Industry
Channel State Information Analysis for Jamming Attack Detection in Static and Dynamic UAV Networks -- An Experimental Study
Mykytyn, Pavlo, Chitauro, Ronald, Dyka, Zoya, Langendoerfer, Peter
--Networks built on the IEEE 802.11 standard have experienced rapid growth in the last decade. Their field of application is vast, including smart home applications, Internet of Things (IoT), and short-range high throughput static and dynamic inter-vehicular communication networks. Within such networks, Channel State Information (CSI) provides a detailed view of the state of the communication channel and represents the combined effects of multipath propagation, scattering, phase shift, fading, and power decay. In this work, we investigate the problem of jamming attack detection in static and dynamic vehicular networks. We utilize ESP32-S3 modules to set up a communication network between an Unmanned Aerial V ehicle (UA V) and a Ground Control Station (GCS), to experimentally test the combined effects of a constant jammer on recorded CSI parameters, and the feasibility of jamming detection through CSI analysis in static and dynamic communication scenarios. The rapid expansion of IEEE 802.11 networks over the past decade has revolutionized wireless communications, particularly in such applications as smart homes [1], Internet of Things (IoT) [2], industrial automation, and short-range high-throughput vehicular networks [3]. This can be contributed to their high throughput capabilities, ease of deployment, and increasingly growing demand for internet connectivity. However, the widespread usage and extensive deployment of these networks make them an attractive target for malicious actors, and thus, more exposed and susceptible to jamming attacks.
StereoDetect: Detecting Stereotypes and Anti-stereotypes the Correct Way Using Social Psychological Underpinnings
Shejole, Kaustubh Shivshankar, Bhattacharyya, Pushpak
Stereotypes are known to have very harmful effects, making their detection critically important. However, current research predominantly focuses on detecting and evaluating stereotypical biases, thereby leaving the study of stereotypes in its early stages. Our study revealed that many works have failed to clearly distinguish between stereotypes and stereotypical biases, which has significantly slowed progress in advancing research in this area. Stereotype and Anti-stereotype detection is a problem that requires social knowledge; hence, it is one of the most difficult areas in Responsible AI. This work investigates this task, where we propose a five-tuple definition and provide precise terminologies disentangling stereotypes, anti-stereotypes, stereotypical bias, and general bias. We provide a conceptual framework grounded in social psychology for reliable detection. We identify key shortcomings in existing benchmarks for this task of stereotype and anti-stereotype detection. To address these gaps, we developed StereoDetect, a well curated, definition-aligned benchmark dataset designed for this task. We show that sub-10B language models and GPT-4o frequently misclassify anti-stereotypes and fail to recognize neutral overgeneralizations. We demonstrate StereoDetect's effectiveness through multiple qualitative and quantitative comparisons with existing benchmarks and models fine-tuned on them. The dataset and code is available at https://github.com/KaustubhShejole/StereoDetect.
Integrating Identity-Based Identification against Adaptive Adversaries in Federated Learning
Szelag, Jakub Kacper, Chin, Ji-Jian, Ansell, Lauren, Yip, Sook-Chin
Federated Learning (FL) has recently emerged as a promising paradigm for privacy-preserving, distributed machine learning. However, FL systems face significant security threats, particularly from adaptive adversaries capable of modifying their attack strategies to evade detection. One such threat is the presence of Reconnecting Malicious Clients (RMCs), which exploit FLs open connectivity by reconnecting to the system with modified attack strategies. To address this vulnerability, we propose integration of Identity-Based Identification (IBI) as a security measure within FL environments. By leveraging IBI, we enable FL systems to authenticate clients based on cryptographic identity schemes, effectively preventing previously disconnected malicious clients from re-entering the system. Our approach is implemented using the TNC-IBI (Tan-Ng-Chin) scheme over elliptic curves to ensure computational efficiency, particularly in resource-constrained environments like Internet of Things (IoT). Experimental results demonstrate that integrating IBI with secure aggregation algorithms, such as Krum and Trimmed Mean, significantly improves FL robustness by mitigating the impact of RMCs. We further discuss the broader implications of IBI in FL security, highlighting research directions for adaptive adversary detection, reputation-based mechanisms, and the applicability of identity-based cryptographic frameworks in decentralized FL architectures. Our findings advocate for a holistic approach to FL security, emphasizing the necessity of proactive defence strategies against evolving adaptive adversarial threats.
