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Intrusion detection plays a critical role in security of people's possessions. Approaches such as video-based, infrared-based, RFID, UWB, etc. can provide satisfying detection accuracy. However, they all require specialized hardware deployment and strict using conditions which hinder their wide deployment. Beyond communication, WLANs can also act as generalized sensor networks and there are several...
With rapid growth of LTE network and Voice-over-LTE(VoLTE), detecting and preventing security threats like Denial of Service attack becomes a necessary and urgent requirement. VoLTE is an voice solution based on Internet Protocol and 4G LTE technology, at the same time exposing many vulnerabilities when using packet-switched network. There are many heavy weighted detection systems using content analysis,...
Twitter is attracting significant interests from the research community in the last few years. Sentiment analysis of tweets is among the hottest topics of research nowadays. State of the art approaches of sentiment analysis present many shortcomings when classifying tweets, in particular when the classification goes beyond the binary or ternary classification. Multi-class sentiment analysis has proven...
eHealth systems generate from the integration of information and communication technologies with traditional healthcare systems. They have widely replaced paper-based systems due to their prominent features of convenience and accuracy. However, eHealth systems also face many challenges, such as the privacy and security concerns over patients' identities and their personal health records (PHRs). Traditional...
In this paper, weighted fractional Fourier transform (WFRFT) is employed to safeguard the physical layer (PHY) security of wireless communications. By leveraging the features of WFRFT, we propose a PHY security modulation scheme, which significantly degrades the equivalent signal-to-noise ratio (SNR) of the unauthorized receiver while imposing no impact on the legitimate receiver. With the proposed...
The last decade has witnessed a dramatic growth of social networks, such as Twitter, Sina Microblog, etc. Messages/short texts on these platforms are generally of limited length, causing difficulties for machines to understand. Moreover, it is rarely possible for users to read and understand all the content due to the large quantity. So it is imperative to cluster and extract the viewpoints of these...
A critical task in forced oscillation technique (FOT), a promising lung function test, is to remove respiratory artefacts. Manual removal by specialists is widely used but time- consuming and subjective. Most existing automated techniques have involved simple thresholding methods in an unsupervised manner. Breath cycles can be classified by a binary classification model (classes: artefactual and accepted)...
The rate of data generation is enormously growing due to the number of internet users and its speed. This increases the possibility of intrusions causing serious financial damage. Detecting the intruders in such high-speed data networks is a challenging task. Therefore, in this paper, we present a high-speed Intrusion Detection System (IDS), capable of working in Big Data environment. The system design...
Many emerging Big Data applications involve real- time classification in which data instances arriving sequentially over time need to be classified based on their feature vectors. A common and implicit assumption in existing works is that the features become available instantly with the instance and simultaneously with each other, which, however, rarely holds in practice. Instead, features of an instance...
Ventricular tachyarrhythmia, in particular Ventricular Fibrillation (VF), is the primary arrhythmic event to cause Sudden Cardiac Death (SCD). Thus, the quick and accurate detection of a VF event is crucial for capturing the life-threat cardiac arrhythmias in real time. However, almost all existing VF detection algorithms are challenged by low accuracy or/and high complexity. To address this challenge,...
In this paper, a novel adequate and concise information extraction approach is explored to provide a promising alternative for manifesting the intrinsic structure of the cyclostationary signals, such as communication signals. A novel graph-based signal representation is proposed to interpret the spectral correlation function into a graph and its adjacency matrix. This graph can represent the proposed...
Context awareness plays an important role in many emerging applications, such as mobile computing and smart space. Since FM signal is ubiquitous, it has been recognized as an attractive and promising technique to realize context awareness. When a target is at different locations or performs different activities, it will exert different influence on the FM signal around it. Therefore, it is possible...
Blind signal search is a technique used in many different types of systems, ranging from cognitive radio to broadcasting applications such as television and radio. A well-known approach used for this, is the Cyclostationary Feature Detection algorithm, which can estimate the baud rate of a detected signal, but is not capable of identifying its position in the spectrum, nor properly analyse spans with...
Abstract-We propose a novel RF signal classification method based on sparse coding, an unsupervised learning method popular in computer vision. In particular, we employ a convolutional sparse coder that can extract high-level features of an unknown received signal by maximal similarity matching against an overcomplete dictionary of filter patterns. Such dictionary can be either generated or learned...
The rapid advances in wireless communication and sensor technologies facilitate the development of viable mobile-Health applications that boost opportunity for ubiquitous real- time healthcare monitoring without constraining patients' activities. However, remote healthcare monitoring requires continuous sensing for different analog signals which results in generating large volumes of data that needs...
Analysing the power usage of an Internet of Things (IoT) device is essential in contexts such as smart building, testbed and forensics. For example, in the smart building case, schemes have been proposed to detect and analyse the activity of electric appliances based on the total power usage. In this work, we intend to take this concept a step further and devise a method to analyse the activity of...
Abstract-Human identification plays an important role in human-computer interaction. There have been numerous methods proposed for human identification (e.g., face recognition, gait recognition, fingerprint identification, etc.). While these methods could be very useful under different conditions, they also suffer from certain shortcomings (e.g., user privacy, sensing coverage range). In this paper,...
Malware authors or attackers always try to evade detection methods to accomplish their mission. Such detection methods are broadly divided into three types: static feature, host-behavior, and network-behavior based. Static feature-based methods are evaded using packing techniques. Host- behavior-based methods also can be evaded using some code injection methods, such as API hook and dynamic link library...
Shopping of the same or similar types of products as shown in the online TV programs has been highly desired by many people, especially the youth. To meet this eminent market need, we develop a prototype system to enable effortless TV-to-Online (T2O) experience. A key component of this system is the product search that maps specific items embedded in the video into a list of online merchants. The...
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