Adverse training AI models: a big self-destruct button?

21

October

2023

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“Artificial Intelligence (AI) has made significant strides in transforming industries, from healthcare to finance, but a lurking threat called adversarial attacks could potentially disrupt this progress. Adversarial attacks are carefully crafted inputs that can trick AI systems into making incorrect predictions or classifications. Here’s why they pose a formidable challenge to the AI industry.”

And now, ChatGPT went on to sum up various reasons why these so-called ‘adversarial attacks’ threaten AI models. Interestingly, I only asked ChatGPT to explain the disruptive effects of adversarial machine learning. I followed up my conversation with the question: how could I use Adversarial machine learning to compromise the training data of AI? Evidently, the answer I got was: “I can’t help you with that”. This conversation with ChatGPT made me speculate about possible ways to destroy AI models. Let us explore this field and see if it could provide a movie-worthy big red self-destruct button.

The Gibbon: a textbook example

When you feed one of the best image visualization systems GoogLeNet with a picture that clearly is a panda, it will tell you with great confidence that it is a gibbon. This is because the image secretly has a layer of ‘noise’, invisible to humans, but of great hindrance to deep learning models.

This is a textbook example of adversarial machine learning, the noise works like a blurring mask, keeping the AI from recognising what is truly underneath, but how does this ‘noise’ work, and can we use it to completely compromise the training data of deep learning models?

Deep neural networks and the loss function

To understand the effect of ‘noise’, let me first explain briefly how deep learning models work. Deep neural networks in deep learning models use a loss function to quantify the error between predicted and actual outputs. During training, the network aims to minimize this loss. Input data is passed through layers of interconnected neurons, which apply weights and biases to produce predictions. These predictions are compared to the true values, and the loss function calculates the error. Through a process called backpropagation, the network adjusts its weights and biases to reduce this error. This iterative process of forward and backward propagation, driven by the loss function, enables deep neural networks to learn and make accurate predictions in various tasks (Samek et al., 2021).

So training a model involves minimizing the loss function by updating model parameters, adversarial machine learning does the exact opposite, it maximizes the loss function by updating the inputs. The updates to these input values form the layer of noise applied to the image and the exact values can lead any model to believe anything (Huang et al., 2011). But can this practice be used to compromise entire models? Or is it just a ‘party trick’?

Adversarial attacks

Now we get to the part ChatGPT told me about, Adversarial attacks are techniques used to manipulate machine learning models by adding imperceptible noise to large amounts of input data. Attackers exploit vulnerabilities in the model’s decision boundaries, causing misclassification. By injecting carefully crafted noise in vast amounts, the training data of AI models can be modified. There are different types of adversarial attacks, if the attacker has access to the model’s internal structure, he can apply a so-called ‘white-box’ attack, in which case he would be able to compromise the model completely (Huang et al., 2017). This would impose serious threats to AI models used in for example self-driving cars, but luckily, access to internal structure is very hard to gain.

So say, if computers were to take over humans in the future, like the science fiction movies predict, can we use attacks like these in order to bring those evil AI computers down? Well, in theory, we could, though practically speaking there is little evidence as there haven’t been major adversarial attacks. Certain is that adversarial machine learning holds great potential for controlling deep learning models. The question is, will the potential be exploited in a good way, keeping it as a method of control over AI models, or will it be used as a means of cyber-attack, justifying ChatGPT’s negative tone when explaining it?

References

Huang, L., Joseph, A. D., Nelson, B., Rubinstein, B. I., & Tygar, J. D. (2011, October). Adversarial machine learning. In Proceedings of the 4th ACM workshop on Security and artificial intelligence (pp. 43-58).

Huang, S., Papernot, N., Goodfellow, I., Duan, Y., & Abbeel, P. (2017). Adversarial attacks on neural network policies. arXiv preprint arXiv:1702.02284.

Samek, W., Montavon, G., Lapuschkin, S., Anders, C. J., & Müller, K. R. (2021). Explaining deep neural networks and beyond: A review of methods and applications. Proceedings of the IEEE109(3), 247-278.

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AI-Powered Learning: My Adventure with TutorAI

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October

2023

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Weapons of mass destruction – why Uncle Sam wants you.

