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Efficient video coding using visual sensitive information for HEVC coding standard

- Podder, Pallab, Paul, Manoranjan, Murshed, Manzur

  • Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
  • Date: 2018
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 6, no. (2018), p. 75695-75708
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  • Description: The latest high efficiency video coding (HEVC) standard introduces a large number of inter-mode block partitioning modes. The HEVC reference test model (HM) uses partially exhaustive tree-structured mode selection, which still explores a large number of prediction unit (PU) modes for a coding unit (CU). This impacts on encoding time rise which deprives a number of electronic devices having limited processing resources to use various features of HEVC. By analyzing the homogeneity, residual, and different statistical correlation among modes, many researchers speed-up the encoding process through the number of PU mode reduction. However, these approaches could not demonstrate the similar rate-distortion (RD) performance with the HM due to their dependency on existing Lagrangian cost function (LCF) within the HEVC framework. In this paper, to avoid the complete dependency on LCF in the initial phase, we exploit visual sensitive foreground motion and spatial salient metric (FMSSM) in a block. To capture its motion and saliency features, we use the dynamic background and visual saliency modeling, respectively. According to the FMSSM values, a subset of PU modes is then explored for encoding the CU. This preprocessing phase is independent from the existing LCF. As the proposed coding technique further reduces the number of PU modes using two simple criteria (i.e., motion and saliency), it outperforms the HM in terms of encoding time reduction. As it also encodes the uncovered and static background areas using the dynamic background frame as a substituted reference frame, it does not sacrifice quality. Tested results reveal that the proposed method achieves 32% average encoding time reduction of the HM without any quality loss for a wide range of videos.

Fast intermode selection for HEVC video coding using phase correlation

- Podder, Pallab, Paul, Manoranjan, Murshed, Manzur, Chakraborty, Subrata

  • Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur , Chakraborty, Subrata
  • Date: 2015
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 2014 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2014; Wollongong, Australia; 25th-27th November 2014 p. 1-8
  • Relation: http://purl.org/au-research/grants/arc/DP130103670
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  • Description: The recent High Efficiency Video Coding (HEVC) Standard demonstrates higher rate-distortion (RD) performance compared to its predecessor H.264/AVC using different new tools especially larger and asymmetric inter-mode variable size motion estimation and compensation. This requires more than 4 times computational time compared to H.264/AVC. As a result it has always been a big concern for the researchers to reduce the amount of time while maintaining the standard quality of the video. The reduction of computational time by smart selection of the appropriate modes in HEVC is our motivation. To accomplish this task in this paper, we use phase correlation to approximate the motion information between current and reference blocks by comparing with a number of different binary pattern templates and then select a subset of motion estimation modes without exhaustively exploring all possible modes. The experimental results exhibit that the proposed HEVC-PC (HEVC with Phase Correlation) scheme outperforms the standard HEVC scheme in terms of computational time while preserving-the same quality of the video sequences. More specifically, around 40% encoding time is reduced compared to the exhaustive mode selection in HEVC. © 2014 IEEE.
  • Description: 2014 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2014

Forecasting plug-in electric vehicles load profile using artificial neural networks

- Panahi, Delshad, Deilami, Sara, Masoum, Mohammad, Islam, Syed

  • Authors: Panahi, Delshad , Deilami, Sara , Masoum, Mohammad , Islam, Syed
  • Date: 2015
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 25th Australasian Universities Power Engineering Conference, AUPEC 2015; Wollongong, Australia; 27th-30th September 2015 p. 1-6
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  • Description: Plug-in electric vehicles (PEVs) are becoming very popular these days and consequently, their load management will be a challenging issue for the network operators in the future. This paper proposes an artificial intelligence approach based on neural networks to forecast daily load profile of individual and fleets of randomly plugged-in PEVs, as well as the upstream distribution transformer loading. An artificial neural network (ANN) model will be developed to forecast daily arrival time (Ta) and daily travel distance (Dtr) of individual PEV using historical data collected for each vehicle in the past two years. The predicted parameters are then will be used to forecast transformer loading with PEV charging activities. The results of this paper will be very beneficial to coordination and charge/discharge management of PEVs as well as demand load management, network planning and operation proposes. Detailed simulations are presented to investigate the feasibility and accuracy of the proposed forecasting strategy.

