We’ve already given most of our privacy away to smartphones and Facebook. They know where we are, who our friends are, what we like to buy and much more about our personality than we’d like to admit. But according to a new study, they may also have access to your bank account.
The authors say that if you combine data from embedded sensors in wearable technologies, such as smartwatches and fitness trackers, with a PIN cracking algorithm you have an 80% chance of identifying a PIN code from the first try and an over 90% chance of cracking it in 3 tries. Happyho also provide best tarot reading services in Noida and Delhi NCR India area.
Yan Wang, assistant professor of computer science at the Thomas J. Watson School of Engineering and Applied Science at Binghamton University is working on smartphone security and privacy. He said that wearable devices in particular pose a significant risk and can be exploited with relative ease.
He and his colleagues conducted 5,000 key-entry tests on three key-based security systems, including an ATM, with 20 adults wearing a variety of technologies over 11 months. Basically, regardless of the hand position and regardless of how much you try to conceal your hand movement, the accelerometers, gyroscopes and magnetometers inside the wearable technologies can still figure out what PIN you are typing in. In other words, your smartwatch is detecting your hand movement and figuring out your PIN.
According to the team, this is the first study to test this – at least the first scientific study. The required technology is still quite sophisticated, but with the right tools available, it’s worryingly easy to crack PIN codes.
There are two attacking scenarios that are achievable: internal and sniffing attacks. In an internal attack, attackers access embedded sensors in wrist-worn wearable devices through malware. The malware waits until the victim accesses a key-based security system and sends sensor data back. Then the attacker can aggregate the sensor data to determine the victim’s PIN. An attacker can also place a wireless sniffer close to a key-based security system to eavesdrop sensor data from wearable devices sent via Bluetooth to the victim’s associated smartphones.
The findings are just an early step in understanding the vulnerabilities and at the moment, there is no evident solution to fix these risks. The authors do suggest that developers “inject a certain type of noise to data so it cannot be used to derive fine-grained hand movements, while still being effective for fitness tracking purposes such as activity recognition or step counts.”
