WiFi Security: Assessment of threats in wireless networks
08/03/2024Wifi connectivity has gone from being limited to restricted environments to becoming omnipresent in virtually every aspect of our daily lives. The ability to connect to the Internet from anywhere, be it at home, in a café, at work, in public spaces, or even in-flight, has enhanced the convenience in our daily lives. Moreover, the expansion of Wifi networks and the use of new manufacturing technologies now allow the interconnection of devices, leading to the significant rise of the Internet of Things (IoT) and providing users with more comprehensive control over their digital environments. However, this proliferation of Wifi networks has also given rise to new threats that require careful evaluation and effective security strategies to ensure secure and risk-free Wifi connections for our data and information. Common Wifi security threats include data interception Man-in-the-Middle (MITM) attacks One of the fundamental challenges in Wifi security is preventing MITM attacks, where an intruder inserts themselves into the communication between two parties, compromising the integrity and confidentiality of sensitive data such as passwords and financial information. Spoofing of access points Hackers can create fake Wifi networks that mimic legitimate ones to attract unsuspecting users. Once connected to these malicious networks, our data can be captured by cybercriminals who may sell or misuse it for illicit purposes. Tips for achieving a secure Wifi connection: Strengthen authentication and use security protocols Prioritize strong encryption for networks to protect confidential information transmitted through it. WPA (Wifi Protected Access) encryption uses stronger algorithms than its predecessor, WEP (Wired Equivalent Privacy), making it more difficult for hackers to intercept and decipher data. Advanced security protocols like WPA3 provide individualized data encryption and advanced two-factor authentication (2FA) methods, adding an extra layer of security by requiring additional verification. Device management Properly manage and monitor devices connected to Wifi networks to minimize risks associated with the large number of connected devices in homes and businesses. Regularly update the router firmware and all connected devices to address potential vulnerabilities. Segmentation of the network to separate critical devices from less secure ones also helps mitigate the risk of threat propagation. Secure Router Configuration The router secure configuration is what will ensure the robustness and overall security of a wireless network. The router, being the first point of contact for devices connected to the Internet, acts as the first line of defence against potential attacks. For this reason, it is important to understand that the proper configuration of the router not only guarantees a stable and efficient connection but also establishes a protected environment that safeguards the integrity and privacy of our data. How to configure the router securely? To ensure a correct and secure configuration of the router, it is recommended to: Change the default username and password of the router, as these are easily accessible to attackers. Use strong passwords containing a combination of letters, numbers, and special characters. Disable remote administration to prevent cybercriminals from accessing the router externally. Enable WPA2 or WPA3 encryption instead of the outdated WEP for enhanced network security. Optionally, disable SSID broadcast to make the network less visible and harder to detect by hackers. Keep the router firmware updated to address vulnerabilities and improve overall device security. By following these steps, you will strengthen the security of your wireless network and reduce the chances of experiencing unwanted attacks or intrusions.
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Google Maps will use AI to update store hours
14/04/2022Google Maps will update the hours of more than 20 million businesses around the world in the next six months. To do this, they will use Artificial Intelligence (AI) and a self-developed machine learning model, which identifies shop hours that are not updated. Through this system, the AI will update the hours according to itsel predictions based on parameters such the last update of the shop's profile, the hours of nearby stores and the busiest hours in that location. In addition, the algorithm will take datas from Google Business, information from the store's website, if it has one, and images from Street View. In some countries, Google will also use Google Duplex conversational AI technology to make calls with the quality of a human voice to the stores and confirm their opening hours. In this list of countries, France will be the only European country where the telephone verification will be carried out. The rest of the countries are Argentina, Australia, Chile, Japan, Mexico, New Zealand, Peru and the United States.
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Recycling containers connected to the mobile to reward the citizen
31/03/2022The Spanish startup Recircula Solutions has just presented Recysmart to the market, a device that can be installed in any type of urban container and identify the material of the recycled packages. The objective of this development is to promote incentive programs that helps population to recycle. The device combines a unique mechanical design with AI algorithms based on acoustics, so the unique and characteristic acoustic signal that a package generates when it's inserted into a container is captured by the sensor, processed and reported in real time to the managers authoritys so they can remunerate the person who has use the container. To do this, the citizen will have previously identified himself on the device through his mobile or using a physical card. In Sant Cugat del Vallés (Barcelona) several of these devices have been installed in various containers in the town. Recircula Solutions will also send several units to Portugal, Austria, France, the United Kingdom and Greece.
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Makeup causes failures in facial recognition systems
22/09/2021A research from the Ben-Gurion University of Israel has concluded that makeup reduces the effectiveness of facial recognition mechanisms. During the tests, the researchers used the ArcFace facial detection system, and they determined an effectiveness of 47,6% in people who did not use make up and 33,7% in those who did. They also confirm that applying makeup in specific face areas that algorithms analyze, the effectiveness of the facial recognition system is significantly altered and only 1.22% persons were recognized. In addition, the researchers from the Israeli university also did the test digitally, making up some photographs of the volunteers and the result was that the system was not able to recognize any of the faces. According to all these results, the researchers believe that the current level of development of facial detection systems is still below the realistic threshold.
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