A novel quality metric using spatiotemporal correlational data of human eye maneuver

- Podder, Pallab, Paul, Manoranjan, Murshed, Manzur

  • Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
  • Date: 2017
  • Type: Text , Conference proceedings
  • Relation: 2017 International Conference on Digital Image Computing : Techniques and Applications, DICTA 2017; Sydney, Australia; 29th November-1st December 2017 Vol. 2017-December, p. 1-8
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  • Description: The popularly used subjective estimator- mean opinion score (MOS) is often biased by the testing environment, viewers mode, domain expertise, and many other factors that may actively influence on actual assessment. We therefore, devise a no- reference subjective quality assessment metric by exploiting the nature of human eye browsing on videos. The participants' eye-tracker recorded gaze-data indicate more concentrated eye- traversing approach for relatively better quality. We calculate the Length, Angle, Pupil-size, and Gaze-duration features from the recorded gaze trajectory. The content and resolution invariant operation is carried out prior to synthesizing them using an adaptive weighted function to develop a new quality metric using eye traversal (QMET). Tested results reveal that the quality evaluation carried out by QMET demonstrates a strong correlation with the most widely used peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and the MOS.
  • Description: DICTA 2017 - 2017 International Conference on Digital Image Computing: Techniques and Applications

Maximising competitive advantage on e-Business websites : A data mining approach

- Alazab, Ammar, Bevinakoppa, Savitri, Khraisat, Ansam

  • Authors: Alazab, Ammar , Bevinakoppa, Savitri , Khraisat, Ansam
  • Date: 2018
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 2018 IEEE Conference on Big Data and Analytics, ICBDA 2018; Langkawi, Malaysia; 21st-22nd November 2018 p. 111-116
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  • Description: Many organizations are interested in analyzing and evaluating the web data for their websites because websites are a very important platform to carry out their business. However, website evaluations face many challenges in using analytics, especially with the huge amount of data that the websites are collecting from various sources. This explosive growth in data requires a complex tool for analyzing and automatically convert the data into valuable information. However, without using a proper analysis tool, it is very difficult to understand the user's behaviour, user's interaction patterns on the website and how users involve in the site. This paper explains methods to examine, understand and visualize the huge amounts of stored data collected from the websites. In this paper, a framework is developed for identifying user's behaviours on websites. Firstly, the attributes are extracted from different websites using Google Analytics and other API tools. Secondly, data mining techniques such as clustering, classification and information gain are applied to build this framework. The findings of these study can be used to evaluate the website and provide some guidelines for the web team to increase user engagement on the website and understand the influence of user behaviour. In addition, this framework is able to identify which behaviour features influence user decisions. Our proposed framework for identifying user's behaviours on websites is tested on a large dataset that contains a variety of individual users from different websites. © 2018 IEEE.

Performance analysis of filter sensing board for measuring the battery online impedance

- Hossain, Kamal, Islam, Syed, Park, Sung-Yeul

  • Authors: Hossain, Kamal , Islam, Syed , Park, Sung-Yeul
  • Date: 2016
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 2016 Asian Conference on Energy, Power and Transportation Electrification, ACEPT 2016; Singapore, Singapore; 25th-27th October 2016 Vol. 2017, p. 1-6
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  • Description: This paper presents the performance analysis of filter sensing board for extracting ac ripple information to estimate the battery impedance for the sinusoidal ripple current charging technique. The charging ac ripple content is extracted from the battery voltage and current by filtering the dc component using an op-amp filter circuit while producing a 90° phase angle in order to transform the a-p frame for calculating the battery impedance. The digital signal processor based board has computational burden due to the many transformations and calculation steps with limited ADC sensing range between 0 to 3 V at 12 bit resolution. Additionally, in the software approach it is observed that the gain and phase angle of sensor output is changing with respect to the AC input ripple frequency. In this paper, we propose a filter sensing circuit board to reduce the transformation and computation burdens for measuring the AC impedance. In this proposed method, the impedance is calculated via a dSPACE interface with a ± 10 V ADC sensing range at 16 bit resolution. This paper also verifies the variation of phase delay between the sensor input and output at different frequencies by using the proposed 16-channel analog filter circuit. A prototype ac load is used as an experimental test bed considering the equivalent battery internal impedance model for measuring the accuracy of the filter sensing board. Finally, the performance of this proposed approach is verified by comparing the experimental result with the simulation and the commercial frequency response analyzer results.