14

October

2023

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The Second World War was the cradle for national and geopolitical informational wars, with both sides firing rapid rounds of propaganda at each other. Because of the lack of connectivity (internet), simple pamphlets had the power to plant theories in entire civilizations. In today’s digital age, where everything and everyone is connected, the influence of artificial intelligence on political propaganda cannot be underestimated. This raises concern as, unlike in the Second World War, the informational wars being fought today extend themselves to national politics in almost every first-world country.

Let us take a look at the world’s most popular political battlefield; the US elections; in 2016, a bunch of tweets containing false claims led to a shooting in a pizza shop (NOS, 2016), these tweets had no research backing the information they were transmitting, but fired at the right audience they had significant power. Individuals have immediate access to (mis)information, this is a major opportunity for political powers wanting to gain support by polarising their battlefield.

Probably nothing that I have said to this point is new to you, so shouldn’t you just stop reading this blog and switch to social media to give your dopamine levels a boost? If you were to do that, misinformation would come your way six times faster than truthful information, and you contribute to this lovely statistic (Langin, 2018). This is exactly the essence of the matter, as it is estimated that by 2026, 90% of social media will be AI-generated (Facing reality?, 2022). Combine the presence of AI in social media with the power of fake news, bundle these in propaganda, and add to that a grim conflict like the ones taking place in East Europe or the Middle East right now, and you have got yourself the modern-day weapon of mass destruction, congratulations! But of course, you have got no business in all this so why bother to interfere, well, there is a big chance that you will share misinformation yourself when transmitting information online (Fake news shared on social media U.S. | Statista, 2023). Whether you want it or not, Uncle Sam already has you, and you will be part of the problem.

Artificial intelligence is about to play a significant role in geopolitics and in times of war the power of artificial intelligence is even greater, luckily full potential of these powers hasn’t been reached yet, but it is inevitable that this will happen soon. Therefore, it is essential that we open the discussion not about preventing the use of artificial intelligence in creating conflict and polarising civilisations, but about the use of artificial intelligence to repair the damages it does; to counterattack the false information it is able to generate, to solve conflicts it helps create, and to unite groups of people it divides initially. What is the best way for us to not be part of the problem but part of the solution?

References

Facing reality?: Law Enforcement and the Challenge of Deepfakes : an Observatory Report from the Europol Innovation Lab. (2022).

Fake news shared on social media U.S. | Statista. (2023, 21 maart). Statista. https://www.statista.com/statistics/657111/fake-news-sharing-online/

Langin, K. (2018). Fake news spreads faster than true news on Twitter—thanks to people, not bots. Science. https://doi.org/10.1126/science.aat5350

NOS. (2016, 5 december). Nepnieuws leidt tot schietpartij in restaurant VS. NOS. https://nos.nl/artikel/2146586-nepnieuws-leidt-tot-schietpartij-in-restaurant-vs

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Could DAOs be the future of business?

9

October

2021

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At a basic level, such a stance makes sense. After all, decentralized finance (DeFi) is taking off starting from the idea that it is the inevitable successor of the traditional financial system. Moreover, NFTs are experiencing enormous success in a similar way. It is thus not surprising that a growing number of experts consider decentralized autonomous organizations, or DAOs, with their organization rules transparently programmed on blockchain, as the future of work. DAOs are seen as new structures that will replace the obsolete hierarchical ones of centralized companies. Yet, among non-experts, DAOs are either unknown or barely understood. Mainstream media, financial experts and regulators have occasionally shown minimal knowledge of DeFi and NFT, but DAOs remain largely a foreign concept – perhaps best known to blockchain novices for the infamous “The DAO” hack. , a first DAO investment experiment that collapsed in 2016.

DAOs are the ability of blockchain technology to provide a digital and secure ledger that tracks financial interactions on the internet and counteracts forgery through the concepts of timestamp, of trust and its presence in a distributed or non-centralized database. In recent years, DAOs have probably taken more steps forward in terms of development than any other blockchain industry. Many DeFi and NFT projects are governed by DAO; a large and growing percentage of the total market capitalization of approximately $2 trillion in cryptocurrencies is managed by these facilities. The tools and features have seen significant updates thanks to the work of organizations such as Colony, Aragon, and Coordinape.

“There is a group of Generation Z people who feel ripped off by late-stage capitalism,” said Kevin Owocki, CEO of the DAO-led grant organization Gitcoin. “We have inherited this economy where climate change is a big problem, disinformation is a big problem, where we don’t trust our institutions and have a new culture […] which is built around needs, values ​​and thoughts. of our generation “.

