Andrey

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Symantec: Using Machine Learning to Improve Malware Research
Andrey
Posted on November 12, 2018 at 7:18 pm
As cybercrime grows, the defenders found a new tool for their arsenal: Machine Learning. Symantec implemented a creative approach that harnesses the power of ML to detect sophisticated actors in cyberspace.

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On November 14, 2018, Andrey commented on The Election Security Challenge: Why Voting-Machine Vendors Resist Open Innovation :

Thanks for the article – this phenomenon has changed the lives of everyone who lives in this country for at least 4 years.
However, I disagree that open innovation does not apply to ES&S. History shows that the more “proprietary” a system is – the more it is open for hacking & manipulation. Most ATMs in the world, for example, still run Windows XP – an operating system has stopped receiving security updates in 2014: https://hackernoon.com/do-atms-running-windows-xp-pose-a-security-risk-you-can-bank-on-it-1b7817902d61. IoT is another example of a platform that is widely hackable – there’s a funny IoT dishwasher example: https://motherboard.vice.com/en_us/article/pg9qkv/a-hackable-dishwasher-is-connecting-hospitals-to-the-internet-of-shit.
When a vendor opposes penetration testing of its system, everyone should be concerned. The best (and cost-effective way) to find vulnerabilities is to welcome hackers. This is what all the big tech companies are doing today with their bug bounty programs, and what ES&S should do. You make a compelling case for open innovation in security, and I think that applies to everyone.

On November 14, 2018, Andrey commented on Detroit and the Future of the Automobile: Will Additive Manufacturing Help GM Beat Silicon Valley at its Own Game? :

Thanks for you article! As I am unfamiliar with the automotive industry, it was an interesting read.
Regarding your question, I think GM should be careful with continuing to change its culture. Embracing additive manufacturing has worked for them and has shown great results, and I think they should keep focusing on that direction for now. Integrating too much too fast will cause confusion and inconsistencies, which will reflect in either delayed production or real faults in production cars. It seems GM is trying to bridge between tradition and innovation, and it should let the feedback loops settle before running too fast. As you’ve mentioned, the competition is going through similar changes, so it would not be losing too much of a relative advantage.

On November 14, 2018, Andrey commented on Additive Manufacturing at GE Aviation :

Love your article! Creating aircraft parts using 3D printers would have been unbelievable just a few years ago. I hope their new CEO will realize the full potential of this manufacturing process.
I wonder why GE decided to focus on additive manufacturing specifically in the aerospace industry. As a conglomerate, I would assume they could bring this innovative approach to all of their divisions. Do you see any reason why aerospace is an especially beneficial field to start from? Where else in GE do you see this process benefitting?

On November 14, 2018, Andrey commented on SenseTime and Public Safety :

Thanks for the article! This is a hard dilemma, and its impact only grows stronger as the days go by.
I believe companies should be held liable for the use of their products. On one end of the spectrum, there are regulations imposed on arms dealers especially for that purpose. Since the law always lags technology, I’m unaware of such regulations yet, but they are sure to come. Such products, if they are used for public defense purposes, should be regulated. The root problem is that we can’t trust the Chinese government to have any checks and balances on the use of such technology.
I call and raise your question: next year, when a criminal group hacks the platform to spy on their targets – who will be held liable? The government or SenseTime?

On November 14, 2018, Andrey commented on American Express has Struck Gold with Machine Learning :

Thanks for the post! Credit card companies have a huge source of data, and I believe they can learn a lot (even maybe too much) about an individual through data science.
I think the point you touched on credit card fraud is especially important. To augment on the issue – in 2018, it is expected that total losses due to credit card fraud would amount to $19B globally (https://www.nasdaq.com/article/credit-card-fraud-and-id-theft-statistics-cm520388). Considering the amount of money on the table, it is not surprising Amex is putting R&D efforts to tackle that issue head on.
I also believe this is an issue to be handled on the long term – as time passes by, more and more transactions move from the physical world to the digital. Thus, people are more susceptible to digital identity theft and fraud – and that must be stopped.

On November 14, 2018, Andrey commented on Steam-powered ideas: a market for open innovation :

Thanks for your article, it adds another interesting perspective to Valve over what we learned in our Valve case. You paint an interesting trend on the tension between Steam’s open innovation and the direction gaming consoles are advancing to.
For your second question – how to prevent inappropriate material – I believe the answer can be combined with another megatrend, machine learning. Policing an open-content platform is a task that is not unique to Valve. For example, Instagram uses an ML algorithm for anti-bullying: https://www.techrepublic.com/article/how-ai-became-instagrams-weapon-of-choice-in-the-war-on-cyberbullying/.
Implementing such a system can save Valve precious manpower and allow users to keep creating content freely.