During four separate Israeli military attacks on Gaza (2006, 2009, 2012, and 2014), about 4000 Palestinians were killed and more than 17 000 injured (412 killed and 1264 injured in 2006; 1383 killed ...and more than 5300 injured in 2009; 130 killed and 1399 injured in 2012; and 2251 killed and 11 231 injured in 2014). An unknown number of people had traumatic amputations of one or more extremities. Use of unmanned Israeli drones for surveillance and armed attacks on Gaza was evident, but exact figures on numbers of drone strikes on Gaza are not available. The aim of this study was to explore the medical consequences of strikes on Gaza with different weapons, including drones.
We studied a cohort of civilians in the Gaza Strip who had one of more traumatic limb amputation during the Israeli military attacks between 2006 and 2016. The study was done at The Artificial Limb and Polio Center (ALPC) in the Gaza Strip where most patients are treated and trained after amputation. We used standardised forms and validated instruments to record date and mechanism of injury, self-assessed health, socioeconomic status, anatomical location and length of amputation, comorbidity, and the results of a detailed clinical examination.
The studied cohort consisted of 254 Paletinian civilians (234 92% men, 20 8% women, and 43 17% children aged 18 years and younger) with traumatic amputations caused by different weapons. 216 (85%) people had amputations proximal to wrist or ankle, 131 (52%) patients had more than one major amputation or an amputation above the knee, or both, and 136 (54%) people were injured in attacks with Israeli drones, including eight (40%) of the women. The most severe amputations were caused by drone attacks (p=0·0001). Extremity injuries after drone attacks led to immediate amputation more often than with other weapons (p=0·014). Patients injured during cease-fire periods were younger than patients injured during periods of declared Israeli military operations (p=0·0001).
Weapons fired on the Gaza Strip from Israeli drones caused severe injuries in surviving Palestinian civilians. Drone-fired missiles resulted in major amputations in almost all victims who had limb losses. Substantially more severe injuries were inflicted by the drone-launched explosives than by other weapons used during the Gaza War. Traumatic amputations caused by drones were often immediately complete. One limitation of our study is that it does not elucidate injury patterns in victims with fatal injuries.
None.
More so than in the past, the US is now embracing the logic of preventive force: using military force to counter potential threats around the globe before they have fully materialized. While popular ...with individuals who seek to avoid too many "boots on the ground," preventive force is controversial because of its potential for unnecessary collateral damage. Who decides what threats are 'imminent'? Is there an international legal basis to kill or harm individuals who have a connection to that threat? Do the benefits of preventive force justify the costs? And, perhaps most importantly, is the US setting a dangerous international precedent?
InPreventive Force, editors Kerstin Fisk and Jennifer Ramos bring together legal scholars, political scientists, international relations scholars, and prominent defense specialists to examine these questions, whether in the context of full-scale preventive war or preventive drone strikes. In particular, the volume highlights preventive drones strikes, as they mark a complete transformation of how the US understands international norms regarding the use of force, and could potentially lead to a 'slippery slope' for the US and other nations in terms of engaging in preventive warfare as a matter of course. A comprehensive resource that speaks to the contours of preventive force as a security strategy as well as to the practical, legal, and ethical considerations of its implementation,Preventive Forceis a useful guide for political scientists, international relations scholars, and policymakers who seek a thorough and current overview of this essential topic.
The Internet of Drones (IoD) provides a coordinated access to unmanned aerial vehicles that are referred as drones. The on-going miniaturization of sensors, actuators, and processors with ubiquitous ...wireless connectivity makes drones to be used in a wide range of applications ranging from military to civilian. Since most of the applications involved in the IoD are real-time based, the users are generally interested in accessing real-time information from drones belonging to a particular fly zone. This happens if we allow users to directly access real-time data from flying drones inside IoD environment and not from the server. This is a serious security breach which may deteriorate performance of any implemented solution in this IoD environment. To address this important issue in IoD, we propose a novel lightweight user authentication scheme in which a user in the IoD environment needs to access data directly from a drone provided that the user is authorized to access the data from that drone. The formal security verification using the broadly accepted automated validation of Internet security protocols and applications tool along with informal security analysis show that our scheme is secure against several known attacks. The performance comparison demonstrates that our scheme is efficient with respect to various parameters, and it provides better security as compared to those for the related existing schemes. Finally, the practical demonstration of our scheme is done using the widely accepted NS2 simulation.
With accelerated advances in various technologies, drones, better known as unmanned aerial vehicles (UAVs), are increasingly commonplace and consequently have a more pronounced impact on society. For ...example, Internet of Drones (IoD), a new communication paradigm offering fundamental navigation assistance and access to information, has widespread applications ranging from agricultural drones in farming to surveillance drones in the COVID-19 pandemic. The increasingly prominent role of IoD in our society also reinforces the importance of securing such systems against various data privacy and security threats. Operationally, it can be challenging to adopt conventional off-the-shelf security products in an IoD system due to the underpinning characteristics of drones (e.g., dynamic and open communication channel). Therefore in this article, we propose a lightweight and privacy-preserving mutual authentication and key agreement protocol, hereafter referred to as PMAP. The latter uses a physical unclonable function (PUF) and chaotic system to support mutual authentication and establish a secure session key between communication entities in the IoD system. To be specific, PMAP consists of two schemes, namely: 1) <inline-formula> <tex-math notation="LaTeX">{\mathrm{ PMAP}}^{D2Z} </tex-math></inline-formula> (that mutually authenticates drone and zone service provider (ZSP) and establishes secure session keys) and 2) <inline-formula> <tex-math notation="LaTeX">{\mathrm{ PMAP}}^{D2D} </tex-math></inline-formula> (that mutually authenticates drones and establishes secure session keys). In addition, PMAP supports conditional privacy preserving so that the genuine identity of drones can only be revealed by trusted ZSPs. We evaluate the security of PMAP using automated validation of Internet security protocols and application (AVISPA), as well as provide formal and informal security analysis to show the resilience of PMAP against various security attacks. We also evaluate the performance of PMAP through extensive experiments and compare its performance with existing AKA and IBE-Lite schemes, whose findings show that PMAP achieves better performance in terms of computation cost, energy consumption, and communication overhead.
•Deep learning algorithm for identification of type and flight mode of detected drones.•Novel deep learning algorithm for detection of multiple drones in radio frequency domain.•Results of three ...indoor experiments concerning collecting and analyzing radio signals from drones.•Public available database with radio signals of drones from two different radio frequency bands.
Unmanned aerial systems, especially drones have gone through remarkable improvement and expansion in recent years. Drones have been widely utilized in many applications and scenarios, due to their low price and ease of use. However, in some applications drones can pose a malicious threat. To diminish risks to public security and personal privacy, it is necessary to deploy an effective and affordable anti-drone system in sensitive areas to detect, localize, identify, and defend against intruding malicious drones. This research article presents a new publicly available radio frequency drone dataset and investigates detection and identification methodologies to detect single or multiple drones and identify a single detected drone's type. Moreover, special attention in this paper has been underlined to examine the possibility of using deep learning algorithms, particularly fully connected deep neural networks as an anti-drone solution within two different radio frequency bands. We proposed a supervised deep learning algorithm with fully-connected deep neural network models that use raw drone signals rather than features. Regarding the research results, the proposed algorithm shows a lot of potentials. The probability of detecting a single drone is 99.8%, and the probability of type identification is 96.1%. Moreover, the results of multiple drones detection demonstrate an average accuracy of 97.3%. There have not been such comprehensive publications, to this time, in the open literature that have presented and enlightened the problem of multiple drones detection in the radio frequency domain.
PDF