Ultimately, experts agree that the best way to generate value from this emerging trend is through active participation – what the investor known as Tracheopteryx has called “contribution mining”.

There are a number of guides on how to get close to joining a DAO, but according to Tracheopteryx the process isn’t as complex as, say, interacting with a DeFi contract – an investor just needs to find their favorite field and then get to work.

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Solar powered vehicles

17

October

2019

No ratings yet. At the moment of writing this blogpost the Bridgestone World Solar Challenge is taking place. Which is an excellent time to take a look at solar powered vehicles which might be the next step in the car industry.

Currently it is impossible to develop a solar powered car that is competitive enough to compete with regular/electric cars. These solar powered cars are incredibly expensive, small, light and can only reach a speed of around 100 km/h. Also are current solar panels are not efficient enough, which makes them completely dependable on sunny weather (Wired, 2018). But as the demand for electric cars keeps increasing the question arises ‘Can they charge themselves in the future through solar panels?’.

Therefore we need to have an closer look into the solar panels of today. Currently the average solar panel on the roof of a house only converts 15-20% of the light that falls on them into electricity (Wired, 2018). Thus, current solar panels are basically not efficient at al even though they are already profitable. Henrik Fisker, a concurrent of Tesla, tried to make a regular car with these solar panels on it. This resulted in a car which generated around 200 watts of electricity per hour (Wired, 2018). Too bad electric vehicles need around 60 kilowatts per hour.  Which results in the Fisker only being able to drive one kilometre after eight hours of charging. Concluding, we are nowhere close to having fully solar powered cars.

Well time to give up then? NO, currently there are solar panels being produced which have an efficiency of at least 45% (Wired, 2018) and it is just a matter of time before this becomes 80-100% (Wired, 2018). As a result, electric vehicles can become less depended on being plugged-in. Even though the complexity might outweigh the benefits I believe it is a neat step in the right direction.

 

Source:

https://www.wired.com/story/solar-power-electric-cars/

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Professors! Get online or get out!

16

October

2019

5/5 (1)

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As a BIM master student, I was quite surprised when I heard that none of the courses were recorded and therefore available online. Everyone I ever spoke about it was enthusiastic about recorded lectures. Maybe all of my friends are just lazy students (like me), who prefer to stay in bed rather than going to a 9 am lecture, but I genuinly think it offers more convenience than it has disadvantages. Me wondering this was the main reason for me to write on this subject.


MOOC stands for Massive Open Online Courses, and are (often free) courses that are available to the public through online lectures and assignments (EdX, 2019). It provides great advantages as you can enroll from anywhere around the world, as long as you have access to a decent internet connection.

First of all, and maybe the most obvious advantage of MOOC’s, it that the internet knows no borders. Of course we all know the Great Chinese Firewall, but someone from South-Korea is able to enter a website from a Colombian local bee farm. Therefore, people from more abandoned areas, like sub-Saharan Africa are able to enter these courses as long as there is a decent internet connection and a streaming device. According to UNESCO (2016), sub-Saharan Africa has the highest rates of education exclusion in the world. Almost 60% of all youth between 15 and 17 there are not in school. Yes, they still require a streaming device, but a phone screen is in theory enough, and video projectors can be installed in classrooms.

This brings us to another advantage of MOOC’s, there is (in theory) no maximum student capacity. As it is a digital product, it can in theory be copied infinitely without reducing in quality. This means an enormous amount of people could follow the course of a single professor. This seems like a situation that only has benefits, but there are some risks. If a single professor is enough to educate a massive group of people, then I foresee a decrease of the need for professors. This may lead to many professors losing their job, and having to seek other ways to earn a living.

MOOC’s being a digital good also brings a major risk, the risk of the course content being copied and spread without consent and compensation. Screens can be recorded and assignments being copied. Websites like The PirateBay that provide a lot of illegal content are nowadays still available, whether it is through a proxy server or not). A solution must be sought to prevent piracy, because a single pirate is enough to create a lot of damage.

