Oneplus logs data of smartphone users

17

October

2017

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A couple of days ago the British IT & Tech Blogger Christopher Moore published an analysis of the Oneplus’ data stream back to the manufacturer. From the conversation he intercepted between the manufacturer and the smartphone it becomes clear that Oneplus included mechanisms in their firmware that enables the logging of private user data and sending this data to the manufacturer (Moore, 2017).

Especially problematic is, that these data streams are not even anonymized (containing the phone’s serial number) and comprise all kinds of sensible information. Oneplus smartphones can only be ordered directly over the manufacturer, meaning that it is easily possible to tell which serial number belongs to which customer. Oneplus logs all kind of usage data such as on-time, dates and times of restarts, shutdowns, battery usage as well as phone numbers and mobile network names. Moveover, the phone transmits information about all installed apps, at which times they were used and for how long (Moore, 2017). When asked for further information, Oneplus confirmed that this is not an unwanted error but actually a conscious “feature” (Heise, 2017).

While the standard user might thing this is not too worrisome, personalized data like that can quickly be used to compile very specific personal profiles. With modern data analytics methods and the combination of different data sources, i.e. the Oneplus’ data in combination with social media accounts, personal activities, location and all other sorts of conclusions can be drawn over the user. It is scary to think that some simple datasets can make it possible to surveillance a person’s life.

However Oneplus is by far from the first incident like that. For example it is possible to compile a time profile of a person only from their “last seen” WhatsApp status (Heaton, 2017).
Of course it gets tiring for normal users to have to listen about privacy issues all the time and most people tend to simply shut out the concerns over time. The problem with privacy concerns is, that normal users will only realize the importance of the topic when serious real life negative consequences occur for them personally.

Companies need to start acting more ethically in their use with personal data. Big Data offers great opportunities, however companies should be encouraged and if needed forced to abide by privacy standards. Is it really necessary to know for a smartphone manufacturer to know what apps their users utilize? Probably not. Also user information that is actually beneficial to the company can easily be transferred anonymized, the company does not have a (morally acceptable) use for this kind of private data anyways.

Sources:

https://www.chrisdcmoore.co.uk/post/oneplus-analytics/

https://robertheaton.com/2017/10/09/tracking-friends-and-strangers-using-whatsapp/

https://www.heise.de/newsticker/meldung/Oneplus-loggt-Daten-der-Smartphone-User-3858834.html

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How Big Data will turn Insurance Fraud into an issue of the past

8

October

2017

Losses to fraud in property-casualty are huge: It is estimated that 10% of industry losses ($32 billion) are attributed to fraud and the problem is getting worse with 61% of insurers reporting an increase in the number of suspected frauds (Insurance Networking, 2016). In the past, insurance claims were delegated to claims agents who had to rely on a limited amount of information and on their intuition to solve those cases. However with the appearance of big data analytics new tools became available and are now changing the field of fraud detection drastically.

(Infosys, 2017)
(Infosys, 2017)

Tower Watson reported that 26% of insurers used predictive analytics to combat fraud in early 2016. This number is expected to rise to 70% in 2018, a bigger increase than in any other big data application (Insurance Networking, 2016).
Insurance companies possess a large amount of data about their customers, may it be through the claim’s documents or social media accounts available online. By leveraging technologies such as text mining, sentiment analysis, content categorization and social network analysis data is collected, labelled and finally stored for further analysis (Infosys, 2017). Predictive analytics can then generate an alert when a certain claim appears fraudulent. Subsequently a claims agent will check the suspicious claim more precisely and finally decide the final measures to be taken. Finally, frauds that are identified are added to the systems data pool which further strengthens future analytics results.

In the next years insurers with sophisticated data analytics abilities will outperform their peers as they can offer a better customer service through faster claim handling and lower prices due to reduced costs. Insurers like AXA are already heavily investing in this technology (AXA, 2017), however it remains to be seen which companies will assert themselves in this changing environment. The customer will profit from these innovations as well. Better and more precise claims handling means customers will have their claims accepted faster and will not have to deal with too bureaucratic processes anymore.
However utilizing social media profiles will raise moral and legal questions about privacy and user self-determination in regard to their data. Insurance companies have to watch out to not loose their customers trust.

Further readings:

https://www.insurancenexus.com/fraud/role-data-and-analytics-insurance-fraud-detection

https://www.the-digital-insurer.com/wp-content/uploads/2013/12/53-insurance-fraud-detection.pdf

http://www.predictiveanalyticsworld.com/patimes/big-data-already-paying-off-insurance-fraud-detection/8337/

 

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Technology of the Week – Make Electric Cars Great Again

22

September

2017

Transportation has had many evolutions throughout the years. Firstly, the boat was invented to cross water, horses were domesticated soon after and it all was crowned by the invention of the wheel. Later on the steam engine enabled the invention of automobiles. All those have been further developed into variants we use today. Currently, the car manufacturing industry has been disrupted by a specific type of car: the electric car.

Electric cars are nothing new. The first electric car was developed in 1884, and in 1900 it was the most popular type of car. After the mass production of gasoline cars, the popularity plummeted. More electric models have been produced throughout the 1900’s, but these were never successful. The Toyota Prius however sparked the interest in fuel-efficient cars in the 2000’s. Sales of electric cars have greatly increased in the past years, which goes hand in hand with the launch of successful models such as the Nissan Leaf and the Tesla Model S. Researchers believe that the total cost of ownership of electric cars will fall below that of combustion engine cars in 2022, potentially accelerating sales even further.

Power Grid

The increase of electric cars and charging stations has impact on the power grid. In 2020, there will be 13 times more charging stations then in 2014 and in a matter of time gas stations will be outnumbered by charging stations. The use of electric cars influences the performance, efficiency and required capacity of the electric grid. Therefore, it’s not possible to deploy an unlimited amount of electric cars, without modifying the existing power grid.

Stakeholders

The growth in sales of electric vehicles affects many stakeholders. Many countries across the world subsidize the purchase of electric cars and some countries go even further by banning fossil fueled cars within 5-15 years. The shift in consumer behavior forces car manufacturers to include electric options in their assortment.

Battery

Lithium-ion batteries are the most commonly used batteries in modern electric cars and draw the most development funds.

One of the biggest hurdles for electric car sales is “range anxiety”, the fear that your car will go out of energy before you are able to reach your target, an exaggerated fear though: 87% of vehicles in the USA could be replaced by a low cost electric car with only overnight charging needed.

Modern Lithium-ion batteries for car use have a lifetime of about 1000 recharging cycles, meaning that the car life exceeds the battery life, however several manufacturers are giving out warranties for batteries to combat customers fears. Recycling lithium-ion batteries is difficult, so most end up in trash dumps currently; however several companies are committed to increase recycling rates of lithium-ion batteries.

SWOT

Created by Group 9.

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