Implementation of IoT domain invites tremendous attacking opportunities which demands end to - end security mechanism. applications related to the domain of IoT varies from critical applications to normal business-ori...
详细信息
Cloud industry is facing significant challenges related to resource under-utilization and high energy consumption. Virtual Machine Consolidation serves as an effective solution to address these issues. However, Virtua...
详细信息
Sequence-to-sequence models are fundamental building blocks for generating abstractive text summaries, which can produce precise and coherent summaries. Recently proposed, different text summarization models aimed to ...
详细信息
Message Queuing Telemetry Transport (MQTT) has emerged as the widely adopted application layer protocol for IoT environments because of its lightweight header, minimal power, and bandwidth requirements. Despite its po...
详细信息
Message Queuing Telemetry Transport (MQTT) has emerged as the widely adopted application layer protocol for IoT environments because of its lightweight header, minimal power, and bandwidth requirements. Despite its popularity, the earlier version of the protocol, MQTT v3.1.1, encounters performance issues in large-scale implementations and required an update to handle the growing requirements of modern IoT applications. In response to these concerns, MQTT v5.0 was released with several significant features designed to enhance the reliability, user experience, and performance of IoT systems. While the MQTT protocol features were intended to facilitate robust and efficient communications, adversaries could exploit these features to mount various types of attacks in IoT deployments. More specifically, the Denial of Service (DoS) attacks towards the MQTT protocol have recently gained a lot of attention from the research community. However, the existing works primarily focus only on exploring the possibilities of misusing the MQTT v3.1.1 protocol features to generate DoS attacks in IoT realms. In this work, we attempt to extensively investigate the advanced protocol features of MQTT v5.0 that can be exploited to launch DDoS attacks impacting the IoT paradigm. We present the first critical evaluation of Distributed Denial of Service (DDoS) attacks on the MQTT v5.0 protocol by analyzing three significant features: CONNECT Properties, User Properties, and Flow Control. Moreover, we systematically propose attack scenarios based on the adversary's capabilities, thus illustrating the practicality of proposed attacks in real-world scenarios. Furthermore, we built a real-world testbed for IoT healthcare application to evaluate the severity of the identified attacks. The experimental results demonstrate the effectiveness of these attacks in impacting the availability of guaranteed IoT services to legitimate users, even in times of need. Additionally, we disclose the insightful fi
The provision of rebate to needy/underprivileged sections of society has been in practice since long in government organizations. The efficacy of such provisions lies in the fact that whether this rebate reaches peopl...
详细信息
The rigorous security requirements and domain experts are necessary for the tuning of firewalls and for the detection of attacks. Those firewalls may create an incorrect sense or state of protection if they are improp...
详细信息
Omnidirectional images provide an immersive viewing experience in a Virtual Reality (VR) environment, surpassing the limitations of traditional 2D media beyond the conventional screen. This VR technology allows users ...
详细信息
Omnidirectional images provide an immersive viewing experience in a Virtual Reality (VR) environment, surpassing the limitations of traditional 2D media beyond the conventional screen. This VR technology allows users to interact with visual information in an exciting and engaging manner. However, the storage and transmission requirements for 360-degree panoramic images are substantial, leading to the establishment of compression frameworks. Unfortunately, these frameworks introduce projection distortion and compression artifacts. With the rapid growth of VR applications, it becomes crucial to investigate the quality of the perceptible omnidirectional experience and evaluate the extent of visual degradation caused by compression. In this regard, viewport plays a significant role in omnidirectional image quality assessment (OIQA), as it directly affects the user’s perceived quality and overall viewing experience. Extracting viewports compatible with users viewing behavior plays a crucial role in OIQA. Different users may focus on different regions, and the model’s performance may be sensitive to the chosen viewport extraction strategy. Improper selection of viewports could lead to biased quality predictions. Instead of assessing the entire image, attention can be directed to areas that are more importance to the overall quality. Feature extraction is vital in OIQA as it plays a significant role in representing image content that aligns with human perception. Taking this into consideration, the proposed ATtention enabled VIewport Selection (ATVIS-OIQA) employs attention based view port selection with Vision Transformers(ViT) for feature extraction. Furthermore, the spatial relationship between the viewports is established using graph convolution, enabling intuitive prediction of the objective visual quality of omnidirectional images. The effectiveness of the proposed model is demonstrated by achieving state-of-the-art results on publicly available benchmark datasets, n
Deep learning has reached many successes in Video *** has become a growing important part of our daily digital *** advancement of better resolution content and the large volume offers serious challenges to the goal of...
详细信息
Deep learning has reached many successes in Video *** has become a growing important part of our daily digital *** advancement of better resolution content and the large volume offers serious challenges to the goal of receiving,distributing,compressing and revealing highquality video *** this paper we propose a novel Effective and Efficient video compression by the Deep Learning framework based on the flask,which creatively combines the Deep Learning Techniques on Convolutional Neural Networks(CNN)and Generative Adversarial Networks(GAN).The video compression method involves the layers are divided into different groups for data processing,using CNN to remove the duplicate frames,repeating the single image instead of the duplicate images by recognizing and detecting minute changes using GAN and recorded with Long Short-Term Memory(LSTM).Instead of the complete image,the small changes generated using GAN are substituted,which helps with frame-level *** wise comparison is performed using K-nearest Neighbours(KNN)over the frame,clustered with K-means and Singular Value Decomposition(SVD)is applied for every frame in the video for all three colour channels[Red,Green,Blue]to decrease the dimension of the utility matrix[R,G,B]by extracting its latent *** frames are packed with parameters with the aid of a codec and converted to video format and the results are compared with the original *** experiments on several videos with different sizes,duration,Frames per second(FPS),and quality results demonstrated a significant resampling *** normal,the outcome delivered had around a 10%deviation in quality and over half in size when contrasted,and the original video.
In today’s era, smartphones are used in daily lives because they are ubiquitous and can be customized by installing third-party apps. As a result, the menaces because of these apps, which are potentially risky for u...
详细信息
Object detection and image restoration pose significant challenges in deep learning and computer vision. These tasks are widely employed in various applications, and there is an increasing demand for specialized envir...
详细信息
暂无评论