IoT security: Review, blockchain solutions, and open challenges

Digital processing of speech signals

A brain-computer interface (BCI) is a hardware and software communications system that permits cerebral activity alone to control computers or external devices. The immediate goal of BCI research is to provide communications capabilities to severely disabled people who are totally paralyzed or 'locked in' by neurological neuromuscular disorders, such as amyotrophic lateral sclerosis, brain stem stroke, or spinal cord injury. Here, we review the state-of-the-art of BCIs, looking at the different steps that form a standard BCI: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and the control interface. We discuss their advantages, drawbacks, and latest advances, and we survey the numerous technologies reported in the scientific literature to design each step of a BCI. First, the review examines the neuroimaging modalities used in the signal acquisition step, each of which monitors a different functional brain activity such as electrical, magnetic or metabolic activity. Second, the review discusses different electrophysiological control signals that determine user intentions, which can be detected in brain activity. Third, the review includes some techniques used in the signal enhancement step to deal with the artifacts in the control signals and improve the performance. Fourth, the review studies some mathematic algorithms used in the feature extraction and classification steps which translate the information in the control signals into commands that operate a computer or other device. Finally, the review provides an overview of various BCI applications that control a range of devices.

/pdf/brain-computer-interfaces-a-review-2z42gnpdfy.pdf

Brain Computer Interfaces, a Review

The present invention involves method and apparatus for analyzing two measured signals that are modeled as containing primary and secondary portions. Coefficients relate the two signals according to a model defined in accordance with the present invention. In one embodiment, the present invention involves utilizing a transformation which evaluates a plurality of possible signal coefficients in order to find appropriate coefficients. Alternatively, the present invention involves using statistical functions or Fourier transform and windowing techniques to determine the coefficients relating to two measured signals. Use of this invention is described in particular detail with respect to blood oximetry measurements.

Signal processing apparatus.

The Internet of Things (IoT) introduces a vision of a future Internet where users, computing systems, and everyday objects possessing sensing and actuating capabilities cooperate with unprecedented convenience and economical benefits. As with the current Internet architecture, IP-based communication protocols will play a key role in enabling the ubiquitous connectivity of devices in the context of IoT applications. Such communication technologies are being developed in line with the constraints of the sensing platforms likely to be employed by IoT applications, forming a communications stack able to provide the required power—efficiency, reliability, and Internet connectivity. As security will be a fundamental enabling factor of most IoT applications, mechanisms must also be designed to protect communications enabled by such technologies. This survey analyzes existing protocols and mechanisms to secure communications in the IoT, as well as open research issues. We analyze how existing approaches ensure fundamental security requirements and protect communications on the IoT, together with the open challenges and strategies for future research work in the area. This is, as far as our knowledge goes, the first survey with such goals.

Security for the Internet of Things: A Survey of Existing Protocols and Open Research Issues

In this paper, we investigate applications of access control to Wireless Sensor Networks (WSNs). Although access control was well established for traditional computer systems, it has not been studied thoroughly in WSN environments. We briefly provide the WSN specifications and then stress the constraints of the WSNs that would affect the access control implementation. We also provide a literature overview and discuss further possible solutions.

A brief survey of access control in Wireless Sensor Networks

This paper investigates the predictability of VBR video traffic which exhibits long-range dependence (LRD) based on the fractional ARIMA (1,d,0) model. We consider a novel predictor based dynamic bandwidth allocation for the short term resource management and study its queueing performance. This method is simple to implement and is demonstrated to provide superior performance over some existing methods. The performance results are presented.

