Forecasting the direction and trend of stock price is an important task which helps investors to make prudent financial decisions in market. Investment market has a big risk associated with it. Minimizing prediction error reduces investment risk. Machine learning (ML) models typically perform better than statistical econometric models. Also, ensemble ML have been shown literature be able produce superior performance single In this work, we compare effectiveness tree-based (Random Forest...

Internet of Medical Things (IoMT) can connect many medical imaging equipment to the information network facilitate process diagnosing and treating doctors. As image contains sensitive information, it is importance yet very challenging safeguard privacy or security patient. In this work, a deep-learning-based encryption decryption (DeepEDN) proposed fulfill encrypting decrypting image. Specifically, in DeepEDN, cycle-generative adversarial (Cycle-GAN) employed as main learning transfer from...

While 5G can facilitate high-speed Internet access and make over-the-horizon control a reality for unmanned aerial vehicles (UAVs; also known as drones), there are potential security privacy considerations, example, authentication among drones. Centralized approaches not only suffer from single point of failure but they incapable cross-domain authentication. This complicates the cooperation drones different domains. To address these limitations, blockchain-based scheme intelligent 5G-enabled...

The need for medical image encryption is increasingly pronounced, example, to safeguard the privacy of patients' imaging data. In this article, a novel deep learning-based key generation network (DeepKeyGen) proposed as stream cipher generator generate private key, which can then be used encrypting and decrypting images. DeepKeyGen, generative adversarial (GAN) adopted learning key. Furthermore, transformation domain (that represents "style" generated) designed guide realize process. goal...

Pneumonia is a microorganism infection that causes chronic inflammation of the human lung cells. Chest X-ray imaging most well-known screening approach used for detecting pneumonia in early stages. While chest-Xray images are mostly blurry with low illumination, strong feature extraction required promising identification performance. A new hybrid explainable deep learning framework proposed accurate disease using chest images. The workflow developed by fusing capabilities both ensemble...

To ensure the security and privacy of patient's health status in wireless body area networks (WBANs), it is critical to secure extra-body communication between smart portable device held by WBAN client application providers, such as hospital, physician or medical staff. Based on certificateless cryptography, this paper proposes a remote authentication protocol featured with nonrepudiation, anonymity, key escrow resistance, revocability for WBANs. First, we present encryption scheme signature...

Device authentication is a critical and challenging issue for the emerging Internet of Things (IoT). One promising solution to authenticate IoT devices extract fingerprint perform device by exploiting variations in transmitted signal caused hardware manufacturing inconsistencies. In this paper, we propose lightweight protocol [named speaker-to-microphone (S2M)] leveraging frequency response speaker microphone from two wireless as acoustic fingerprint. S2M authenticates legitimate user...

As a cornerstone service for many Internet of Things applications, channel state information (CSI)-based activity recognition has received immense attention over recent years. However, performance general approaches might significantly decrease when applying the trained model to left-out user whose CSI data are not used training. To overcome this challenge, we propose semi-supervised generative adversarial network (GAN) CSI-based (CsiGAN). Based on GANs, mainly design three components CsiGAN...

Privacy in the Internet of Things is a fundamental challenge for Ubiquitous healthcare systems that depend on data aggregated and collaborative deep learning among different parties. This paper proposes MSCryptoNet, novel framework enables scalable execution conversion state-of-the-art learned neural network to MSCryptoNet models privacy-preservation setting. We also design method approximation activation function basically used convolutional (i.e., Sigmoid Rectified linear unit) with low...

Medical practitioners generally rely on multimodal brain images, for example based the information from axial, coronal, and sagittal views, to inform tumor diagnosis. Hence, further utilize 3D embedded in such datasets, this paper proposes a multi-view dynamic fusion framework (hereafter, referred as MVFusFra) improve performance of segmentation. The proposed consists three key building blocks. First, deep neural network architecture, which represents multi learning networks segmenting...

