E-commerce system has become more popular and implemented in almost all business areas. is a platform for marketing promoting the products to customer through online. Customer segmentation known as process of dividing customers into groups which shares similar characteristics. The purpose determine how deal with each category order increase profit business. Segmenting assist identify their profitable satisfy needs by optimizing services products. Therefore, helps promote right product...

Owing to the prevalence of Internet things (IoT) devices connected Internet, number IoT-based attacks has been growing yearly. The existing solutions may not effectively mitigate IoT attacks. In particular, advanced network-based attack detection using traditional Intrusion systems are challenging when network environment supports as well protocols and uses a centralized architecture such software defined (SDN). this paper, we propose long short-term memory (LSTM) based approach detect SDN...

The Internet of Things (IoT) has rapidly progressed in recent years and immensely influenced many industries how they operate. Consequently, IoT technology improved productivity sectors, smart farming also hugely benefited from the IoT. Smart enables precision agriculture, high crop yield, efficient utilization natural resources to sustain for a longer time. includes sensing capabilities, communication technologies transmit collected data sensors, analytics extract meaningful information...

Blockchain technology is one of the most important inventions and creative advancements that play a crucial role in today's business world. heading direction systematic innovation revolution. It digital ledger transactions, every block contains information transactions linked by cryptographic references. Every covers maintains trust among people based on how far they are. system used for storing data, it ensures security system. The resurgence blockchain has encouraged scholars specialists...

Cybercriminals use domain generation algorithms (DGAs) to prevent their servers from being potentially blacklisted or shut down. Existing reverse engineering techniques for DGA detection is labor intensive, extremely time-consuming, prone human errors, and have significant limitations. Hence, an automated real-time technique with a high rate warranted in such applications. In this article, we present novel detect randomly generated names name system (DNS) homograph attacks without the need...

Integrating the internet of things (IoT) in medical applications has significantly improved healthcare operations and patient treatment activities. Real-time monitoring remote diagnostics allow physician to serve more patients save human lives using (IoMT) technology. However, IoMT devices are prone cyber attacks, security privacy have been a concern. The operate on low computing memory, implementing technology is not feasible. In this article, we propose particle swarm optimization deep...

This article presents an analysis of data extraction for classification using correlation coefficient and fuzzy model. Several traditional methods are used that could not provide sufficient information further step on class. It needs refinement features to distinguish a class differs from Thus, it proposes the feature tiny (subfeature data) find two such as model select well subfeature distinguishing In first approach, with gradient descent technique dataset in second supreme minimum value...

Lung diseases are a tremendous challenge to the health and life of people globally, accounting for 5 out 30 most common causes death. Early diagnosis is crucial help in faster recovery improve long-term survival rates. Deep learning techniques offer great promise automated, fast, reliable detection lung from medical images. Specifically, convolutional neural networks have accomplished encouraging results disease detection. In spite that, performance such supervised models depends heavily on...

Recently computer-aided diagnosis methods have been widely adopted to aid doctors in disease making their decisions more reliable and error-free. Electrocardiogram (ECG) is the most commonly used, noninvasive diagnostic tool for investigating various cardiovascular diseases. In real life, patients suffer from than one heart at a time. So any practical automated system should identify multiple diseases present single ECG signal. this article, we propose novel deep learning-based method...

Abstract Internet usage became increasingly ubiquitous. The concern regarding security and privacy has become essential for users. As the of increases number cyber‐attacks also substantially. Intrusion detection is one challenging aspects network security. Efficient intrusion crucial every organization to mitigate vulnerability. This paper presents a novel system detect malicious attacks targeted at smart environment. proposed method uses correlation tool random forest predominant...

Abstract With the popularity of internet and smartphones, malware on smartphones has increased dramatically. In addition, ubiquity openness Android operating system have made it a lucrative platform for cybercriminals to develop malware. Traditional detection techniques require lot time manual effort classify accurately. Recently, deep learning (DL) based classification been developed solve this issue. This article proposes DL‐based two‐stage framework that detects classifies its variants...

A literature survey shows that the number of malware attacks is gradually growing over years due to trend Internet Medical Things (IoMT) devices. To detect and classify attacks, automated detection classification an essential subsystem in healthcare cyber-physical systems. This work proposes attention-based multidimensional deep learning (DL) approach for a cross-architecture IoMT system based on byte sequences extracted from Executable Linkable Format (ELF; formerly named Extensible Linking...

One of the top causes mortality in people globally is a brain tumor. Today, biopsy regarded as cornerstone cancer diagnosis. However, it faces difficulties, including low sensitivity, hazards during treatment, and protracted waiting period for findings. In this context, developing non-invasive computational methods identifying treating cancers crucial. The classification tumors obtained from an MRI crucial making variety medical diagnoses. analysis typically requires much time. primary...

This article presents a deep learning-based approach for network-based intrusion detection in the Internet of medical things (IoMT) systems using features network flows and patient biometrics. The proposed effectively learns optimal feature representation by passing information biometrics into more than one hidden layer learning. includes global attention which helps to extract from spatial temporal To avoid data imbalance, cost-sensitive learning is integrated model. model showed 10-fold...