Dr Ali Hilal Al-Bayatti

Job: Associate Professor in Cyber Security

Faculty: Computing, Engineering and Media

School/department: School of Computer Science and Informatics

Research group(s): Cyber Technology Institute (CTI) (Software Technology Research Laboratory (STRL))

Address: 黑料网, The Gateway, Leicester, LE1 9BH, United Kingdom

T: +44 (0)116 207 8586

E: alihmohd@dmu.ac.uk

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Personal profile

Dr. Ali Al-Bayatti is a Senior Lecturer in Intelligent Transportation systems at Software Technology Research Laboratory, a research institute established within 黑料网, Leicester, UK. , his research deals with vehicular (e.g. Vehicular Ad hoc Networks), Cyber Security (e.g. Security Management) and smart technologies (e.g. Context-aware Systems) that promote collective intelligence. Applications range from promoting comfort, to enabling safety in critical scenarios. The goal of his research is to improve the effectiveness, efficiency, mobility, security and safety of transportationsystems.

Dr. Ali Al-Bayatti is currently teaching Undergraduate module ‘CTEC3604 Multi-service Networks’ in Computer Science. He is currently the programme leader for MSc Cyber Technology, MSc Software Engineering, MSc Cyber Security and MSc Professional Practice in Digital Forensics and Security.