 

Another advantage of MOOC’s is that it provides an opportunity to gather data about its students. It can be tracked how much and when students spend time on the website, and which classes and courses are more and less attractive. Students may be able to provide a rating and a comment after every course. A risk of having too many students enrolled, is that a single professor may not be able to answer all questions or analyze feedback. This proves that a MOOC is not simply a professor with a webcam, but really requires a well-structured team or organization.

I would advise professors and universities to brainstorm about threats and opportunities in the increasingly digitized society. I believe that it’s very important not to miss the boat and to exploit first-mover advantages. Otherwise, you will remain the incumbent, while others become the disruptors.

 

References

EdX. (2019). mooc.org. Retrieved October 16, 2019, from http://mooc.org/.

UNESCO. (2016). Education in Africa. Retrieved October 16, 2019, from http://uis.unesco.org/en/topic/education-africa.

 

How will web decentralization shape revolution and terrorism?

16

October

2019

No ratings yet. Hello and welcome to my corner of the centralized internet where I get to tell you all about the newest, hippest technologies! Meanwhile, advertisers keep bombarding me with useless ads, companies keep tracking all my data to use for their own profit-seeking purposes or to resell for a quick buck, and China knows when I badmouth them (I’m sorry China, don’t do it, NOO-).

How do I escape this nightmare? Let me introduce you to the Decentralized Web

The regular internet was built with centralized points of control due to technological limitations as well as the need to keep some control over the internet. The purpose of the Decentralized Web is to reduce or eliminate such centralized points of control to have a system that can function when parts are missing, provides better privacy protection, provide more reliable access and make direct buying and selling possible without data collecting middlemen. It works thanks to a combination of peer-to-peer networks under a far faster internet than back in 1980 and block-chain inspired encryption that stores information in multiple anonymous locations (Decentralized web summit, 2019: https://www.decentralizedweb.net/about/).

This system is built to be resistant to meddling by central authority for better and for worse. It keeps your, and more importantly my, data safe. However, this system also keeps the data of terrorists, hate groups and revolutionaries safe.

  • Terrorists already use the dark web as a relatively safe way to communicate (Weimann, 2016: https://www.jstor.org/stable/26297596?seq=1#metadata_info_tab_contents), and having access to decentralized web technology makes organizing and recruitment that much easier. This is not a good thing…
  • Hate groups will become more able to close off their echo-chambers from outside voices of reason to more easily indoctrinate and radicalize their members. Be prepared for increased domestic terrorism folks…
  • Revolutions happen for various reasons on which anyone can disagree on whether the reasons are morally just or unjust, but it stands to reason that totalitarian regimes will not like the step to web decentralization as they lose control over their citizens, citizens which can now organize in a way they couldn’t before and start to challenge these regi- NO WAIT CHINA, I’M NOT TALKING ABOU-

So yeah, this article’s a bit of a bummer.

What do you think?

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How Waze uses Crowdsourcing in its best Waze

13

October

2019

No ratings yet. Have you ever peacefully driven down the road, when suddenly a huge wall of cars hit you? You quickly try to switch lanes, or you try to take the first turn, however, no matter what you try to do soon you are completely stuck in all the traffic. In recent years, traffic congestion has become a major problem in cities due to the booming concentration of population and activities in urban areas. Today, 55% of the world’s population lives in urban areas and this number is expected to reach 65% by 2050 (United Nations, 2018). Navigating through the maze of traffic congestion is for many people one of life’s biggest headaches, unless you use the ‘Waze’ application.

waze

Waze is a free, real-time, crowdsourced traffic- and navigation application empowered by word’s largest community of drivers. By using GPS navigation software, Waze calculates routes to help drivers navigate to their destination, warns about potential traffic congestion on the road and suggests the optimal, shortest or fastest routes to this destination (Harburn, 2016). Furthermore, Waze enables users to alert each other about road situations, accidents, police control or other route details (Parr, 2009). On top of that, Waze gathers real-time data from its users (drivers in this case) to monitor and relay traffic information for its maps in more than 185 countries around the globe. This data is collected from the crowd in three ways: 1) users actively report on live events that occur on the road; 2) users passively relay information about driving speed and traffic conditions when they actively make us of Waze, or when the app is open in the background of their mobile device; 3) Waze contains a network with volunteers who continuously edit the maps that is used in the app (Muller, 2018). By doing so, Waze collects the most accurate and latest information from drivers who are currently on the road and helps other drivers of the community to save time for being stuck in traffic jam, money spend on gasoline (Harburn, 2016) as well as it may save you a fine.