An approach towards resource management and transportation of VBR video traffic

Wireless Sensor Networks (WSNs) continue to grow as one of the most exciting and challenging research areas of engineering. They are characterized by severely constrained computational and energy resources and also restricted by the ad-hoc network operational environment. They pose unique challenges, due to limited power supplies, low transmission bandwidth, small memory sizes and limited energy. Therefore, security techniques used in traditional networks cannot be directly adopted. So, new ideas and approaches are needed, in order to increase the overall security of the network. Security applications in such resource constrained WSNs with minimum overhead provides significant challenges, and is the main focus of this dissertation. 
In general, the following processes may be involved in securing WSNs: Intrusion Prevention, Intrusion Detection, and Intrusion Mitigation. This dissertation presents solutions (algorithms and schemes) to the first two lines of defenses of the security provisioning plan, namely, Intrusion Prevention and Intrusion Detection. 
As a first line of defense in securing WSNs, this dissertation presents our proposed algorithm ("Two-Level User Authentication" scheme) as an Intrusion Prevention System (IPS) for WSNs. The algorithm uses two-level authentication between a sensor node and a user. It is designed for heterogeneous WSNs, meaning that the network consists of two components: regular nodes and more powerful cluster heads. The proposed scheme is evaluated both analytically and also in a simulation environment, by comparing it to the current state-of-the-art schemes in the literature. 
A comprehensive and systematic survey of the state-of-the-art in Intrusion Detection Systems (IDSs) that are proposed for Mobile Ad-Hoc Networks (MANETs) and WSNs is presented. Firstly, detailed information about IDSs is provided. This is followed by the analysis and comparison of each scheme along with their advantages and disadvantages from the perspective of security. Finally, guidelines on IDSs that are potentially applicable to WSNs are provided. Overall, this work would be very helpful to the researchers in developing their own IDSs for their WSNs. 
Clustering (of the nodes) is very important for WSNs not only in data aggregation, but also in increasing the overall performance of the network, especially in terms of total life-time. Besides, with the help of clustering, complex intrusion prevention and detection algorithms can be implemented. Therefore, background on the clustering algorithms is provided and then a clustering algorithm for WSNs is proposed, that is both power and connectivity aware. The proposed algorithm provides higher energy efficiency and increases the life-time of the network. In evaluating the proposed clustering algorithm (in a simulation environment by comparing its' performance to the previously proposed algorithm, namely Kachirski et al.'s algorithm), it is demonstrated that the proposed algorithm improves energy efficiency in WSNs. 
Finally, an IDS framework based on multi-level clustering for hierarchical WSNs is proposed. It is based upon (the nodes use our proposed clustering algorithm while forming their clusters) the clustering algorithm that is proposed in this dissertation. The framework provides two types of intrusion detection approaches, namely "Downwards-IDS (D-IDS)" to detect the abnormal behavior (intrusion) of the subordinate (member) nodes and "Upwards-IDS (U-IDS)" to detect the abnormal behavior of the cluster heads. By using analytical calculations, the optimum parameters for the D-IDS (number of maximum hops) and U-IDS (monitoring group size) of the framework are evaluated and presented. (Abstract shortened by UMI.)

/pdf/prevention-and-detection-of-intrusions-in-wireless-sensor-4o4mw3cs70.pdf

Prevention and detection of intrusions in wireless sensor networks

A Brain Computer Interface (BCI) is a device that allows the user to communicate with the world without utilizing voluntary muscle activity (i.e., using only the electrical activity of the brain). It makes use of the well-studied observation that the brain reacts differently to different stimuli, as a function of the level of attention allotted to the stimulus stream and the specific processing triggered by the stimulus. In this article we present a single trial independent component analysis (ICA) method that is working with a BCI system proposed by Farwell and Donchin. It can dramatically reduce the signal processing time and improve the data communicating rate. This ICA method achieved 76.67% accuracy on single trial P300 response identification.

P300 Based Single Trial Independent Component Analysis on EEG Signal

Arterial oxyhemoglobin saturation (SpO/sub 2/) values are currently computed using weighted moving average techniques. Digital signal processing algorithms were explored to identify improved algorithms for SpO/sub 2/ computation. The fast Fourier transform and discrete cosine transform were identified as potentially superior algorithms. Improvements to the original algorithm using combinations of overlapped processing and averaging techniques were also explored. >

Ravi Sankar

Papers

A brief survey of access control in Wireless Sensor Networks

An approach towards resource management and transportation of VBR video traffic

Prevention and detection of intrusions in wireless sensor networks

P300 Based Single Trial Independent Component Analysis on EEG Signal

Alternate pulse oximetry algorithms for SpO/sub 2/ computation