Publications and outputs

dc.title: A Hybrid Classification and Identification of Pneumonia Using African Buffalo Optimization and CNN from Chest X-Ray Images dc.contributor.author: Alalwan, Nasser; Taloba, Ahmed I.; Abozeid, Amr; Alzahrani, Ahmed Ibrahim; Al-Bayatti, Ali Hilal dc.description.abstract: An illness known as pneumonia causes inflammation in the lungs. Since there is so much information available from various X-ray images, diagnosing pneumonia has typically proven challenging. To improve image quality and speed up the diagnosis of pneumonia, numerous approaches have been devised. To date, several methods have been employed to identify pneumonia. The Convolutional Neural Network (CNN) has achieved outstanding success in identifying and diagnosing diseases in the fields of medicine and radiology. However, these methods are complex, inefficient, and imprecise to analyze a big number of datasets. In this paper, a new hybrid method for the automatic classification and identification of Pneumonia from chest X-ray images is proposed. The proposed method (ABO-CNN) utilized the African Buffalo Optimization (ABO) algorithm to enhance CNN performance and accuracy. The Weinmed filter is employed for pre-processing to eliminate unwanted noises from chest X-ray images, followed by feature extraction using the Grey Level Co-Occurrence Matrix (GLCM) approach. Relevant features are then selected from the dataset using the ABO algorithm, and ultimately, high-performance deep learning using the CNN approach is introduced for the classification and identification of Pneumonia. Experimental results on various datasets showed that, when contrasted to other approaches, the ABO-CNN outperforms them all for the classification tasks. The proposed method exhibits superior values like 96.95%, 88%, 86%, and 86% for accuracy, precision, recall, and F1-score, respectively. dc.description: open access article
dc.title: Evaluating self-reported pedestrian behaviour and investigating factors influencing road interactions in Jordan dc.contributor.author: Shehadeh, Eman; Al-Bayatti, Ali Hilal; Bingol, Muhammed Ali dc.description.abstract: A variety of self-reported questionnaires have been developed worldwide across to classify pedestrians鈥� behaviours. However, to the best of our knowledge, no pedestrian behaviour questionnaire has been validated to investigate Jordanian pedestrians鈥� behaviour. Thus, this study aimed to develop and validate a self-reporting pedestrian behaviour questionnaire for the Jordanian population (JPBQ), spanning all ages. Our JPBQ consisted of 40 items describing pedestrian behaviour, whilst the validation study itself included 400 participants (45.25% females). Principal component analysis (PCA) revealed a four-factor structure: transgressions, lapses, positive behaviours, and aggressive behaviours for both Long (31-item) and short (20-item) versions of the JPBQ, confirming validity (significant association with p < 0.05) and reliability (Cronbach鈥檚 alpha > 0.7) for each factor. This addressed the reliability issue with positive behaviour factor found in previous self-reported questionnaires by incorporating effective questions concerning positive behaviours while walking. Across the four factors, the highest mean scores that pedestrians reported were for positive behaviours, while the least commonly reported behaviours were aggressive behaviours and lapses. Male participants were found to declare higher rates of violations and aggressions, while young participants reported more violations and fewer lapses. The lack of alternatives to walking was positively associated with unsafe behaviours (violations, errors, lapses). Income level was negatively associated with aggressive behaviours towards other road users. Divorced individuals were found to self-report lower rates of lapses and positive behaviours. Overall, this study contributes to understanding pedestrian behaviours in Jordan, providing a reliable validated questionnaire for research and road safety initiatives. dc.description: open access article
dc.title: Advancements in brain tumor identification: Integrating synthetic GANs with federated-CNNs in medical imaging analysis dc.contributor.author: Alalwan, Nasser; Alwadin, Ayed; Alzahrani, Ahmed Ibrahim; Al-Bayatti, Ali Hilal; Abozeid, Amr; El-Aziz, Rasha M. Abd dc.description.abstract: Brain tumors are a significant health concern worldwide, necessitating accurate and timely diagnosis for effective treatment planning and management. However, conventional methods for brain tumor identification through medical imaging analysis often face challenges related to accuracy, efficiency, and privacy concerns. Current approaches may struggle with limited datasets, privacy regulations hindering data sharing, and the need for specialized expertise in interpreting medical images. Accurately identifying brain tumors is pivotal in diagnosis, treatment planning, and patient prognosis. This research proposes a novel approach for advancing brain tumor identification by integrating Synthetic Generative Adversarial Networks with federated convolutional neural Networks in medical imaging analysis. Federated-CNNs are a type of neural network architecture designed for federated learning scenarios. In federated learning, model training occurs locally