We propose a novel failure-aware reactive UAV delivery service composition framework. A skyway network infrastructure is presented for the effective provisioning of services in urban areas. We present a formal drone delivery service model and a system architecture for reactive drone delivery services. We develop radius-based, cell density-based, and two-phased algorithms to reduce the search space and perform reactive service compositions when a service failure occurs. We conduct a set of experiments with a real drone dataset to demonstrate the effectiveness of our proposed approach.

Active intelligent reflecting surface (IRS) is a revolutionary technique for the future 6G networks. The conventional far-field single-IRS-aided directional modulation(DM) networks have only one (no direct path) or two (existing direct path) degrees of freedom (DoFs). This means that there are only one or two streams transmitted simultaneously from base station to user and will seriously limit its rate gain achieved by IRS. How to create multiple DoFs more than two for DM? In this paper, single large-scale IRS is divided to multiple small IRSs and a novel multi-IRS-aided multi-stream DM network is proposed to achieve a point-to-point multi-stream transmission by creating $K$ ($\geq3$) DoFs, where multiple small IRSs are placed distributively via multiple unmanned aerial vehicles (UAVs). The null-space projection, zero-forcing (ZF) and phase alignment are adopted to design the transmit beamforming vector, receive beamforming vector and phase shift matrix (PSM), respectively, called NSP-ZF-PA. Here, $K$ PSMs and their corresponding beamforming vectors are independently optimized. The weighted minimum mean-square error (WMMSE) algorithm is involved in alternating iteration for the optimization variables by introducing the power constraint on IRS, named WMMSE-PC, where the majorization-minimization (MM) algorithm is used to solve the total PSM. To achieve a lower computational complexity, a maximum trace method, called Max-TR-SVD, is proposed by optimize the PSM of all IRSs. Numerical simulation results has shown that the proposed NSP-ZF-PA performs much better than Max-TR-SVD in terms of rate. In particular, the rate of NSP-ZF-PA with sixteen small IRSs is about five times that of NSP-ZF-PA with combining all small IRSs as a single large IRS. Thus, a dramatic rate enhancement may be achieved by multiple distributed IRSs.

The United States says it will supply Patriot air defence missile systems to Ukraine as part of a 6bn additional aid package, Defense Secretary Lloyd Austin announced on Friday, calling it the largest security assistance package to Kyiv since Russia's invasion in 2022. The package is the second this week after President Joe Biden signed a much-delayed bill to provide a total of 61bn of new funding for Ukraine. The package also includes more munitions for the National Advanced Surface-to-Air Missile Systems, or NASAMS, and additional gear to integrate Western air defence launchers, missiles and radars into Ukraine's existing weaponry, much of which still dates back to the Soviet era. Ukrainian President Volodymyr Zelenskyy discussed the need for Patriots early on Friday with the Ukraine Defense Contact Group, a coalition of about 50 countries gathering virtually in a Pentagon-led meeting. The meeting fell on the second anniversary of the group, which Austin said has "moved heaven and Earth" since April 2022 to source millions of rounds of ammunition, rocket systems, armoured vehicles and even jets to help Ukraine rebuff Russia.

Iranian-backed Houthis rebels have claimed responsibility for a U.S. MQ-9 Reaper drone crash off the coast of Yemen on Thursday, Fox News confirmed on Friday. Thursday's crash is the fourth remotely piloted drone brought down by Iranian-proxy groups since November, costing the U.S. government upwards of 120 million. It is also the third time Houthi rebels have brought down a U.S. MQ-9 drone. Remotely piloted MQ-9 Reaper drones cost around 30 million each. Last fall, the Houthis released video of a reaper drone the rebels shot down on Nov. 8, one day after Hamas' unprovoked attack on Israel.

It is the largest security assistance package the US has committed to date, Mr Austin said, and includes air defence munitions, counter-drone systems, artillery ammunition an critical intercepts for Patriot air defence systems.

Autonomous Driving (AD) systems rely on AI components to make safety and correct driving decisions. Unfortunately, today's AI algorithms are known to be generally vulnerable to adversarial attacks. However, for such AI component-level vulnerabilities to be semantically impactful at the system level, it needs to address non-trivial semantic gaps both (1) from the system-level attack input spaces to those at AI component level, and (2) from AI component-level attack impacts to those at the system level. In this paper, we define such research space as semantic AI security as opposed to generic AI security. Over the past 5 years, increasingly more research works are performed to tackle such semantic AI security challenges in AD context, which has started to show an exponential growth trend. In this paper, we perform the first systematization of knowledge of such growing semantic AD AI security research space. In total, we collect and analyze 53 such papers, and systematically taxonomize them based on research aspects critical for the security field. We summarize 6 most substantial scientific gaps observed based on quantitative comparisons both vertically among existing AD AI security works and horizontally with security works from closely-related domains. With these, we are able to provide insights and potential future directions not only at the design level, but also at the research goal, methodology, and community levels. To address the most critical scientific methodology-level gap, we take the initiative to develop an open-source, uniform, and extensible system-driven evaluation platform, named PASS, for the semantic AD AI security research community. We also use our implemented platform prototype to showcase the capabilities and benefits of such a platform using representative semantic AD AI attacks.

Autonomous Unmanned Aerial Vehicles (UAVs) have become essential tools in defense, law enforcement, disaster response, and product delivery. These autonomous navigation systems require a wireless communication network, and of late are deep learning based. In critical scenarios such as border protection or disaster response, ensuring the secure navigation of autonomous UAVs is paramount. But, these autonomous UAVs are susceptible to adversarial attacks through the communication network or the deep learning models - eavesdropping / man-in-the-middle / membership inference / reconstruction. To address this susceptibility, we propose an innovative approach that combines Reinforcement Learning (RL) and Fully Homomorphic Encryption (FHE) for secure autonomous UAV navigation. This end-to-end secure framework is designed for real-time video feeds captured by UAV cameras and utilizes FHE to perform inference on encrypted input images. While FHE allows computations on encrypted data, certain computational operators are yet to be implemented. Convolutional neural networks, fully connected neural networks, activation functions and OpenAI Gym Library are meticulously adapted to the FHE domain to enable encrypted data processing. We demonstrate the efficacy of our proposed approach through extensive experimentation. Our proposed approach ensures security and privacy in autonomous UAV navigation with negligible loss in performance.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. A top security official in Belarus claimed Thursday that the country has prevented attempted drone strikes from Lithuania targeting the Belarusian capital and surrounding areas. He did not present evidence for the claim or give any details. He also said that "radicals" in Lithuania and Poland are producing drones to attack Belarus.

A woman has claimed that she witnessed a possible UFO while flying in a passenger airplane over New York City. Michelle Reyes shared the video online, which she capture from the window seat, showing a'flying cylinder' whizz by as she traveled over LaGuardia Airport. She told NewsNation that she observed the black object moving at high speeds - much faster than the airplane - and that another passenger had also witnessed it. A UFO expert analyzed the clip, determining no evidence that the video was fake or a hoax - but some have suggested the object was a drone. Michelle Reyes spoke NewsMax's Ashleigh Banfield about the mysterious object she spotted while flying over New York City'The first thing I did was email the FAA to let them know what I saw,' Reyes told NewsMax's Ashleigh Banfield, noting she has yet to receive a response.

Al Jazeera drone video shows the widespread destruction of neighbourhoods in Khan Younis, an area of Gaza that was declared a'safe zone' for displaced Palestinians early in the war before Israeli forces later bombed and occupied it.