Security hardening of implantable cardioverter defibrillators

- Jaffar, Iram, Usman, Muhammad, Jolfaei, Alireza

  • Authors: Jaffar, Iram , Usman, Muhammad , Jolfaei, Alireza
  • Date: 2019
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 2019 IEEE International Conference on Industrial Technology, ICIT 2019; Melbourne, Australia; 13th-15th February 2019 Vol. 2019-February, p. 1173-1178
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  • Description: Contemporary healthcare has witnessed a wide deployment of Implantable Cardioverter Defibrillators (ICDs), which have the capability to be controlled remotely, making them equally accessible from both home and hospitals. The therapeutic benefits of ICDs seem to outweigh potential security concerns, yet overlooking the presence of malicious attacks cannot be justified. This study investigates the scenario where an adversary falsifies a controller command and sends instructions to issue high electric shocks in succession. We propose a novel security hardening mechanism to protect data communications between ICD and controller from malicious data manipulations. Our proposed method verifies the correctness of an external command with respect to the history of heart rhythms. The proposed method is evaluated using real data. Multi-aspect analyses show the effectiveness of the proposed scheme.
  • Description: Proceedings of the IEEE International Conference on Industrial Technology

Keyword search for building service-based systems

- He, Qiang, Zhou, Rui, Zhang, Xuyun, Wang, Yanchun, Ye, Dayong, Chen, Feifei, Grundy, John, Yang, Yun

  • Authors: He, Qiang , Zhou, Rui , Zhang, Xuyun , Wang, Yanchun , Ye, Dayong , Chen, Feifei , Grundy, John , Yang, Yun
  • Date: 2017
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Software Engineering Vol. 43, no. 7 (2017), p. 658-674
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  • Description: With the fast growth of applications of service-oriented architecture (SOA) in software engineering, there has been a rapid increase in demand for building service-based systems (SBSs) by composing existing Web services. Finding appropriate component services to compose is a key step in the SBS engineering process. Existing approaches require that system engineers have detailed knowledge of SOA techniques which is often too demanding. To address this issue, we propose Keyword Search for Service-based Systems (KS3), a novel approach that integrates and automates the system planning, service discovery and service selection operations for building SBSs based on keyword search. KS3 assists system engineers without detailed knowledge of SOA techniques in searching for component services to build SBSs by typing a few keywords that represent the tasks of the SBSs with quality constraints and optimisation goals for system quality, e.g., reliability, throughput and cost. KS3 offers a new paradigm for SBS engineering that can significantly save the time and effort during the system engineering process. We conducted large-scale experiments using two real-world Web service datasets to demonstrate the practicality, effectiveness and efficiency of KS3. © 1976-2012 IEEE.

Vulnerability modelling for hybrid IT systems

- Ur-Rehman, Attiq, Gondal, Iqbal, Kamruzzuman, Joarder, Jolfaei, Alireza

  • Authors: Ur-Rehman, Attiq , Gondal, Iqbal , Kamruzzuman, Joarder , Jolfaei, Alireza
  • Date: 2019
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 2019 IEEE International Conference on Industrial Technology, ICIT 2019; Melbourne, Australia; 13th-15th February 2019 Vol. 2019-February, p. 1186-1191
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  • Description: Common vulnerability scoring system (CVSS) is an industry standard that can assess the vulnerability of nodes in traditional computer systems. The metrics computed by CVSS would determine critical nodes and attack paths. However, traditional IT security models would not fit IoT embedded networks due to distinct nature and unique characteristics of IoT systems. This paper analyses the application of CVSS for IoT embedded systems and proposes an improved vulnerability scoring system based on CVSS v3 framework. The proposed framework, named CVSSIoT, is applied to a realistic IT supply chain system and the results are compared with the actual vulnerabilities from the national vulnerability database. The comparison result validates the proposed model. CVSSIoT is not only effective, simple and capable of vulnerability evaluation for traditional IT system, but also exploits unique characteristics of IoT devices.
  • Description: Proceedings of the IEEE International Conference on Industrial Technology

