Intrusion detection and prevention system for an IoT environment

Internet of Things (IoT) security is the act of securing IoT devices and networks. IoT devices, including industrial machines, smart energy grids, and building automation, are extremely vulnerable. With the goal of shielding network systems from illegal access in cloud servers and IoT systems, Intrusion Detection Systems (IDSs) and Network-based Intrusion Prevention Systems (NBIPSs) are proposed in this study. An intrusion prevention system is proposed to realize NBIPS to safeguard top to bottom engineering. The proposed NBIPS inspects network activity streams to identify and counteract misuse instances. The NBIPS is usually located specifically behind a firewall, and it provides a reciprocal layer of investigation that adversely chooses unsafe substances. Network-based IPS sensors can be installed either in an inline or a passive model. An inline sensor is installed to monitor the traffic passing through it. The sensors are installed to stop attacks by blocking the traffic using an IoT signature-based protocol.     

EMA-PRBDS: efficient multi-attribute packet rank based data scheduling in wireless sensor networks for real-time monitoring systems

ABSTRACT

In recent years, Wireless Sensor Networks (WSNs) are widely placed in real-time monitoring systems like environmental, structural, patient monitoring, etc. The major criterion for WSN includes energy efficiency and network lifetime. Scheduling is used as a large number of data packets focus on the same queue at the same time. Only limited data scheduling schemes have been implemented in WSN to enhance the performance. The existing First Come First Serve (FCFS) and Dynamic Multilevel Priority (DMP) have some technical challenges like delay, packet drop and high energy consumption due to starvation and deadlock. In this paper, we proposed a new algorithm to optimise and rank the incoming data packets based on multi-attributes decision-making methodology named as Packet Rank Based Data Scheduling (PRBDS), the algorithm selects packet priority, deadline, and size as the metrics to rank the incoming data packets. A simulation result shows when compared with existing scheduling, PRBDS not only provides less energy consumption, also significantly reduces the packet drop and increases the lifetime. Thus, the proposed algorithm is most suitable for real-time monitoring system since it combines data ranking method with scheduling algorithm to create accurate and reliable results to evaluate the incoming data packets.     

G-band (140-220-GHz) InP-based HBT amplifiers

We report tuned amplifiers designed for the 140-220-GHz frequency band. The amplifiers were designed in a transferred-substrate InP-based heterojunction bipolar transistor technology that enables efficient scaling of the parasitic collector-base junction capacitance. A single-stage amplifier exhibited 6.3-dB small-signal gain at 175 GHz. Three-stage amplifiers were subsequently fabricated with one design demonstrating 12.0-dB gain at 170 GHz and a second design exhibiting 8.5-dB gain at 195 GHz.     

Curvelet-based fingerprint anti-spoofing

Existing perspiration-based liveness detection algorithms need two successive images (captured in certain time interval), hence they are slow and not useful for real-time applications. Liveness detection methods using extra hardware increase the cost of the system. To alleviate these problems, we propose new curvelet-based method which needs only one fingerprint to detect liveness. Wavelets are very effective in representing objects with isolated point singularities, but fail to represent line and curve singularities. Curvelet transform allows representing singularities along curves in a more efficient way than the wavelets. Ridges oriented in different directions in a fingerprint image are curved; hence curvelets are very significant to characterize fingerprint texture. Textural measures based on curvelet energy and co-occurrence signatures are used to characterize fingerprint image. Dimensionalities of feature sets are reduced by running Pudil’s sequential forward floating selection (SFFS) algorithm. Curvelet energy and co-occurrence signatures are independently tested on three different classifiers: AdaBoost.M1, support vector machine and alternating decision tree. Finally, all the aforementioned classifiers are fused using the “Majority Voting Rule” to form an ensemble classifier. A fingerprint database consisting of 185 real, 90 Fun-Doh and 150 Gummy fingerprints is created by using varieties of artificial materials for casts and moulds of spoof fingerprints. Performance of the new liveness detection approach is found very promising, as it needs only one fingerprint and no extra hardware to detect vitality.     