on data distributed across multiple devices or institutions without exchanging raw data. Federated CNNs allow collaborative model training across these distributed datasets by aggregating local model updates rather than exchanging raw data. This approach ensures that sensitive data remain localized within each participating institution, thus addressing privacy concerns in medical imaging analysis. Our methodology harnesses the power of GANs to generate synthetic brain MRI images, addressing data scarcity issues commonly encountered in medical imaging datasets. These synthetic images are then utilized in conjunction with Federated-CNNs, enabling cooperative model training between many healthcare institutions while maintaining the anonymity and privacy of data. Moreover, integrating Federated CNNs ensures that sensitive medical imaging data remain localized within participating institutions, addressing data privacy concerns and fostering collaboration among medical professionals. The research advances medical imaging analysis by introducing a novel methodology that leverages existing technologies to improve brain tumor identification accuracy. Specifically, the feature extraction phase using DenseNet121, implemented in MATLAB, achieves an outstanding accuracy of 99.82鈥�% and outperforms Various existing methods, including Inception-V3, ResNet-18, and GoogleNet, demonstrating the efficacy of our approach in capturing discriminative features from medical imaging data. This high accuracy underscores the potential of our methodology to enhance diagnostic accuracy and clinical decision-making in neurology and oncology. The research offers a promising avenue for further exploration and innovation in medical imaging analysis, with significant implications for improving patient outcomes and advancing healthcare practices. dc.description: open access article
dc.title: Security, Privacy, and Decentralized Trust Management in VANETs: A Review of Current Research and Future Directions dc.contributor.author: Kiraz, Mehmet Sabir; AlMarshoud, Mishri Saleh; Al-Bayatti, Ali Hilal dc.description.abstract: Vehicular Ad Hoc Networks (VANETs) are powerful platforms for vehicular data services and applications. The increasing number of vehicles has made the vehicular network diverse, dynamic, and large-scale, making it difficult to meet the 5G network鈥檚 demanding requirements. Decentralized systems are interesting and provide attractive services because they are publicly available (transparency), have an append-only ledger (robust integrity protection), remove single points of failure, and enable distributed key management and communication in a peer-to-peer network. Researchers dedicated substantial efforts to advancing vehicle communications, however conventional cryptographic mechanisms are insufficient which enabled us to look at decentralized technologies. Therefore, we revisit decentralized approaches with VANETs. Endpoint devices hold a wallet which may incorporate threshold key management methods like MPC wallets, HD Wallets, or multi-party threshold ECDSA/EdDSA/BLS. We also discuss trust management approaches and demonstrate how decentralization can improve integrity, security, privacy, and resilience to single points of failure. We also conduct a comprehensive review, comparing them with current requirements, and the latest authentication and secure communication architectures, which require the involvement of trusted but non-transparent authorities in certificate issuance/revocation. We highlight the limitations of these schemes from PKI deployment and recommend future research, particularly in the realm of quantum cryptography. dc.description: The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
dc.title: Mitigating MEV attacks with a two-tiered architecture utilizing verifiable decryption dc.contributor.author: Kiraz, Mehmet Sabir; Alnajjar, Mustafa Ibrahim; Al-Bayatti, Ali Hilal; Kardas, Suleyman dc.description.abstract: A distributed ledger is a shared and synchronized database across multiple designated nodes, often referred to as miners, validators, or peers. These nodes record, distribute, and access data to ensure security and transparency. However, these nodes can be compromised and manipulated by selectively choosing which user transactions to include, exclude, or reorder, thereby gaining an unfair advantage. This is known as a miner/maximal extractable value (MEV) attack. Existing solutions can be classified into various categories, such as MEV auction platforms and time-based ordering properties, which rely on private transaction Mempools. In this paper, we first identify some architectural weaknesses inherent in the latest proposals that divide the block creation and execution roles into separate functions: block builders and block executors. The existing schemes mainly suffer from the verifiability of the decryption process, where a corrupted builder or executor can simply deny the inclusion of specific targeted transactions by exploiting the fact that all transactions are in plain format. To address this, we propose an enhanced version that incorporates a verifiable decryption process. On a very high level, within our proposal, whenever an Executor or a Builder performs a decryption, the decrypted values must be broadcasted. This enables any entity in the network to publicly verify whether the decryption was executed correctly, thus preventing malicious behavior by either party from going undetected. We also define a new adversary model for MEV and conduct a comprehensive security analysis of our protocol against all kinds of potential adversaries related to MEV. Finally, we present the performance analysis of the proposed solution. dc.description: open access article