New state observer gain tuning methodology based on the stable margin theory

- Ogawa, Kenji, Ohnishi, Kouhei, Ibrahim, Yousef

  • Authors: Ogawa, Kenji , Ohnishi, Kouhei , Ibrahim, Yousef
  • Date: 2017
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 2017 IEEE International Conference on Industrial Technology, ICIT 2017; Toronto, Canada; 23rd-25th March 2017 p. 677-682
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  • Description: This paper proposes a new observer gain tuning methodology to achieve a robust position control. The state observer is often used to estimate the state of the system. Generally, the observer gain is tuned by an evaluation function and the operator needs to arbitrarily select a weight function to obtain an optimal observer gain. This paper introduces a methodology for observer gain tuning using the stability margin theory. In addition, the state observer is combined with the Disturbance Observer (DOB) to achieve a robust position control. The validity of the proposed methodology was tested and confirmed by simulations and experimental study. © 2017 IEEE.
  • Description: Proceedings of the IEEE International Conference on Industrial Technology

A 3D object encryption scheme which maintains dimensional and spatial stability

- Jolfaei, Alireza, Wu, Xinwen, Muthukkumarasamy, Vallipuram

  • Authors: Jolfaei, Alireza , Wu, Xinwen , Muthukkumarasamy, Vallipuram
  • Date: 2015
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Information Forensics and Security Vol. 10, no. 2 (2015), p. 409-422
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  • Description: Due to widespread applications of 3D vision technology, the research into 3D object protection is primarily important. To maintain confidentiality, encryption of 3D objects is essential. However, the requirements and limitations imposed by 3D objects indicate the impropriety of conventional cryptosystems for 3D object encryption. This suggests the necessity of designing new ciphers. In addition, the study of prior works indicates that the majority of problems encountered with encrypting 3D objects are about point cloud protection, dimensional and spatial stability, and robustness against surface reconstruction attacks. To address these problems, this paper proposes a 3D object encryption scheme, based on a series of random permutations and rotations, which deform the geometry of the point cloud. Since the inverse of a permutation and a rotation matrix is its transpose, the decryption implementation is very efficient. Our statistical analyses show that within the cipher point cloud, points are randomly distributed. Furthermore, the proposed cipher leaks no information regarding the geometric structure of the plain point cloud, and is also highly sensitive to the changes of the plaintext and secret key. The theoretical and experimental analyses demonstrate the security, effectiveness, and robustness of the proposed cipher against surface reconstruction attacks.

Modelling and analysis of multi-junction solar cells to improve the conversion efficiency of photovoltaic systems

- Das, Narottam, Al Ghadeer, Abdulmohsen, Islam, Syed

  • Authors: Das, Narottam , Al Ghadeer, Abdulmohsen , Islam, Syed
  • Date: 2014
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 24th Australasian Universities Power Engineering Conference, AUPEC 2014; Perth, Australia; 28th September-1st October 2014 p. 1-5
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  • Description: This paper presents modelling and analysis of multi-junction solar cells to improve the conversion efficiency of photovoltaic (PV) power generation systems. For this modelling, Matlab/Simulink tool is used to obtain the simulation results. The modelling of a single junction solar cell can be performed by single or double diode models. From the simulation results, it was found that the double diode model is more accurate than the single diode model. Hence, the double diode model is used to simulate dual and triple junction solar cells. The simulations were performed under varying the critical factors, such as temperature and solar irradiance. The effect of these factors was clearly demonstrated on the I-V and P-V characteristics of the solar cells. It was found that the temperature increases, short circuit current increases slightly and open circuit voltage drops significantly. Consequently, the PV power generation decreases considerably. However, when the irradiance increases, the short circuit current increases slightly and the open circuit voltage increases significantly. Consequently, the power generation increases considerably and the conversion efficiency increases of the PV systems.