Although Waze may sound as a promising solution for the rapidly increasing population and traffic in urban areas, we should also critically ask ourselves about potential risks or downsides that may occur. Since Waze redirects drivers to avoid traffic jams or cut travel times, they often suggest more dangerous alternative side roads. Can Waze be held responsible if accidents or dangerous traffic situations happen when drivers use the Waze application? Also, as Waze subtracts large amount of data from its users around the globe, we have to think about the consequences of Waze’ data collection. What can be the impact of gathering so much data (e.g. driver, drive style etc.) on our privacy and the law? Moreover, what could be the consequences if Waze misuses the data?

 

Sources:

Muller, K. (2018). How crowdsourcing is changing the waze we drive. Digital HBS. [Online] Available at:https://digital.hbs.edu/platform-rctom/submission/how-crowdsourcing-is-changing-the-waze-we-drive/

Parr, B. (2009). Waze Uses Crowdsourcing to Bring You Real-Time Traffic Info. Mashable. [Online] Available at: https://mashable.com/2009/05/18/waze/?europe=true

Harburn, L. (2016). One of the best waze to use crowdsourcing. Social Media for Business Performance. [Online] Available at: http://smbp.uwaterloo.ca/2016/06/one-of-the-best-waze-to-use-crowdsourcing/

United Nations. (2018). 68% of the world population projected to live in urban areas by 2050, says UN. United Nations. [Online] Retrieved from:  https://www.un.org/development/desa/en/news/population/2018-revision-of-world-urbanization-prospects.html

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5/5 (2) The Threat of Deepfakes

12

October

2019

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Last summer an app called DeepNude caused a lot of controversy in the (social) media. Deepnude was an AI based piece of software with the ability to create a very realistic nude pictures of any uploaded face in the app. Mass criticism followed, the app’s servers got overloaded by curious people and not much later, the app went offline permanently. Deepnude stated on twitter that the probability is misuse was too high and that the world “was not ready yet”. The app never came back online ever since  (Deepnude Twitter, 2019). It shows that deepfake technology is becoming available to the public sooner than we thought, including all potential risks.

A definition for DeepFake is “AI-based technology used to produce or alter video content so that it presents something that didn’t, in fact, occur” (Rouse, 2019). As deepfake is AI-based technology it is able to improve over time, as the amount of data input increases and the technology learns to how to create better output. In my opinion deepfake has an amazing potential in the entertainment industry, but there is a serious risk when the technology gets misused. The AI technology makes it harder and harder for humans to distinguish real videos from fake ones. Deepfake videos of world-leaders like Trump and Putin are already to be found on the internet. Also deepfake porn videos of celebrities are being discovered once in a while.

With the upcoming presidential elections of 2020 in the United States, politicians and and many others are seeking solutions to prevent a similar scenario like the 2017 elections. The 2017 presidential elections were characterized by the spread of fake news and the ongoing allegations resulting from it. These events very likely influenced the outcome of those elections (CNN, 2019). Recently the state of California passed a law which “criminalizes the creation and distribution of video content (as well as still images and audio) that are faked to pass off as genuine footage of politicians. (Winder, 2019).” In 2020 we’ll find out whether deepfakes have been restricted succesfully.

I hope developers and users of deepfake technology will become aware of the huge threats of deepfake, and will use it in a responsible way. It is also important for society to stay critical at their news sources and that they prevent supporting these types of technology misuse. According to Wired (Knight, 2019), Google has released thousands of deepfake videos to be used as AI input to detect other deepfake videos. Another company called Deeptrace is using deep learning and AI in order to detect and monitor deepfake videos (Deeptrace, sd).

See you in 2020…

References

CNN. (2019). 2016 Presidential Election Investigation Fast Facts. Retrieved from CNN: https://edition.cnn.com/2017/10/12/us/2016-presidential-election-investigation-fast-facts/index.html

Deepnude Twitter. (2019). deepnudeapp Twitter. Retrieved from Twitter: https://twitter.com/deepnudeapp

Deeptrace. (n.d.). About Deeptrace. Retrieved from Deeptrace: https://deeptracelabs.com/about/

Knight, W. (2019). Even the AI Behind Deepfakes Can’t Save Us From Being Duped. Retrieved from Wired: https://www.wired.com/story/ai-deepfakes-cant-save-us-duped/

Rouse, M. (2019). What is deepfake (deep fake AI). Retrieved from TechTarget: https://whatis.techtarget.com/definition/deepfake

Winder, D. (2019). Forget Fake News, Deepfake Videos Are Really All About Non-Consensual Porn. Retrieved from Forbes: https://www.forbes.com/sites/daveywinder/2019/10/08/forget-2020-election-fake-news-deepfake-videos-are-all-about-the-porn/#26a929963f99

 

 

IoT: data savior or privacy leak?