A Real-time Face Mask Detection and Social Distancing System for COVID-19 using Attention-InceptionV3 Model
Asif, Abdullah Al, Tisha, Farhana Chowdhury
One of the deadliest pandemics is now happening in the current world due to COVID-19. This contagious virus is spreading like wildfire around the whole world. To minimize the spreading of this virus, World Health Organization (WHO) has made protocols mandatory for wearing face masks and maintaining 6 feet physical distance. In this paper, we have developed a system that can detect the proper maintenance of that distance and people are properly using masks or not. We have used the customized attention-inceptionv3 model in this system for the identification of those two components. We have used two different datasets along with 10,800 images including both with and without Face Mask images. The training accuracy has been achieved 98% and validation accuracy 99.5%. The system can conduct a precision value of around 98.2% and the frame rate per second (FPS) was 25.0. So, with this system, we can identify high-risk areas with the highest possibility of the virus spreading zone. This may help authorities to take necessary steps to locate those risky areas and alert the local people to ensure proper precautions in no time.
A long lost silver dollar may be worth 5 million
The'King of American Coins' remained hidden in a late collector's archive for decades. Breakthroughs, discoveries, and DIY tips sent every weekday. One of the country's rarest coins is rarer than even expert coin collectors believed. After the surprise discovery of a long-lost 1804 dollar (aka the " King of American Coins "), the rarity's total known count now stands at 16. Regardless of its ranking, the silver coin is expected to fetch significantly more than its original worth when it hits the auction block on December 9. According to auctioneers at Stack's Bowers Galleries, the story begins with former President Andrew Jackson.
Haaland joins Premier League 100 club - who else is in it?
Haaland joins Premier League 100 club - who else is in it? Erling Haaland has become the 35th footballer to join the Premier League's '100 club' by reaching a century of goals in the competition with the opener in Manchester City's fixture at Fulham. The Norwegian striker has also become the fastest player to reach the milestone, with his 100th goal coming in his 111th game - beating Alan Shearer's previous record, set in 1995, by 13 appearances. Haaland's total goals-per-game rate in the Premier League is now 0.90, and he may eventually challenge for Shearer's overall goals record of 260 in the division, which launched in 1992-93 when it broke away from the English Football League. Haaland's City contract - a record nine-and-a-half-year deal announced in January - runs through to the end of the 2033-34 season.
The 157 Best Cyber Week Deals--Save up to 57% Off Gear We Love
Cyber Monday is over, but many deals are still available, at least for now. These are the absolute best discounts on gear we've tested ourselves. Cyber Monday may be over, but many Cyber Week deals are still going strong. Whether you're checking off your holiday shopping or snagging a special treat for yourself, now's the time to pounce. The WIRED Reviews team has hundreds of years of collective experience tracking deals--not just inflated markdowns--on products we've hand-tested. Below, you'll find everything that made the cut and is still on sale: True discounts on the gear and gadgets we'd recommend to our friends and family. Amazon Kindle Paperwhite (2024, 12th Generation) $ 160 Our all-time favorite Kindle packs a three-month battery life, an auto-adjusting warm light, and a nice seven-inch screen for one of the best e-reader experiences. Dell had a killer $500 discount all weekend on the Core Ultra 5 version of its Dell 14 Plus. It was a high-end laptop being sold for downright budget-level prices. It's sold out now, unfortunately. But the current discount is still quite good. This is a very strong display for a laptop at this price. While the Surface Laptop is better in many ways, the $650 Dell 14 Plus gets you a full terabyte of storage. Microsoft's Surface Laptop is the closest thing the Windows world has to a MacBook, and it's never been so cheap. Usually, inexpensive Chromebooks have subpar displays and touchpads, but this Acer model's are just fine--at a killer price. Our favorite gaming laptop has a sleek, thin design and impressive graphics. Weighing only 2.16 pounds, it's one of the lightest laptops you can buy, without making any major sacrifices to achieve that weight. The M4 MacBook Air has been the best laptop on the market since it was released in 2024.
OECD warns tariffs, AI will test resilience of the global economy
Global growth is holding up better than expected as an artificial intelligence (AI) investment boom helps offset some of the shock from United States tariff hikes, according to the Organisation for Economic Co-operation and Development (OECD). The Paris-based organisation, however, warned on Tuesday that global growth was vulnerable to any new outbreak of trade tensions, while investor optimism about AI could trigger a stock market correction if expectations are not met. It predicted a rebound to 3.1 percent in 2027. OECD head Mathias Cormann said the trade shocks triggered by US President Donald Trump's tariff hikes had so far proved relatively mild, but added their costs were likely to rise. "The full effects of those higher tariffs since the start of the year will become clearer as firms run down the inventories that they built up," he told a press conference.
How to tell time on Mars
Physicists finally know how much faster time moves on the Red Planet. Breakthroughs, discoveries, and DIY tips sent every weekday. Tracking the first astronauts' visit to Mars won't be as simple as watching a clock or marking days off of a calendar. Thanks to relativity, time actually moves faster on the Red Planet than it does here on Earth. For years, scientists have wondered about the exact temporal difference between planets, but physicists at the National Institute of Standards and Technology (NIST) finally have an answer.