Mohammad Alauthman | Detection | Excellence in Research

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Assist Prof Dr. Mohammad Alauthman | Detection | Excellence in Research

Assistant Professor at Information Security Department, University of Petra, Jordan

Dr. Mohammad Alauthman is an accomplished academic with a focus on cybersecurity and network security. Currently serving as an Assistant Professor at Petra University in Amman, Jordan, since 2020, Mohammad teaches a variety of courses in the Department of Information Security, including topics such as SOC analyst, Ethical Hacking, and Digital Forensics Investigation. Prior to this role, Mohammad was an Assistant Professor at Zarqa University from 2016 to 2020, where they taught courses in computer science, including Advanced Information and Networks Security and Introduction to Cybersecurity. Mohammad’s research interests lie in the application of artificial intelligence to cybersecurity, particularly in areas such as botnet detection, DDoS detection, and spam email detection. They have received grants for several research projects, demonstrating their dedication to advancing knowledge in their field. Mohammad’s academic background and teaching experience make them a valuable asset to the academic community, contributing to both research and education in the field of cybersecurity.

Profile

Education

Dr. Mohammad Alauthman is an Assistant Professor with a strong background in computer science and a specialization in network security. They earned their Ph.D. in Computer Science from Northumbria University at Newcastle, UK, in 2016, with a focus on Network Security. Their doctoral thesis, titled “An Efficient Approach to Online Bot Detection Based on a Reinforcement Learning Technique,” demonstrates their expertise in this field. Prior to their Ph.D., Mohammad completed a Master’s degree in Computer Science from Amman Arab University, Jordan, in 2005, and a Bachelor’s degree in Computer Science from Hashemite University, Jordan, in 2002. Mohammad’s academic journey has equipped them with a comprehensive understanding of computer science principles, particularly in the realm of network security.

Experience:

Dr. Mohammad Alauthman has a wealth of experience in academia, holding key positions at various institutions. Since 2021, they have served as the Chairman of the Information Security department at the Faculty of Information Technology, University of Petra, Amman, Jordan. Mohammad has also been a Full-time Assistant Professor in the Department of Information Security at the same university since 2020. Prior to their current role, Mohammad was the Chairman of the Internet Technology department and an Assistant Professor at the Faculty of Information Technology, Zarqa University, Jordan, from 2018 to 2020. Before that, they were a Full-time Assistant Professor in the Computer Science Department at Zarqa University from 2016 to 2018. Mohammad’s academic career also includes positions as a Lecturer in the Department of Computer Science and Information at Majmmah University, Saudi Arabia, from 2008 to 2012, and as a Lecturer at Al-Balqa Applied University, Jordan, from 2007 to 2008. These roles have provided Mohammad with a diverse range of experiences in academia, contributing to their expertise in computer science and information security.

Research Interest:

Dr. Mohammad Alauthman’s research interests are primarily focused on cybersecurity and network security, with a particular emphasis on cross-layered solutions for intrusion detection systems. Their central research revolves around the use of artificial intelligence for early botnet detection, DDoS detection, spam email detection, Internet of Things (IoT) security, and network traffic classification. In addition to their work in cybersecurity, Mohammad also has research interests in healthcare, specifically in the areas of skin cancer detection, diabetic retinopathy, and pain intensity assessment, utilizing deep learning techniques. Their research projects are interdisciplinary and aimed at addressing real-life problems, reflecting their commitment to advancing knowledge and solving practical challenges in these fields.

Grants:

Dr. Mohammad Alauthman has received several grants to support their research in cybersecurity and network security. In 2022, they were awarded a grant from the Dean of Scientific Research at the University of Petra (UoP) for a project titled “Forecasting Citation Counts Using Deep Recurrent Neural Network Techniques.” In 2021, Mohammad received a grant from Al-Balqa Applied University for a project focused on “Darknet Traffic Identification Using Max Voting Algorithms.” Prior to that, in 2019, they received another grant from Al-Balqa Applied University for their work on “Fast Flux Botnet Catcher Approach (FFBCA).” At Zarqa University (ZU), Mohammad received grants from the Dean of Scientific Research for two projects. In 2017, they received a grant for a project titled “P2P Bot Detection Using Deep Learning with Traffic Reduction Schema.” In 2018, Mohammad received a grant for a project titled “Botnet Spam Email Detection Using Deep Recurrent Neural Network.” These grants highlight Mohammad’s dedication to advancing research in cybersecurity and network security, focusing on innovative approaches to detect and mitigate threats.