An enhancement to the spatial pyramid matching for image classification and retrieval

- Karmakar, Priyabrata, Teng, Shyh, Lu, Guojun, Zhang, Dengsheng

  • Authors: Karmakar, Priyabrata , Teng, Shyh , Lu, Guojun , Zhang, Dengsheng
  • Date: 2020
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 8, no. (2020), p. 22463-22472
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  • Description: Spatial pyramid matching (SPM) is one of the widely used methods to incorporate spatial information into the image representation. Despite its effectiveness, the traditional SPM is not rotation invariant. A rotation invariant SPM has been proposed in the literature but it has many limitations regarding the effectiveness. In this paper, we investigate how to make SPM robust to rotation by addressing those limitations. In an SPM framework, an image is divided into an increasing number of partitions at different pyramid levels. In this paper, our main focus is on how to partition images in such a way that the resulting structure can deal with image-level rotations. To do that, we investigate three concentric ring partitioning schemes. Apart from image partitioning, another important component of the SPM framework is a weight function. To apportion the contribution of each pyramid level to the final matching between two images, the weight function is needed. In this paper, we propose a new weight function which is suitable for the rotation-invariant SPM structure. Experiments based on image classification and retrieval are performed on five image databases. The detailed result analysis shows that we are successful in enhancing the effectiveness of SPM for image classification and retrieval. © 2013 IEEE.

Dynamic improvement of inductive power transfer systems with maximum energy efficiency tracking using model predictive control : analysis and experimental verification

- Liu, Shunpan, Mai, Ruikun, Zhou, Li, Li, Yong, Hu, Jiefeng, He, Zhengyou, Yan, Zhaotian, Wang, Shiqi

  • Authors: Liu, Shunpan , Mai, Ruikun , Zhou, Li , Li, Yong , Hu, Jiefeng , He, Zhengyou , Yan, Zhaotian , Wang, Shiqi
  • Date: 2020
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Power Electronics Vol. 35, no. 12 (2020), p. 12752-12764
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  • Description: For inductive power transfer (IPT) systems, loads and system input voltages are subject to change, which affects system efficiency and stability. This article presents a perturbation and observation (P&O) method for maximum energy efficiency tracking (MEET) with a model predictive control (MPC) scheme for improving the dynamic performance of series-series compensated IPT systems. In the IPT system, the inverter at the primary side incorporates the P&O method and phase shift modulation (PSM) to minimize system input power. Meanwhile, the rectifier at the secondary side is controlled by MPC control based PSM to improve the dynamic response of the output voltage. Simulated and experimental results show that, compared to the PI controller, the MPC controller, based on a simple but accurate mathematical model, has a better dynamic response to load and input voltage variations. With the MPC controller, the settling time of the output voltage is reduced by 85.7%, which indicates a particularly stable power supply to the load. Furthermore, MEET adopting the P&O method in the IPT system can promote the system efficiency by 1.85% on average when the output voltage is regulated by the MPC controller. © 1986-2012 IEEE.

The evolution of Turing Award Collaboration Network : bibliometric-level and network-level metrics

- Kong, Xiangjie, Shi, Yajie, Wang, Wei, Ma, Kai, Wan, Liangtian, Xia, Feng

  • Authors: Kong, Xiangjie , Shi, Yajie , Wang, Wei , Ma, Kai , Wan, Liangtian , Xia, Feng
  • Date: 2019
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Computational Social Systems Vol. 6, no. 6 (2019), p. 1318-1328
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  • Description: The year of 2017 for the 50th anniversary of the Turing Award, which represents the top-level award in the computer science field, is a milestone. We study the long-term evolution of the Turing Award Collaboration Network, and it can be considered as a microcosm of the computer science field from 1974 to 2016. First, scholars tend to publish articles by themselves at the early stages, and they began to focus on tight collaboration since the late 1980s. Second, compared with the same scale random network, although the Turing Award Collaboration Network has small-world properties, it is not a scale-free network. The reason may be that the number of collaborators per scholar is limited. It is impossible for scholars to connect to others freely (preferential attachment) as the scale-free network. Third, to measure how far a scholar is from the Turing Award, we propose a metric called the Turing Number (TN) and find that the TN decreases gradually over time. Meanwhile, we discover the phenomenon that scholars prefer to gather into groups to do research with the development of computer science. This article presents a new way to explore the evolution of academic collaboration network in the field of computer science by building and analyzing the Turing Award Collaboration Network for decades. © 2014 IEEE.

