Iris biometrics allow contactless authentication, which makes it widely deployed human recognition mechanisms since the couple of years. Susceptibility of iris identification systems remains a challenging task due to ...
详细信息
Ensuring user-centered phishing detection is a significant challenge due to the difficulty in distinguishing threats. To address this, we propose a personalized tool - Holistic User-Centered Identification of Threats ...
详细信息
We propose a protocol in quantum illumination (QI) leveraging entanglement in discrete-variable states. Our investigation shows that, as M→∞, the M-mode Bell state matches the 6 dB advantage of the two-mode squeezed...
详细信息
We propose a protocol in quantum illumination (QI) leveraging entanglement in discrete-variable states. Our investigation shows that, as M→∞, the M-mode Bell state matches the 6 dB advantage of the two-mode squeezed vacuum in high noise. It also excels in low- and mid-noise conditions, demonstrating that QI's benefits are not restricted to high background noise. Moreover, the protocol benefits from a sequential decision rule, increasing the advantage beyond 6 dB. These findings present an intriguing alternative to continuous-variable states and open different applications for QI using discrete-variable states.
With unexpectedness as a component of serendipity, many previous studies on serendipity-oriented recommender systems have quantified the degree of unexpectedness of items for users as a score. A user's browsing an...
详细信息
In light of recent incidents involving the leakage of private photographs of Hollywood celebrities from iCloud, the need for robust methods to safeguard image content has gained paramount importance. This paper addres...
详细信息
In light of recent incidents involving the leakage of private photographs of Hollywood celebrities from iCloud, the need for robust methods to safeguard image content has gained paramount importance. This paper addresses this concern by introducing a novel framework for reversible image editing (RIT) supported by reversible data hiding with encrypted images (RDH-EI) techniques. Unlike traditional approaches vulnerable to hacking, this framework ensures both efficient and secure data embedding while maintaining the original image’s privacy. The framework leverages two established methods: secret writing and knowledge activity. While secret writing is susceptible to hacking due to the complex nature of cipher languages, RDH-EI-supported RIT adopts a more secure approach. It replaces the linguistic content of the original image with the semantics of a different image, rendering the encrypted image visually indistinguishable from a plaintext image. This novel substitution prevents cloud servers from detecting encrypted data, enabling the adoption of reversible data hiding (RDH) methods designed for plaintext images. The proposed framework offers several distinct advantages. Firstly, it ensures the confidentiality of sensitive information by concealing the linguistic content of the original image. Secondly, it supports reversible image editing, enabling the restoration of the original image from the encrypted version without any loss of data. Lastly, the integration of RDH techniques designed for plaintext images empowers the cloud server to embed supplementary data while preserving image quality. Incorporating convolutional neural network (CNN) and generative adversarial network (GAN) models, the framework ensures accurate data extraction and high-quality image restoration. The applications of this concealed knowledge are vast, spanning law enforcement, medical data privacy, and military communication. By addressing limitations of previous methods, it opens new avenues
Conventional subspace-based direction-of-arrival (DOA) estimation algorithms require optimal environments to achieve satisfactory estimation accuracy. With the advancement of sparse signal recovery theory, sparse opti...
详细信息
This paper explores the potential of eye-tracking technology in adaptive human-machine interfaces for pilots in aviation. We argue that an interface able to adjust its layout and elements based on pilots' real-tim...
详细信息
One of the most challenging issues in computer imaging is the automated segmentation of brain tumors using Magnetic Resonance Images (MRI). Several approaches are explored using Deep Neural Networks in image segmentat...
详细信息
There has been a considerable increase in the use of drones,or unmanned aerial vehicles(UAVs),in recent times,for a wide variety of purposes such as security,surveillance,delivery,search and rescue operations,penetrat...
详细信息
There has been a considerable increase in the use of drones,or unmanned aerial vehicles(UAVs),in recent times,for a wide variety of purposes such as security,surveillance,delivery,search and rescue operations,penetration of inaccessible or unsafe areas,*** increasing number of drones working in an area poses a challenge to finding a suitable charging or resting station for each drone after completing its task or when it goes low on its *** classical methodology followed by drones is to return to their pre-assigned charging station every time it requires a *** approach is found to be inefficient as it leads to an unnecessary waste of time as well as power,which could be easily saved if the drone is allotted a nearby charging station that is ***,we propose a drone-allocation model based on a preference matching algorithm where the drones will be allotted the nearest available station to land if the station is *** problem is modeled as three entities:Drones,system controllers and charging *** matching algorithm was then used to design a Drone-Station Matching *** simulation results of our proposed model showed that there would be considerably less power consumption and more time saving over the conventional *** would save its travel time and power and ensure more efficient use of the drone.
Today,securing devices connected to the internet is challenging as security threats are generated through various *** protection of cyber-physical systems from external attacks is a primary *** presented method is pla...
详细信息
Today,securing devices connected to the internet is challenging as security threats are generated through various *** protection of cyber-physical systems from external attacks is a primary *** presented method is planned on the prime motive of detecting cybersecurity attacks and their impacted *** proposed architecture employs the LYSIS dataset and formulates Multi Variant Exploratory Data Analysis(MEDA)through Principle Component Analysis(PCA)and Singular Value Decompo-sition(SVD)for the extraction of unique *** feature mappings are analyzed with Recurrent 2 Convolutional Neural Network(R2CNN)and Gradient Boost Regression(GBR)to identify the maximum *** Late Fusion Aggregation enabled with Cyber-Net(LFAEC)is the robust derived *** quantitative analysis uses predicted threat points with actual threat variables from which mean and difference vectors *** performance of the presented system is assessed against the parameters such as Accuracy,Precision,Recall,and F1 *** proposed method outperformed by 98% to 100% in all quality measures compared to existing methods.
暂无评论