Teaching Experience:

Dr. Mohammad Alauthman has been serving as an Assistant Professor at Petra University in the Department of Information Security, Faculty of Information Technology, Amman, Jordan, since 2020. In this role, they teach a range of courses covering topics such as SOC analyst, Ethical Hacking, Intrusion Detection System, Digital Forensics Investigation, Database Security, E-commerce Environment Security, Information and Network Security, Wireless Networks, and Introduction to Data Communication & Networking. Prior to joining Petra University, Mohammad was an Assistant Professor at Zarqa University in the Department of Computer Science, Faculty of Information Technology, Zarqa, Jordan, from 2016 to 2020. During their tenure at Zarqa University, Mohammad taught courses including Advanced Information and Networks Security (Master Level), Introduction to Cybersecurity, Introduction to Machine Learning, Networks, Artificial Intelligence, Special Languages in CS II (Python), Information Retrieval, Programming Language I (Java), Concepts of Programming Languages, Research Methodology and Ethics, and Advanced Programming Language (C#). These positions highlight Mohammad’s expertise in teaching a wide range of topics related to computer science and information security.

Publications:

  1. IoT transaction processing through cooperative concurrency control on fog–cloud computing environment
    • Authors: A Al-Qerem, M Alauthman, A Almomani, BB Gupta
    • Citations: 244
    • Year: 2019
  2. An efficient reinforcement learning-based Botnet detection approach
    • Authors: M Alauthman, N Aslam, M Al-Kasassbeh, S Khan, A Al-Qerem, KKR Choo
    • Citations: 131
    • Year: 2020
  3. A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks
    • Authors: M Alauthaman, N Aslam, L Zhang, R Alasem, MA Hossain
    • Citations: 129
    • Year: 2018
  4. Phishing Website Detection With Semantic Features Based on Machine Learning Classifiers: A Comparative Study
    • Authors: A Almomani, M Alauthman, MT Shatnawi, M Alweshah, A Alrosan
    • Citations: 120
    • Year: 2022
  5. DNS rule-based schema to botnet detection
    • Authors: K Alieyan, A Almomani, M Anbar, M Alauthman, R Abdullah, BB Gupta
    • Citations: 113
    • Year: 2021
  6. Machine Learning-driven optimization for SVM-based intrusion detection system in vehicular ad hoc networks
    • Authors: A Alsarhan, M Alauthman, E Alshdaifat, AR Al-Ghuwairi, A Al-Dubai
    • Citations: 49
    • Year: 2023
  7. Feature selection using a machine learning to classify a malware
    • Authors: M Al-Kasassbeh, S Mohammed, M Alauthman, A Almomani
    • Citations: 49
    • Year: 2020
  8. An online intrusion detection system to cloud computing based on NeuCube algorithms
    • Authors: A Almomani, M Alauthman, F Albalas, O Dorgham, A Obeidat
    • Citations: 43
    • Year: 2018
  9. Machine learning for phishing detection and mitigation
    • Authors: M Alauthman, A Almomani, M Alweshah, W Alomoush, K Alieyan
    • Citations: 28*
    • Year: 2019
  10. Botnet Spam E-Mail Detection Using Deep Recurrent Neural Network
    • Authors: M ALAUTHMAN
    • Citations: 26
    • Year: 2020

 

Ms. Sharmila B S | Intrusion Detection and Prevention | Women Researcher Award

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Ms. Sharmila B S | Intrusion Detection and Prevention | Women Researcher Award

Assistant Professor at Intrusion Detection and Prevention, The National Institute of Engineering, Mysuru, India

Sharmila B S is currently pursuing a Ph.D. focusing on Network Security for IoT devices. Their research interests primarily lie in Network Security, Internet of Things (IoT), and Artificial Intelligence (AI). With 7 years of combined teaching and industry experience, Sharmila has also delivered talks on Python, AI, and IoT for technical talks and workshops.