dc.title: A New Framework for Enhancing VANETs through Layer 2 DLT Architectures with Multiparty Threshold Key Management and PETs dc.contributor.author: Kiraz, Mehmet Sabir; Al-Bayatti, Ali Hilal; Adarbah, Haitham; Kardas, Suleyman; Al-Bayatti, Hilal M. Y. dc.description.abstract: This work proposes a new architectural approach to enhance the security, privacy, and scalability of VANETs through threshold key management and Privacy Enhancing Technologies (PETs), such as homomorphic encryption and secure multiparty computation, integrated with Decentralized Ledger Technologies (DLTs). These advanced mechanisms are employed to eliminate centralization and protect the privacy of transferred and processed information in VANETs, thereby addressing privacy concerns. We begin by discussing the weaknesses of existing VANET architectures concerning trust, privacy, and scalability and then introduce a new architectural framework that shifts from centralized to decentralized approaches. This transition applies a decentralized ledger mechanism to ensure correctness, reliability, accuracy, and security against various known attacks. The use of Layer 2 DLTs in our framework enhances key management, trust distribution, and data privacy, offering cost and speed advantages over Layer 1 DLTs, thereby enabling secure vehicle-to-everything (V2X) communication. The proposed framework is superior to other frameworks as it improves decentralized trust management, adopts more efficient PETs, and leverages Layer 2 DLT for scalability. The integration of multiparty threshold key management and homomorphic encryption also enhances data confidentiality and integrity, thus securing against various existing cryptographic attacks. Finally, we discuss potential future developments to improve the security and reliability of VANETs in the next generation of networks, including 5G networks. dc.description: open access article
dc.title: Effect of roadway environment characteristics on pedestrian safety at signalised intersections in Amman dc.contributor.author: Shehadeh, Eman A.; Al-Bayatti, Ali Hilal; Bingol, Muhammed Ali dc.description.abstract: Pedestrian safety becoming a serious issue, especially in developing nations, wherein higher crash rates have been reported by the World Health Organization. Despite evidence suggesting higher pedestrian crash counts at signalised intersections in urban areas, there is a lack of in-depth analysis in most developing countries. Motivated by this need, this study aims to: 1) identify significant roadway environment characteristics and traffic volume factors influencing pedestrian 鈥� vehicle accidents at signalised intersections in Amman, Jordan, 2) elucidate relationships between pedestrian 鈥� vehicle accidents and these factors, and 3) discuss the limitations of pedestrian crash data and propose solutions for future research. We have analysed 166 accidents at 47 signalised intersections in Amman during the period of 2007鈥�2019. The multilevel Generalised Linear Mixed Gamma regression model is the best fit for the data, indicating significant positive correlations between pedestrian crash frequencies and Annual Average Daily Traffic, pedestrian crossing volume, number of lanes, average lane width, and number of parking sides. Conversely, commercial land use and the presence of public transit facilities showed significant negative correlations with pedestrian crashes. This work presents a novel approach that will help developing countries to determine and explain pedestrian crash causes while considering various challenges in these contexts. dc.description: open access article
dc.title: Security, Privacy, and Decentralized Trust Management in VANETs: A Review of Current Research and Future Directions dc.contributor.author: AlMarshoud, Mishri Saleh; Al-Bayatti, Ali Hilal; Kiraz, Mehmet Sabir dc.description.abstract: Vehicular Ad Hoc Networks (VANETs) are powerful platforms for vehicular data services and applications. The increasing number of vehicles has made the vehicular network diverse, dynamic, and large-scale, making it difficult to meet the 5G network鈥檚 demanding requirements. Decentralized systems are interesting and provide attractive services because they are publicly available (transparency), have an append-only ledger (robust integrity protection), remove single points of failure, and enable distributed key management and communication in a peer-to-peer network. Researchers dedicated substantial efforts to advancing vehicle communications, however conventional cryptographic mechanisms are insufficient which enabled us to look at decentralized technologies. Therefore, we revisit decentralized approaches with VANETs. Endpoint devices hold a wallet which may incorporate threshold key management methods like MPC wallets, HD Wallets, or multi-party threshold ECDSA/EdDSA/BLS. We also discuss trust management approaches and demonstrate how decentralization can improve integrity, security, privacy, and resilience to single points of failure. We also conduct a comprehensive review, comparing them with current requirements, and the latest authentication and secure communication architectures, which require the involvement of trusted but non-transparent authorities in certificate issuance/revocation. We highlight the limitations of these schemes from PKI deployment and recommend future research, particularly in the realm of quantum cryptography. dc.description: The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
