A good strategy is to gather lots of potentially irrelevant periphery information from a multitude of (non-traditional) sources. It’s those who go the extra mile in identifying and aggregating quality contextual information who will win the personalization game.\n\nOften, the benefits to integrate various data systems aren’t clear. Also, personalization might not seem like a priority for product owners at the moment. However, beware that the so-called silo-mentality inevitably hurts businesses down the road. Divergent goals of different organizational units lead to a misalignment in incentives, and to that much-needed holistic user context to be missing.\n\n## The rise of context-aware security\nAn excellent example of a business case where understanding a nuanced user context has been of key importance is account takeover fraud, an $8B problem. Banks, online payment services and e-commerce stores have been relying on rule-based security measures that deny transactions at the slightest sign of fraud, without even attempting to understand the users’ context. This is not only a problem from a customer experience or a missed transactions perspective, but also because hackers are always one step ahead of those rigid rule-systems.\n\nReversing the problem has been the key to finding an adaptive solution: instead of modeling what an attack is like, security experts want to know what a user is not like. And that requires a precise understanding of legitimate user behavior with all of its obscure variations in a given context.\n\n## The signal and the noise\nIn an online setting, a sophisticated model of an individual consists of behavioral markers such as individual typing style, mouse movements and navigation profiles; purchasing habits, demographic information; device fingerprints, IP addresses, browser and network characteristics, along with a range of other fancy hacker stuff.\n\nRecognizing the rich contextual significance of individual user actions is only possible by utilizing all of the above-mentioned information that describes the user from multiple different angles. This is hard, and bringing in alternative information sources often requires lots of creativity and engineering swag. One of the frontrunners in the cognitive business space, [ThreatMark](www.threatmark.com/cognitive), takes pride in going out of their way to gather and aggregate heaps of non-traditional user information to build arguably the most sophisticated individual user models in the industry. They utilize these models to understand individuals to such degree that even yet-unseen anomalous behavior becomes apparent. That means that ThreatMark’s user authentication system knows which actions are likely to be within a normal range for an individual, even if they’ve never done those actions before (such as traveling to Bangkok or purchasing a yacht on a whim). That’s possible by interpreting actions in both the context of the individual and the general norm. Ultimately, it’s not about what a user knows, but about what a user does.\n\n## Context as a competitive advantage\nThe key takeaway is that among the terabytes of noisy data sets, deeply hidden patterns emerge if there is enough variation in the context. As mundane and profound as it sounds, the value and meaning of every piece of information changes based on the context. At times, potentially alarming signals get amplified. Other times, exceptions are made from rigid rules.\n\nThe most beautiful part is algorithmically understanding what is normal or optimal, without being explicitly told the conditions under which certain rules can be bent. Intelligence is beyond learning from past examples. It is about understanding the likely variation in certain patterns, much like experts, which lies at [the core of building a cognitive business](https://steemit.com/ai/@whimz/beyond-machine-learning-the-3-pillars-of-cognitive-business). By gathering lots of quality data that can serve as user context, companies pave their way to gaining an understanding of their individual users, allowing for intelligent, real-time personalization of features, UI elements or promotions. This user context serves as the core to understanding behavior, essentially like that latticework of theory Charlie mentions, but customized for each individual.\n\n------------------------------------------------------------------------------------------------------\nComment and share to discuss.\n[Get in touch](https://www.vyte.in/5u2ie) to talk about personalization and user modeling.\n[Follow](https://twitter.com/5u2iea) to learn more about everything cognitive, data and startups.\n[Refer](https://www.vyte.in/5u2ie) apps who need real-time fraud detection / user authentication.",
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      "parent_author": "",
      "parent_permlink": "context",
      "permlink": "security-is-context-awareness",
      "title": "Security is Context Awareness"
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  "timestamp": "2017-03-06T17:15:48",
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