Molecularly‐Engineered, 4D‐Printed Liquid Crystal Elastomer Actuators

Three‐dimensional structures that undergo reversible shape changes in response to mild stimuli enable a wide range of smart devices, such as soft robots or implantable medical devices. Herein, a dual thiol‐ene reaction scheme is used to synthesize a class of liquid crystal (LC) elastomers that can be 3D printed into complex shapes and subsequently undergo controlled shape change. Through controlling the phase transition temperature of polymerizable LC inks, morphing 3D structures with tunable actuation temperature (28 ± 2 to 105 ± 1 °C) are fabricated. Finally, multiple LC inks are 3D printed into single structures to allow for the production of untethered, thermo‐responsive structures that sequentially and reversibly undergo multiple shape changes.     

Metal gate-HfO/sub 2/ MOS structures on GaAs substrate with and without Si interlayer

In this letter, we studied the effects of post-deposition anneal (PDA) time and Si interface control layer (ICL) on the electrical characteristics of the MOS capacitor with high-/spl kappa/ (HfO/sub 2/) material on GaAs. Thin equivalent oxide thickness (EOT<3 nm) with excellent capacitance-voltage (C-V) characteristics has been obtained. The thickness of the Si ICL and PDA time were correlated with C-V characteristics. It was found that high temperature Si ICL deposition and longer PDA time at 600/spl deg/C improved the C-V shape, leakage current, and especially frequency dispersion (<5%).     

Special Issue: Technological Advancements in Wireless and Optical Communication Systems

Wireless Personal Communications -     

LMS adaptive filters using distributed arithmetic for high throughput

We present a new hardware adaptive filter architecture for very high throughput LMS adaptive filters using distributed arithmetic (DA). DA uses bit-serial operations and look-up tables (LUTs) to implement high throughput filters that use only about one cycle per bit of resolution regardless of filter length. However, building adaptive DA filters requires recalculating the LUTs for each adaptation which can negate any performance advantages of DA filtering. By using an auxiliary LUT with special addressing, the efficiency and throughput of DA adaptive filters can be of the same order as fixed DA filters. In this paper, we discuss a new hardware adaptive filter structure for very high throughput LMS adaptive filters. We describe the development of DA adaptive filters and show that practical implementations of DA adaptive filters have very high throughput relative to multiply and accumulate architectures. We also show that DA adaptive filters have a potential area and power consumption advantage over digital signal processing microprocessor architectures.     

Sound event detection in real-life audio using joint spectral and temporal features

Typical methods for overlapping sound event detection (SED) do not fully consider the joint spectral and temporal transition characteristics of the audio signal. They are generally based on training models using either separate data from each event class or mixed signals containing simultaneous sound events. This paper introduced a new approach for SED in real-life audio using Nonnegative Matrix Factor 2-D Deconvolution and RUSBoost techniques. The idea is to capture the two-dimensional joint spectral and temporal information from the time-frequency representation while possibly separating the sound mixture into several sources. In addition, the RUSBoost technique is utilized to address the class imbalance problem of the training data. The proposed approach is evaluated using the TUT Sound Event 2016 and 2017 datasets. The results showed that the proposed method outperformed the baseline methods. For the TUT Sound Event 2016 dataset, the proposed method reduced the total error rate by 5% while increasing the F1 score by 13.8%. For the TUT Sound Event 2017 dataset, the proposed method reduced the total error rate by 3% while increasing the F1 score by 8.1%.     

Noninvasive measurement of compliance of human leg arteries

Electrical impedance plethysmography has been evaluated for early detection of peripheral atherosclerosis. A pressure cuff was wrapped around the lower leg and the cuff pressure increased. Two circumferential electrodes glued in the middle of the cuff recorded the impedance pulse, from which the arterial pulse volume was calculated. The ratio of maximal arterial volume change to the pulse pressure was determined as a measure of maximal compliance Cp. Based on the data from 118 human subjects, Cp was found to correlate well with known cardiovascular risk factors. For example, Cp decreased on the average from 3.08 to 1.92 microL.mm Hg-1.cm-1 (1 microL.mm Hg-1.cm-1 = 7.5 x 10(-10) m4.N-1) in groups of subjects of increasing age from 22 to 70 years. Subjects on a regular exercise program had an average value of 3.86, while those with proven peripheral vascular disease had a value of 0.70. In a related pathologic validation study on 15 monkeys fed a cholesterol-control diet a good correlation was found between the limb peak compliance and morphometric data obtained from iliac and carotid arteries.