dc.title: Location Privacy in VANETs: Provably Secure Anonymous Key Exchange Protocol Based on Self-Blindable Signatures dc.contributor.author: Kiraz, Mehmet Sabir; Al-Bayatti, Ali Hilal; AlMarshoud, Mishri Saleh dc.description.abstract: Security and privacy in vehicular ad hoc networks (VANETs) are challenging in terms of Intelligent Transportation Systems (ITS) features. The distribution and decentralisation of vehicles could threaten location privacy and confidentiality in the absence of trusted third parties (TTP)s or if they are otherwise compromised. If the same digital signatures (or the same certificates) are used for different communications, then adversaries could easily apply linking attacks. Unfortunately, most of the existing schemes for VANETs in the literature do not satisfy the required levels of security, location privacy, and efficiency simultaneously. This paper presents a new and efficient end-to-end anonymous key exchange protocol based on Yang et al. 's self-blindable signatures. In our protocol, vehicles first privately blind their own private certificates for each communication outside the mix-zone and then compute an anonymous shared key based on zero-knowledge proof of knowledge (PoK). The efficiency comes from the fact that once the signatures are verified, the ephemeral values in PoK are also used to compute a shared key through an authenticated Diffie-Hellman key exchange protocol. Therefore, the protocol does not require any further external information to generate a shared key. Our protocol also does not require an interference with the Roadside Units or Certificate Authorities, and hence can be securely run outside the mixed-zones. We demonstrate the security of our protocol in an ideal/real simulation paradigm. Hence, our protocol achieves secure authentication, forward unlinkability, and accountability. Furthermore, the performance analysis shows that our protocol is more efficient in terms of computational and communication overheads compared to existing schemes. dc.description: open access article
dc.title: Improved Chaff-Based CMIX for Solving Location Privacy Issues in VANETs dc.contributor.author: Kiraz, Mehmet Sabir; Al-Bayatti, Ali Hilal; Saleh AlMarshoud, Mishri dc.description.abstract: Safety application systems in Vehicular Ad-hoc Networks (VANETs) require the dissemination of contextual information about the scale of neighbouring vehicles; therefore, ensuring security and privacy is of utmost importance. Vulnerabilities in the messages and the system鈥檚 infrastructure introduce the potential for attacks that lessen safety and weaken passengers鈥� privacy. The purpose of short-lived anonymous identities, called 鈥減seudo-identities鈥�, is to divide the trip into unlinkable short passages. Researchers have proposed changing pseudo-identities more frequently inside a pre-defined area, called a cryptographic mix-zone (CMIX) to ensure enhanced protection. According to ETSI ITS technical report recommendations, the researchers must consider the low-density scenarios to achieve unlinkability in CMIX. Recently, Christian et al. proposed a Chaff-based CMIX scheme that sends fake messages under the consideration of low-density conditions to enhance vehicles鈥� privacy and confuse attackers. To accomplish full unlinkability, in this paper, we first show the following security and privacy vulnerabilities in the Christian et al. scheme: Linkability attacks outside the CMIX may occur due to deterministic data sharing during the authentication phase (e.g., duplicate certificates for each communication). Adversaries may inject fake certificates, which breaks Cuckoo Filters鈥� (CFs) updates authenticity, and the injection may be deniable. CMIX symmetric key leakage outside the coverage may occur. We propose a VPKI-based protocol to mitigate these issues. First, we use a modified version of Wang et al.鈥檚 scheme to provide mutual authentication without revealing the real identity. To this end, the messages of a vehicle are signed with a different pseudo-identity 鈥渃ertificate鈥�. Furthermore, the density is increased via the sending of fake messages in low traffic periods to provide unlinkability outside the mix-zone. Second, unlike Christian et al.鈥檚 scheme, we use the Adaptive Cuckoo Filter (ACF) instead of CF to overcome the false positives鈥� effect on the whole filter. Moreover, to prevent any alteration of the ACFs, only RUSs distribute the updates, and they sign the new fingerprints. Third, the mutual authentication prevents any leakage from the mix zones鈥� symmetric keys by generating a fresh one for each communication through a Diffie鈥揌ellman key exchange. dc.description: open access article

