This anti-detection starter pack came recommended for those looking to shield themselves from government surveillance while protesting in support of Black Lives Matter. In the future, the Federal Aviation Agency might be a resource added to the list. The gamut of surveillance tools used during protests runs wide. It's unlikely that your Twitter account was hacked, much like Donald Trump's was thought to be last month, to determine your location while protesting. But it may have been analyzed with a social media scanning tool.

Unmanned aerial vehicles (UAVs) can be deployed to monitor very large areas without the need for network infrastructure. UAVs communicate with each other during flight and exchange information with each other. However, such communication poses security challenges due to its dynamic topology. To solve these challenges, the proposed method uses two phases to counter malicious UAV attacks. In the first phase, we applied a number of rules and principles to detect malicious UAVs. In this phase, we try to identify and remove malicious UAVs according to the behavior of UAVs in the network in order to prevent sending fake information to the investigating UAVs. In the second phase, a mobile agent based on a three-step negotiation process is used to eliminate malicious UAVs. In this way, we use mobile agents to inform our normal neighbor UAVs so that they do not listen to the data generated by the malicious UAVs. Therefore, the mobile agent of each UAV uses reliable neighbors through a three-step negotiation process so that they do not listen to the traffic generated by the malicious UAVs. The NS-3 simulator was used to demonstrate the efficiency of the SAUAV method. The proposed method is more efficient than CST-UAS, CS-AVN, HVCR, and BSUM-based methods in detection rate, false positive rate, false negative rate, packet delivery rate, and residual energy.

The U.S. Air Force recently bought dozens of Chinese-made drones to use for testing and training, according to officials and records of the purchase, fueling concerns about continued Defense Department use of technology that lawmakers consider a threat to national security. The Air Force Special Operations Command, the service's highly trained commando division, bought 57 drones in September from Da-Jiang Innovations, or DJI, the world's largest maker of unmanned aerial systems, based in Shenzhen, China.

A handful of drone-delivery startups want to help transport Covid-19 vaccines from distribution facilities to health centers, vying for a logistical role in what is likely to be a sprawling and complex undertaking. Several of these businesses recently have entered into medical delivery partnerships with drug companies and retailers--including Merck & Co. and Walmart Inc.-- that could help position them to take part in the high-profile effort to distribute Covid-19 vaccines.

Neuromorphic processors like Loihi offer a promising alternative to conventional computing modules for endowing constrained systems like micro air vehicles (MAVs) with robust, efficient and autonomous skills such as take-off and landing, obstacle avoidance, and pursuit. However, a major challenge for using such processors on robotic platforms is the reality gap between simulation and the real world. In this study, we present for the very first time a fully embedded application of the Loihi neuromorphic chip prototype in a flying robot. A spiking neural network (SNN) was evolved to compute the thrust command based on the divergence of the ventral optic flow field to perform autonomous landing. Evolution was performed in a Python-based simulator using the PySNN library. The resulting network architecture consists of only 35 neurons distributed among 3 layers. Quantitative analysis between simulation and Loihi reveals a root-mean-square error of the thrust setpoint as low as 0.005 g, along with a 99.8% matching of the spike sequences in the hidden layer, and 99.7% in the output layer. The proposed approach successfully bridges the reality gap, offering important insights for future neuromorphic applications in robotics. Supplementary material is available at https://mavlab.tudelft.nl/loihi/.

At the outset of World War II, you'd have a better chance of finding a needle in a haystack with a camel stuck in its eye than you did shooting down an enemy aircraft in your first dozen or so shots. This is because anti-aircraft shells at the time used manual fuses that had to be dialed in for specific lengths of time to delay their explosion. The idea was that you'd estimate where the targeted plane would be in, say five seconds, based on its currently flight path, then time the shell for that length, fire the shell at the plane and hope that the timing and location were close enough that shrapnel from the exploding shell hits the plane. If your calculations were off by even a hair, the shell would miss by thousands of feet. And if shooting down piloted aircraft was this hard, intercepting Germany's terrifyingly fast V1 and V2 rockets required far more luck than skill. But that's exactly what the team at Section T set out to do.

NCCR Robotics researchers at EPFL have developed a drone with a feathered wing and tail that give it unprecedented flight agility. The northern goshawk is a fast, powerful raptor that flies effortlessly through forests. This bird was the design inspiration for the next-generation drone developed by scientists of the Laboratory of Intelligent Systems of EPFL led by Dario Floreano. They carefully studied the shape of the bird's wings and tail and its flight behavior, and used that information to develop a drone with similar characteristics. "Goshawks move their wings and tails in tandem to carry out the desired motion, whether it is rapid changes of direction when hunting in forests, fast flight when chasing prey in the open terrain, or when efficiently gliding to save energy," says Enrico Ajanic, the first author and PhD student in Floreano's lab. Floreano adds: "our design extracts principles of avian agile flight to create a drone that can approximate the flight performance of raptors, but also tests the biological hypothesis that a morphing tail plays an important role in achieving faster turns, decelerations, and even slow flight."

Fifteen years ago, when I returned home after fighting in Iraq, a friend asked me to describe the bravest thing I saw anyone do. I had led a Marine platoon in the Second Battle of Fallujah, in 2004, and had seen plenty of heroism--Marines dragging their wounded off machine-gun-swept streets, or fighting room to room to recover a comrade's body. But none of these compared to the cumulative heroism of the 19- and 20-year-old infantrymen who placed their bodies across that fatal funnel--a doorway with a potential enemy inside--every day. Clearing the enemy from the city, house by house, was a game of Russian roulette played on a grand scale. You never knew who might be waiting on the other side of the door.

Japan may effectively shut off China from supplying drones to its government to protect sensitive information, according to six people in government and the ruling party familiar with the matter, as part of a broad effort to bolster national security. The primary concerns, those people said, centered on information technology, supply chains, cybersecurity and intellectual property -- worries that have been rising outside Japan as well. But Japan must balance such fears -- particularly Beijing's growing push to export sensitive technologies such as commercial drones and security cameras -- against deep economic dependence on China. It must also navigate increasingly choppy waters between China and Japan's closest ally, the United States, which is at odds with Beijing over many things, including technology. "China is a big market and it is important for Japan," one of the senior government officials said. "On the other hand, there are worries that advanced technologies and information could leak to China and could be diverted for military use."

This paper presents a smart contract-based solution for autonomous administration of construction progress payments. It bridges the gap between payments (cash flow) and the progress assessments at job sites (product flow) enabled by reality capture technologies and building information modeling (BIM). The approach eliminates the reliance on the centralized and heavily intermediated mechanisms of existing payment applications. The construction progress is stored in a distributed manner using content addressable file sharing; it is broadcasted to a smart contract which automates the on-chain payment settlements and the transfer of lien rights. The method was successfully used for processing payments to 7 subcontractors in two commercial construction projects where progress monitoring was performed using a camera-equipped unmanned aerial vehicle (UAV) and an unmanned ground vehicle (UGV) equipped with a laser scanner. The results show promise for the method's potential for increasing the frequency, granularity, and transparency of payments. The paper is concluded with a discussion of implications for project management, introducing a new model of project as a singleton state machine.