![\"Shuman](\"https:\/\/saudishopper.com.sa\/en\/wp-content\/uploads\/2021\/03\/Shuman-Ghosemajumder_F5.png\")
<\/a><\/figure><\/div>\n\n\n\nProtecting the privacy of one\u2019s own data in 2021 is hard and is seemingly getting harder. For most people, learning to use new technology isn\u2019t easy, and adapting to continual changes in products and services makes it more complex. With rapidly evolving security and privacy risks, there are always more privacy threats than individual consumers can track.<\/p>\n\n\n\n
You are likely familiar with the most common threats that put your data at risk, such as using insecure passwords, sharing passwords, and not installing security updates on your devices. Poor privacy practices and inadequate security in online applications pose greater risk, regardless of the actions taken to protect oneself.<\/p>\n\n\n\n
But there are many other privacy risks that go beyond these typical scenarios. Here are some examples of the more subtle privacy threats that you may not be thinking about regularly:<\/p>\n\n\n\n
1. Geotagging:<\/strong>\u00a0When you share a photo from your smartphone, what are you actually sharing? You might not realize it, but smartphones record detailed metadata about your device and the image in each JPEG file\u2014including precise GPS coordinates for where the picture was taken. When you share that JPEG with others, or upload it, you are sharing this metadata too, and this is how social media platforms can automatically categorize photos by time and location. If you share photos on a regular basis, you could effectively be sharing a detailed trail of your movements. Law enforcement bodies regularly use image metadata\u00a0to locate unwitting criminals<\/a>. While most major social platforms will strip out the metadata from uploaded photos, occasionally a defect or gap in their site may result in this metadata becoming\u00a0accessible<\/a>.<\/p>\n\n\n\n 2. High-resolution risks:<\/strong>\u00a0Digital cameras today offer incredible image quality, such that even amateur photos can look fantastic. However, there is a downside to those sharp images with many megapixels of detail: they can reveal more information than was intended. For example, it is possible to take advantage of this high resolution to identify nearby people who are not in the photo\u2014from their\u00a0reflections in the eyes<\/a>\u00a0of the subjects. It is also possible to pick up other fine details, like the text on\u00a0confidential papers someone is carrying<\/a>, or\u00a0someone\u2019s fingerprints<\/a>, even from a distance. The same risk applies to advances in media fidelity in other fields. High-quality audio recordings from sensitive microphones\u2014such as those in intelligent personal assistants\u2014can pick up private conversations that are not meant to be recorded.\u00a0You can even analyze audio recordings of keyboard sounds to reconstruct what was typed<\/a>, and as the quality of video and audio sensors and devices increases, these risks will multiply.<\/p>\n\n\n\n 3. Van Eck Phreaking:<\/strong>\u00a0uses specialized equipment to analyze electromagnetic signals to eavesdrop on communications. Anyone that handles highly sensitive information will be familiar with working in rooms with no windows, or inside a Faraday cage where no devices with microphones are allowed, due to techniques that use\u00a0radio emissions<\/a>\u00a0or\u00a0microphones<\/a>\u00a0to \u2018watch\u2019 your laptop screen. There are analogous techniques that can use a laser to listen to a conversation\u00a0from 500 meters away<\/a>, or\u00a0exfiltrate data<\/a>\u00a0using ultrasonic signals. This type of technology can actually be used for beneficial purposes as well\u2014it\u2019s how the\u00a0Zoom app<\/a>\u00a0detects physical Zoom appliances in the same room\u2014but of course it can be, and is, used by malicious actors to spy on others.<\/p>\n\n\n\n 4. Scraping:<\/strong>\u00a0When you upload data to an online application, you might expect that it will stay there unless someone who knows you intentionally copies it somewhere else. But in fact, there are thousands of groups constantly scraping online data, for a variety of reasons, both good and bad. Google constantly scrapes the web to create its search index, but there are other scrapers who maliciously use bots to create attacks so vast in scale that they would not be possible using manual means. At F5, we regularly see that more than\u00a090% of all login attempts<\/a>\u00a0on many major web applications, on a 24\/7 basis, come from bots looking to take over accounts. Bots are also used to scrape images from social media platforms, to then create additional fake accounts that look plausible to other users. This is one of the reasons you see so many social media bots with the same profile photos. If you are wondering if your social media image is being used by fake accounts, you can do a\u00a0reverse image search<\/a>\u00a0and investigate.