Trusted autonomous vehicle : measuring trust using on-board unit data

- Chowdhury, Abdullahi, Karmakar, Gour, Kamruzzaman, Joarder

  • Authors: Chowdhury, Abdullahi , Karmakar, Gour , Kamruzzaman, Joarder
  • Date: 2019
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications/13th IEEE International Conference on Big Data Science and Engineering, TrustCom/BigDataSE 2019 p. 787-792
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  • Description: Vehicular Ad-hoc Networks (VANETs) play an essential role in ensuring safe, reliable and faster transportation with the help of an Intelligent Transportation system. The trustworthiness of vehicles in VANETs is extremely important to ensure the authenticity of messages and traffic information transmitted in extremely dynamic topographical conditions where vehicles move at high speed. False or misleading information may cause substantial traffic congestions, road accidents and may even cost lives. Many approaches exist in literature to measure the trustworthiness of GPS data and messages of an Autonomous Vehicle (AV). To the best of our knowledge, they have not considered the trustworthiness of other On-Board Unit (OBU) components of an AV, along with GPS data and transmitted messages, though they have a substantial relevance in overall vehicle trust measurement. In this paper, we introduce a novel model to measure the overall trustworthiness of an AV considering four different OBU components additionally. The performance of the proposed method is evaluated with a traffic simulation model developed by Simulation of Urban Mobility (SUMO) using realistic traffic data and considering different levels of uncertainty. © 2019 IEEE.
  • Description: E1

Measuring trustworthiness of IoT image sensor data using other sensors' complementary multimodal data

- Islam, Mohammad, Karmakar, Gour, Kamruzzaman, Joarder, Murshed, Manzur

  • Authors: Islam, Mohammad , Karmakar, Gour , Kamruzzaman, Joarder , Murshed, Manzur
  • Date: 2019
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications/13th IEEE International Conference on Big Data Science and Engineering, TrustCom/BigDataSE 2019 p. 775-780
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  • Description: Trust of image sensor data is becoming increasingly important as the Internet of Things (IoT) applications grow from home appliances to surveillance. Up to our knowledge, there exists only one work in literature that estimates trustworthiness of digital images applied to forensic applications, based on a machine learning technique. The efficacy of this technique is heavily dependent on availability of an appropriate training set and adequate variation of IoT sensor data with noise, interference and environmental condition, but availability of such data cannot be assured always. Therefore, to overcome this limitation, a robust method capable of estimating trustworthy measure with high accuracy is needed. Lowering cost of sensors allow many IoT applications to use multiple types of sensors to observe the same event. In such cases, complementary multimodal data of one sensor can be exploited to measure trust level of another sensor data. In this paper, for the first time, we introduce a completely new approach to estimate the trustworthiness of an image sensor data using another sensor's numerical data. We develop a theoretical model using the Dempster-Shafer theory (DST) framework. The efficacy of the proposed model in estimating trust level of an image sensor data is analyzed by observing a fire event using IoT image and temperature sensor data in a residential setup under different scenarios. The proposed model produces highly accurate trust level in all scenarios with authentic and forged image data. © 2019 IEEE.
  • Description: E1

Selective adversarial learning for mobile malware

- Khoda, Mahbub, Imam, Tasadduq, Kamruzzaman, Joarder, Gondal, Iqbal, Rahman, Ashfaqur

  • Authors: Khoda, Mahbub , Imam, Tasadduq , Kamruzzaman, Joarder , Gondal, Iqbal , Rahman, Ashfaqur
  • Date: 2019
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications/13th IEEE International Conference on Big Data Science and Engineering, TrustCom/BigDataSE 2019 p. 272-279
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  • Description: Machine learning models, including deep neural networks, have been shown to be vulnerable to adversarial attacks. Adversarial samples are crafted from legitimate inputs by carefully introducing small perturbation to the input so that the classifier is fooled. Adversarial retraining, which involves retraining the classifier using adversarial samples, has been shown to improve the robustness of the classifier against adversarial attacks. However, it has been also shown that retraining with too many samples can lead to performance degradation. Hence, a careful selection of the adversarial samples that are used to retrain the classifier is necessary, yet existing works select these samples in a randomized fashion. In our work, we propose two novel approaches for selecting adversarial samples: based on the distance from cluster center of malware and based on the probability derived from a kernel based learning (KBL). Our experiment results show that both of our selective mechanisms for adversarial retraining outperform the random selection technique and significantly improve the classifier performance against adversarial attacks. In particular, selection with KBL delivers above 6% improvement in detection accuracy compared to random selection. The method proposed here has greater impact in designing robust machine learning system for security applications. © 2019 IEEE.
  • Description: E1