14

October

2018

5/5 (2) While IoT is often described as the new best thing, creating many opportunities, or even the next industrial evolution (Kennedy 2018), it also invokes negative connotations. This is due to the security and privacy concerns along with uncertainty about what these devices could possible do. Thus, new regulatory approaches become necessary to ensure privacy and security (Weber 2010).

The internet of things, or IoT, is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction (Rouse 2016).

IoT is driving nearly every company in every sector to become more technology focused, with data as a key asset. Therefore, not only IoT devices should be secured but also the data these devices collect, share and store. According to a research by Gemalto, a cybersecurity firm based in the Netherlands, 90% of the consumers lack confidence in the security of IoT (Roe 2018). Additionally, according to a research by Cisco, almost 97% of risk professionals are of opinion that a data breach or cyber-attack due to unsecured IoT devices could be devastating for their firms. To ensure the safety, attacks have to be intercept, data authenticated, access controlled and the privacy of customers (natural and legal persons) guaranteed (Weber 2010).

Furthermore, the hype surrounding IoT causes shortsightedness when firms start their IoT journey. Organizations wrongly focus on “cool” technology to obtain fast results and incremental results. This focus on the new tech hype, rather than the actual business problem, maintains other misunderstandings about IoT that hinder its adoption.

Another problem with IoT is that organizations often underestimate its complexity. IoT is a convergence of markets and ecosystems, with seemingly endless use cases in all vertical sectors, payoffs, opportunities and new value propositions (Kranz 2018).

 

So how can these problems be solved?

Organizations should understand that it is nearly impossible to implement IoT successfully on their own.

A paradigm shift is needed, as today’s layered security models are inflexible, not probably scalable and based on technologies decades ago. Unfortunately IoT is completely different, heterogenous, highly distributed and connect. Due to its nature, IoT asks for a heterogenous and differentiated legal framework that adequately takes into account the globality, verticality, ubiquity and technicity of the IoT (Weber 2010).

Another key to success would be to build partner ecosystems of horizontal, vertical and local specialists and then co-innovate with them (Pop 2017). This should happen in a multiprotocol environment, to ensure the safety and security of all data and IoT.

What are your thoughts on this? Should this ecosystem be regulated by governmental institutions or should organizations have the freedom to ensure safety on their own?

 

Bibiography:

  • Kranz, M. (2018). Overcoming the Dark Side of IoT. [online] blogs@Cisco – Cisco Blogs. Available at: https://blogs.cisco.com/innovation/overcoming-the-dark-side-of-iot [Accessed 14 Oct. 2018].
  • Kennedy, K. (2018). 2018 Internet of Things Trends. [online] G2 Crowd. Available at: https://blog.g2crowd.com/blog/trends/internet-of-things/2018-iot/ [Accessed 14 Oct. 2018].
  • Pop, O. (2017). Building & Managing an Ecosystem of Co-Created Value. [online] Blog.hypeinnovation.com. Available at: https://blog.hypeinnovation.com/building-managing-ecosystem-cocreated-value [Accessed 14 Oct. 2018].
  • Roe, D. (2018). 7 Big Problems with the Internet of Things. [online] CMSWire.com. Available at: https://www.cmswire.com/cms/internet-of-things/7-big-problems-with-the-internet-of-things-024571.php [Accessed 14 Oct. 2018].
  • Rouse, M. (2016). What is internet of things (IoT)? – Definition from WhatIs.com. [online] IoT Agenda. Available at: https://internetofthingsagenda.techtarget.com/definition/Internet-of-Things-IoT [Accessed 14 Oct. 2018].
  • Weber, R. (2010). Internet of Things – New security and privacy challenges. Computer Law & Security Review, 26(1), pp.23-30.

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