Key research outputs

Research interests/expertise

Intelligent transpiration
Vehicular Ad hoc Networks
Mobile Computing
Wireless Computing
Context-aware Systems
Pervasive Computing
Computer/Mobile Security.

Areas of teaching

CTEC3604 Multi-service Networks (30 credit).

Qualifications

B.Sc. in Computer Engineering and Information Technology at the University of Technology, Iraq.

Ph.D. in Computer Science at 黑料网, UK.

Courses taught

Programme leader for MSc Cyber Technology, MSc Software Engineering, MSc Cyber Security and MSc Professional Practice in Digital Forensics and Security.

Current research students

Successful PhD Completion

Dr. Khalid Alodadi “Solving Non-Line of Sight using Context-aware Systems in Vehicle Ad Hoc Networks” 黑料网 (2016).

Dr. Ahmed Alghamdi “Features interaction: detection and resolution in Smart Homes Systems” 黑料网 (2016).

Dr. Tareq Binjammaz “GPS Integrity Monitoring for an Intelligent Transport System“ 黑料网 (2015).

Dr. Abdullah Aldawsari “Context-aware Driving Behaviour Detection System in Vehicle Ad Hoc Networks“ 黑料网 (2015).

Dr. Yasser Almajed “Privacy Management in Data Warehousing” 黑料网 (2015). Dr. Fahad Alqahtani “E-commerce Customer Anonymity and Fair Exchange Protocol for Digital Contents” 黑料网 (2015).

Dr. Abdulmalik Alhammad “Intelligent Parking Systems in Vehicle Ad Hoc Networks” 黑料网 (2015).

Dr. Hani Alquhayz “Security Management System for 4G Heterogenous Networks“ 黑料网 (2015).

Dr. Mussab Aswad “Crash Detection Model Using Dynamic Bayesian Networks” 黑料网 (2014).

Dr. Mafawez Alharbi “Context-aware PLE Architecture”, 黑料网 (2014).

Dr. Laila Alhimale “Fall Detection Algorithm for Video Images”, 黑料网 (2013).

Dr. Saif Al-Sultan “Context Aware Driving Behaviour Model for VANET”, 黑料网 (2013).

Dr. Awatef Rahuma “Semantically Enhanced Image Tagging System”, 黑料网 (2013).

Dr. Moath Al-Doori “Directional Routing Technique in Vehicle Ad hoc Networks, 黑料网 (2011).

Dr. Muhammed Khan “A Co-Evolutionary Framework to Reducing the Gap between and Information Technology (2011).

Current PhD Students (Main Supervisor)

Mr. Dennis Bohmlander "Innovative Crash-sensing Architectures - A new approach in contactless vehicle crash detection" 黑料网.

Mr. Raphael Riebl "Perfomance Testing methodology for Vehicle Ad hoc Networks" 黑料网.

Mr. Sadir Fadhil "Context-aware overtaking assistant system. 黑料网.

Mr. Nawaf Alqabandi “Context-aware Intrusion Detection system using Artificial intelligence in VANET” 黑料网.

Successful MSc Completion

Mr. Shadman Salah (2014).

Mr. Ahmed Malik (2013) “Factors effecting Delivering Insulin for diabetic patients using Bayesian Networks”

Mr. Anjanna Silva (2013) “Car Polling System”

Mr. Anas Alsharif (2012) “Automated Taxi Dispatch System (Taxi Business) 黑料网.

Mr. Mahran Alsubee (2012) “Intelligent Car Parking System - A case of City of Medina, Saudi Arabia” 黑料网.

Mr. Salman Alenezi (2012) “The Lines Between Augmented Reality and Virtual Reality” 黑料网.

Mr. Uqonna Ekwueme (2011)“Intelligent Car Parking Schemes” 黑料网.

Mrs. Nada Al-Fakih (2011) “Cloud Based Personal Health Record” 黑料网.

Mrs. Entisar Alshirf (2011) “Selection of Computer Programming Languages for Developing Distributed Systems. 黑料网.

Mrs. Ohud Almutairi (2011) “Designing an Effective Intersection Collision Warning System: An Investigation into Important Criteria” 黑料网.