A low-complexity equalizer for video broadcasting in cyber-physical social systems through handheld mobile devices

- Solyman, Ahmad, Attar, Hani, Khosravi, Mohammad, Menon, Varun, Jolfaei, Alireza, Balasubramanian, Venki, Selvaraj, Buvana, Tavallali, Pooya

  • Authors: Solyman, Ahmad , Attar, Hani , Khosravi, Mohammad , Menon, Varun , Jolfaei, Alireza , Balasubramanian, Venki , Selvaraj, Buvana , Tavallali, Pooya
  • Date: 2020
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 8, no. (2020), p. 67591-67602
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  • Description: In Digital Video Broadcasting-Handheld (DVB-H) devices for cyber-physical social systems, the Discrete Fractional Fourier Transform-Orthogonal Chirp Division Multiplexing (DFrFT-OCDM) has been suggested to enhance the performance over Orthogonal Frequency Division Multiplexing (OFDM) systems under time and frequency-selective fading channels. In this case, the need for equalizers like the Minimum Mean Square Error (MMSE) and Zero-Forcing (ZF) arises, though it is excessively complex due to the need for a matrix inversion, especially for DVB-H extensive symbol lengths. In this work, a low complexity equalizer, Least-Squares Minimal Residual (LSMR) algorithm, is used to solve the matrix inversion iteratively. The paper proposes the LSMR algorithm for linear and nonlinear equalizers with the simulation results, which indicate that the proposed equalizer has significant performance and reduced complexity over the classical MMSE equalizer and other low complexity equalizers, in time and frequency-selective fading channels. © 2013 IEEE.

ESMLB : efficient switch migration-based load balancing for multicontroller SDN in IoT

- Sahoo, Kshira, Puthal, Deepak, Tiwary, Mayank, Usman, Muhammad, Sahoo, Bibhudatta, Wen, Zhenyu, Sahoo, Biswa, Ranjan, Rajiv

  • Authors: Sahoo, Kshira , Puthal, Deepak , Tiwary, Mayank , Usman, Muhammad , Sahoo, Bibhudatta , Wen, Zhenyu , Sahoo, Biswa , Ranjan, Rajiv
  • Date: 2020
  • Type: Text , Journal article
  • Relation: IEEE Internet of Things Journal Vol. 7, no. 7 (2020), p. 5852-5860
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  • Description: In software-defined networks (SDNs), the deployment of multiple controllers improves the reliability and scalability of the distributed control plane. Recently, edge computing (EC) has become a backbone to networks where computational infrastructures and services are getting closer to the end user. The unique characteristics of SDN can serve as a key enabler to lower the complexity barriers involved in EC, and provide better quality-of-services (QoS) to users. As the demand for IoT keeps growing, gradually a huge number of smart devices will be connected to EC and generate tremendous IoT traffic. Due to a huge volume of control messages, the controller may not have sufficient capacity to respond to them. To handle such a scenario and to achieve better load balancing, dynamic switch migrating is one effective approach. However, a deliberate mechanism is required to accomplish such a task on the control plane, and the migration process results in high network delay. Taking it into consideration, this article has introduced an efficient switch migration-based load balancing (ESMLB) framework, which aims to assign switches to an underutilized controller effectively. Among many alternatives for selecting a target controller, a multicriteria decision-making method, i.e., the technique for order preference by similarity to an ideal solution (TOPSIS), has been used in our framework. This framework enables flexible decision-making processes for selecting controllers having different resource attributes. The emulation results indicate the efficacy of the ESMLB. © 2014 IEEE.