According to research, classifiers and detectors are less accurate when images blurry, have low contrast, or other flaws which raise questions about the machine learning model’s ability recognize items effectively. The chest X-ray image has proven be preferred modality for medical imaging as it contains more information a patient. Its interpretation is quite difficult, nevertheless. goal of this research construct reliable deep-learning model capable producing high classification accuracy on...

Battiti's mutual information feature selector (MIFS) and its variant algorithms are used for many classification applications. Since they ignore synergy, MIFS variants may cause a big bias when features combined to cooperate together. Besides, estimate redundancy regardless of the corresponding task. In this paper, we propose an automated greedy selection algorithm called conditional information-based (CMIFS). Based on link between interaction information, CMIFS takes account both synergy...

Never before have data sharing been more convenient with the rapid development and wide adoption of cloud computing. However, how to ensure user’s security is becoming main obstacles that hinder computing from extensive adoption. Proxy re-encryption serves as a promising solution secure in It enables owner encrypt shared under its own public key, which further transformed by semitrusted server into an encryption intended for legitimate recipient access control. This paper gives solid...

We propose a novel classification framework to precisely identify individuals with Alzheimer’s disease (AD) or mild cognitive impairment (MCI) from normal controls (NC). The proposed method combines three different features structural MR images: gray-matter volume, gray-level cooccurrence matrix, and Gabor feature. These can obtain both the 2D 3D information of brains, experimental results show that better performance be achieved through multifeature fusion. also analyze multifeatures...

Public key encryption supporting equality test (referred to as PKE-ET) provides the capability of testing equivalence between two messages encrypted under different public keys. Ciphertext-policy attribute-based (CP-ABE) is a promising primitive achieve versatile and secure data sharing in cloud computing by providing flexible one-to-many encryption. In this paper, we first initialize concept CP-ABE with (CP-ABE-ET) combining notions PKE-ET CP-ABE. Using ABE-ET primitive, receiver can...

Smart homes expects to improve the convenience, comfort, and energy efficiency of residents by connecting controlling various appliances. As personal information computing hub for smart homes, smartphones allow people monitor control their anytime anywhere. Therefore, security privacy stored data are crucial in homes. To protect from potential attacks, built-in sensors can be utilized user authentication/identification access achieve enhanced security. In this paper, we propose a framework,...

Due to its nonintrusive character, WiFi channel state information (CSI)-based activity recognition has attracted tremendous attention in recent years. Since performance heavily relies on segmentation results, a number of methods have been designed, and most them focus seeking optimal thresholds segment activities. However, these threshold-based are strongly dependent designers' experience might suffer from decline when applying the scenario, including both fine-grained coarse-grained To...

The Internet of Health Things (IoHT) is a medical concept that describes uniquely identifiable devices connected to the can communicate with each other. As one most important components smart health monitoring and improvement systems, IoHT presents numerous challenges, among which cybersecurity priority. well-received security solution achieve fine-grained access control, ciphertext-policy weighted attribute-based encryption (CP-WABE) has potential ensure data in IoHT. However, many issues...

Introduction and Background: Despite fast developments in the medical field, histological diagnosis is still regarded as benchmark cancer diagnosis. However, input image feature extraction that used to determine severity of at various magnifications harrowing since manual procedures are biased, time consuming, labor intensive, error-prone. Current state-of-the-art deep learning approaches for breast histopathology classification take features from entire images (generic features). Thus, they...

Leveraging a wireless multipath channel as the source of common randomness, many key generation methods have been proposed according to information-theory security. However, existing schemes suffer low rate and entropy, mainly rely on nodes' mobility. To overcome this limitation, we present protocol with known artificial interference, named SmokeGrenade, new physical-layer approach for secret in narrowband fading channel. Our scheme utilizes interference contribute change measured values...

Fog computing dramatically extends the cloud to edge of network and admirably solves problem that brokers (in publish-subscribe system) generally lack capacity energy power. However, may be disguised, hacked, sniffed, corrupted. The traditional security technology cannot protect system privacy when facing a possible collusion attack. In this paper, we propose privacy-preserving content-based publish/subscribe scheme with differential in fog context, named PCP, where nodes act as brokers....