One team, for instance, synced a smartphone mic and portable speaker. That let them create an on-the-fly sonar system to map movements throughout a house. The team reported the work in a September study. Selcuk Uluagac is an electrical and computer engineer. He works at Florida International University in Miami.
Legitimate apps often harvest info to compile such things as your search-engine and app-download history. The makers of these apps sell that info to advertising companies and outside parties. Take a health-insurance company. So researchers are devising ways to give people more control over what information apps can siphon data from their devices.
Some safeguard apps could appear as standalone programs. Uluagac and his colleagues recently proposed a system called 6thSense. Then it alerts an owner when it detects unusual behaviors. This might include tasks like calling, Web browsing or driving. That program is on the lookout for something odd. This might be the motion sensors reaping data when a user is just sitting and texting. Then, 6thSense alerts the user. Users can check if a recently downloaded app is responsible for a suspicious activity. If so, they can delete the app from their phones.
Smartphones put your privacy at risk
The owners of 50 of these phones trained with 6thSense to identify their typical sensor activity. The researchers then fed the 6thSense system examples of benign data from daily activities mixed with bits of malicious sensor operations. His team devised DEEProtect for people who want more active control over their data. People could use DEEProtect to specify what their apps would be allowed to do with sensor data. For example, someone may want an app to transcribe speech but not identify the speaker.
DEEProtect intercepts whatever raw sensor data an app tries to access.
Smartphones open new opportunities for privacy invasion | Science News
It then strips those data down to only the features needed to make user-approved inferences. Consider speech-to-text translation. For this, the phone typically needs sound frequencies and the probabilities of particular words following each other in a sentence.
So DEEProtect distorts the dataset before releasing it to the app. However, it leaves alone data on word orders. Users get to control how much DEEProtect changes the data. More distortion offers more privacy — but at a price: It degrades app functions.
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He and his colleagues took a different approach. They are trying to protect users from accidentally allowing sensor access to deceitful apps. Their security system is called AWare. When they are first installed, apps have to get a user permission to access certain sensors. This might include the mic and camera. But people can be careless about granting those permissions, Uluagac says. They may give no thought to why the apps might — or might not — need them.
AWare would instead request permission from a user before an app can access a certain sensor the first time a user provided a certain input. On top of that, the AWare system memorizes the state of the phone when the user grants that first permission. It remembers the exact appearance of the screen, the sensors that were requested and other information.
That way, AWare can tell users if and when the app later attempts to trick them into granting unintended permissions. The Penn State researchers imagined a crafty data-stealing app.
It would ask for camera access when the user first pushes a camera button. But it would then also try to access the mic when the user later pushes that same button. It would then ask the user again if he or she would like to grant this additional permission. Petracca and his colleagues tested AWare with people using Nexus smartphones. Those using phone equipped with AWare avoided unwanted authorizations about 93 percent of the time. He and his colleagues are keeping tabs on the latest security studies coming out of university labs.
The team wants to restrict access for nefarious apps but not slow or degrade the functions of trustworthy programs, Mayrhofer explains. Tech companies may also be reluctant to adopt more security measures. These extra protections can come at the cost of user friendliness.
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But phones are relying on ever more — and more powerful — sensors. And algorithms for analyzing their data are becoming more wise.
Solutions will improve. And security teams will engineer still more clever solutions. And on and on it goes. The game will continue, Chakraborty agrees.
These sensors typically can measure movement changes in all three dimensions front-to-back, side-to-side and up-and-down. Algorithms are used in mathematics and in computer programs for figuring out solutions. Malignant, in contrast, means harmful and generally refers to cancer. The writing of these instructions is known as computer programming. Examples include tropical reefs, rainforests, alpine meadows and polar tundra. As a verb, to engineer means to design a device, material or process that will solve some problem or unmet need. Mechanical forms of the device tend to use a spinning wheel or disc that allows one axle inside it to take on any orientation.
Air with a lot of water vapor in it is known as humid. Machine learning is the basis of some forms of artificial intelligence AI. To test, sample or watch something, especially on a regular or ongoing basis. On the internet. A term for what can be found or accessed on the internet. For instance, exposure to radiation poses a risk of cancer. Or the hazard — or peril — itself. For instance: Among cancer risks that the people faced were radiation and drinking water tainted with arsenic.
While this is certainly possible, it is especially difficult to manage for small-time app developers who will have to do this while also staying on top of maintaining their apps, developing new features, and various other developer-related tasks.
To make this easier, developers use third-party trackers who know other businesses interested in mobile advertising and mediate between them and the app developers who want to monetize their apps through ads. Developers embed pieces of software developed by these services inside their apps which allows them to collect information about the users and use it to display targeted advertisements.
This lack of transparency is not helped by the fact that they regularly end up in the news for sharing or selling large amounts of mobile tracking data.
These patterns could allow a government analyst to find cases in which people used their phones in an unusual way, such as taking particular privacy precautions. A few examples of things that a government might try to figure out from data analysis: determining whether people know each other; detecting when one person uses multiple phones or switches phones; detecting when groups of people are traveling together or regularly meeting one another; detecting when groups of people use their phones in unusual or suspicious ways.
It is not yet available for iOS. Lumen helps users identify these third-party services in their apps by monitoring network activities of the apps that are running on your phone. It also tells you what kind of data is collected by them and organization is collecting the data. Lumen brings the much-needed transparency into the equation and having this information is half the battle, but users need to have some sort of control over this behaviour.
Lumen also gives them the option to block those flows. This feature gives the users granular control over the network communications of their apps and helps them prevent unwanted tracking by third-party services. Blokada is another such tool for Android devices that efficiently blocks ads and trackers. It is also free and an open source project. Concerned about your Google data? You better be!