<\/p>\n\n\n\n 5. Cross-correlation risks.<\/strong>\u00a0Individual bits of benign data can be correlated to expose more about you than you might realize is possible from the pieces themselves. Giving your phone number to a drug store to save some money may seem innocuous, but when that number is looked upon third-party marketing lists, and then combined with\u00a0leaked lists of voter registrations<\/a>, it can now be used to identify where you live, how you vote, your\u00a0health issues<\/a>, your\u00a0movements<\/a>, and\u00a0who you communicate with on<\/a>\u00a0social media. This profile of you can then also be re-sold over and over. Years ago, AOL released what it thought was a data set of \u2018anonymized\u2019 search requests, but by combining bits of personally identifiable information (PII), some users in their dataset\u00a0were able to be identified<\/a>.<\/p>\n\n\n\n These are just a few examples of an ever-growing list of threats to one\u2019s privacy. It\u2019s probably a lot for most people to process.\u00a0But AI and automation technologies in the hands of cybercriminals and other malicious actors make these privacy threats exponentially worse.<\/p>\n\n\n\n As illustrated by scraping, massive amounts of data can be stolen and repurposed at high-speed using sophisticated bots. Similarly, bots can scrape geotagging information from billions of online photos, and AI can rapidly analyze these datasets to detect \u2018interesting\u2019 patterns, such as fingerprints or recognized faces. Van Eck Phreaking and similar techniques were traditionally thought to require physical proximity. Still, now the ubiquity of vulnerable IoT devices makes the large-scale invasion of privacy possible at a distance (think of The Dark Knight, when Batman hijacks every mobile phone in Gotham to emit high-frequency bursts to perform radar-like mass surveillance to find the Joker). Our security research teams have found that the entire IPv4 space can be automatically scanned for vulnerable devices in a matter of hours. They also found Internet-connected baby cameras compromised through automation and then used to\u00a0speak to children in their homes. Finally, deep learning systems take cross-correlation privacy risks to a new level, identifying patterns that humans would never find on their own. In short, automation and AI, combined with security issues, create entirely new categories of privacy threats\u2014which can be exploited at an Internet-scale.<\/p>\n\n\n\n Dealing with all of these threats in the long-term is clearly beyond most individual consumers’ abilities and energies. So, what\u2019s the solution? For a comprehensive, societal-level answer, the onus is on governmental policy and regulation, along with\u00a0platforms, products, and organizations to keep us as safe as possible<\/a>, using the best available security and privacy technology, which incorporate their own advanced AI and automation capabilities on our behalf. Over time, we have seen consumers and governments holding companies more accountable for doing this effectively, and we\u2019ve already seen\u00a0actions punishing companies that fail to protect against<\/a>\u00a0these threats. Meanwhile, companies like Apple, who are approaching product design from a privacy-first standpoint, are justly praised and rewarded.<\/p>\n\n\n\n While addressing privacy threats systemically is our best long-term defense, at the same time, we should take several simple steps ourselves that can go a long way toward protecting our own privacy, especially against today\u2019s most common risks.\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":" AI and protecting against the next generation of privacy threats By Shuman Ghosemajumder, Global Head of AI at F5 Protecting the privacy of one\u2019s own data in 2021 is hard and is seemingly getting harder. For most people, learning to use new technology isn\u2019t easy, and adapting to continual changes in products and services makes it more […]<\/p>\n","protected":false},"author":17,"featured_media":21213,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_yoast_wpseo_meta-robots-noindex":"","_et_pb_use_builder":"off","_et_pb_old_content":"","_et_gb_content_width":"","_pr_autopilot_social_copy":"","_yoast_wpseo_opengraph_title":"","_yoast_wpseo_opengraph_description":"","_yoast_wpseo_opengraph_image":"","_yoast_wpseo_opengraph_image_id":0,"_yoast_wpseo_twitter_title":"","_yoast_wpseo_twitter_description":"","_yoast_wpseo_twitter_image":"","_yoast_wpseo_twitter_image_id":0,"_yoast_wpseo_primary_category":439,"_extra_hide_author_box":"","_extra_featured_post":"0","_partner_post_id":0,"footnotes":""},"categories":[439],"tags":[],"class_list":["post-21209","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-cybersecurity","et-has-post-format-content","et_post_format-et-post-format-standard"],"yoast_head":"\n