Mrs. Ruqayah Aljameel (2011) “The Application’s Usability Evaluation of Web-based Geographic Information System for Pst Office Webs” 黑料网.

Mr. Khalid Shaban (2011) “Evaluating Mobile Application Performance and Power Consumption Trough Model-Driven Engineering Methodology” 黑料网.

Mrs. Laila Elgamel (2011) “ Selection of Programming Languages for Developing Distributed Systems” 黑料网.

Mr. Ahmed Alghamdi (2010) “Feasibility of Separating Control/Data in 802.11 Family” 黑料网.

Mr. Mafawez Alharbi (2010) “Mobile Lecture” 黑料网.

Mr. Abdulkariem Alqarni (2010) “Global Intelligent Parking Schemes” 黑料网.

Mr. Abdullah Algashami (2010) “Good Practice for Effective E-assessment” 黑料网.

Mr. Sharaf Alzhrani (2010) “Intelligent Application for Car Hiring (Mileage Tracking Application)” 黑料网.

Mr. Anas Alsharif (2010) “Automated Taxi Dispatch System” 黑料网.

Mrs. Asma Alothaim (2010) “Location Finder and Weather Forecast Application” 黑料网.

Mr. Fauwaz Alshammari “Risk Management in Software Development Projects” 黑料网.

Mr. Ali Almiman “Security Survey in VoIP” 黑料网. Mr. Thamir Alghamdi “Comparison of Two Parking Management Systems” 黑料网.

Professional esteem indicators

Journal Article Reviewing
Networking [IET] 2016. Vehicular Communications [Elsevier] 2014, 2015, 2016. Sensors [MDPI] 2016. Frontiers of Information Technology & Electronic Engineering [Springer] 2014, 2015. The Journal of Engineering [IET] 2014, 2015; Journal of Advances in Engineering Software [Elsevier]; Journal of Network & Computer Applications 2013 [Elsevier]; Computer & Electrical Engineering Journal (CEE) 2011, 2012 [Elsevier]; International Journal of Ad Hoc Ubiquitous Computing (IJAHUC) 2010

Program Committee Member / Other Conference & Workshop Reviewing
IEEE 83rd Vehicular Technology Conference: VTC2016-Spring 15–18 May 2016, Nanjing, ChinaIEEE Vehicular Technology Conference: VTC2015-Spring 11–14 May 2015, Glasgow, ScotlandInternational Conference on Computer, Communications, and Control Technology (I4CT) 2014Springer based Applied Electromagnetic International Conference (APPEIC) 2014Renewable Energy and Green Technology International Conference (REEGETECH) 2014International Symposium on Technology Management and Emerging Technologies (ISTMET) 2014International Conference on Communication and Computer Engineering, focusing on Industrial and Manufacturing Theory and Applications of Electronics, Communications, Computing, and Information Technology (ICOCOE) 2014IEEE Symposium on Computer Application & Industrial Electronics (ISCAIE) 2013IEEE International RF and Microwave Conference (RFM) 2013IEEE Symposium on Industrial Electronics and Applications (ISIEA) 2013IEEE Conference on Wireless Sensors (ICWiSE) 2013IEEE Symposium on Computer & Informatics (ISCI) 2013IEEE Asia-Pacific Conference on Applied Electromagnetic (APACE ) 2012IEEE Symposium on Wireless Technology & Applications (ISWTA) 2012, 2013IEEE Symposium on Industrial Electronic & Applications (ISIEA ) 2012ICNS Networking and Services 2008, 2009, 2010, 2011, 2012, 2013, 2014International Symposium on Innovation in Information & Communication Technology (ISIICT) 2011, 2012, 2013, 2014International Conference on Computer Science & Information Technology (ICCSIT) 2011, 2012, 2013, 2014 International Symposium on Wireless Pervasive Computing (ISWPC) 2010 Member of the Steering committee of the International Online Workshop on writing a research paper (IOW-WRP) 2011AIRCC Worldwide Conferences