Professional profiles

🎓Education:

Sharmila B S completed their academic qualifications as follows: a Ph.D. from the Department of ECE at the National Institute of Engineering, Mysuru, under Visweshwaraiah Technological University in 2018; an MTech in VLSI Design & Embedded Systems from SJCE, Mysore; and a BE in E&C from Kalpataru Institute of Technology, Tiptur, both under Visweshwaraiah Technological University, obtained in 2013 and 2011 respectively.

👩‍🏫Professional Experience:

Sharmila B S has professional experience as an Assistant Professor at the National Institute of Engineering, Mysuru, from July 25, 2016, to the present. Prior to this, they worked as a Lecturer at the same institute from July 27, 2015, to June 26, 2016. Before joining the National Institute of Engineering, Sharmila was an Assistant Professor at PESITM, Shivamogga, from July 21, 2014, to June 30, 2015. They also have internship experience at LG Soft India, Bangalore, from July 11, 2012, to December 31, 2013.

Subjects Taught:

Sharmila B S has taught a range of subjects, including Internet of Things, Data Structures using C++, Information Theory and Network Security, Embedded Systems, and Fundamentals of CMOS VLSI.

Publications:

“Intrusion Detection System using Naive Bayes algorithm” by BS Sharmila, R Nagapadma, published in the 2019 IEEE International WIE Conference on Electrical and Computer, with 24 citations in 2019.

“Comparison of time complexity in median filtering on multi-core architecture” by BS Sharmila, N Kaulgud, published in the 2017 3rd International Conference on Advances in Computing, Communication, with 2 citations in 2017.

“Multi Core DNN based IDS for Botnet Attacks using KPCA Reduction Techniques” by BS Sharmila, R Nagapadma, published in 2021.

“Design of memristor based multiplier” by N Jagan, U NS, S Kouser, published in the International Research Journal of Engineering and Technology, 6(1), 2019.

“Optimizing Deep Learning Networks for Edge Devices with an Instance of Skin Cancer and Corn Leaf Disease Dataset” by BS Sharmila, HS Santhosh, S Parameshwara, MS Swamy, WH Baig, published in SN Computer Science, 4(6), 793, 2023.

“QAE-IDS: DDoS anomaly detection in IoT devices using Post-Quantization Training” by BS Sharmila, R Nagapadma, published in Smart Science, 11(4), 774-789, 2023.

“Quantized autoencoder (QAE) intrusion detection system for anomaly detection in resource-constrained IoT devices using RT-IoT2022 dataset” by BS Sharmila, R Nagapadma, published in Cybersecurity, 6(1), 41, 2023.

“P‐DNN: Parallel DNN based IDS framework for the detection of IoT vulnerabilities” by S BS, R Nagapadma, published in Security and Privacy, e330, 2023.

“KNN classification using multi-core architecture for intrusion detection system” by BS Sharmila, R Nagapadma, published in the Communication and Computing Systems: Proceedings of the 2nd International Conference.

 

 

Qussai Yaseen | Android Malware Detection | Outstanding Scientist Award

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Qussai Yaseen | Android Malware Detection | Outstanding Scientist Award

Assoc Prof Dr Qussai Yaseen Ajman University, United Arab Emirates

He is a cybersecurity expert with a focus on malware detection, network security, and insider threats. With numerous publications in areas such as network security, insider threat mitigation, IoT security, machine learning applied to cybersecurity (security analytics), and spam filtering, he has established himself as a thought leader in the field. Additionally, he actively contributes to the academic community as a chair, TPC (Technical Program Committee) member, and reviewer for various events, conferences, and journals in cybersecurity and other information technology domains. His expertise and contributions play a vital role in advancing knowledge and practices in cybersecurity, making him a respected figure in both academia and industry.

Education:

He pursued his academic journey with dedication, earning his BSc. in Computer Science from Yarmouk University in Irbid, Jordan, from September 1998 to June 2002. Continuing his education, he completed his MSc. in Computer Science at Jordan University of Science and Technology in Irbid, Jordan, from September 2003 to June 2006. Building on his master’s degree, he went on to achieve a Ph.D. in Cybersecurity from the University of Arkansas in Fayetteville, AR, USA, between August 2008 and May 2012. His doctoral dissertation, titled “Mitigating Insider Threat in Relational Database Systems,” was conducted under the guidance of Prof. Brajendra Panda.

Profile:

Experience:

He has played a prominent role in curriculum development within the field of cybersecurity, serving as the Head of the Cybersecurity Program Committee at both Ajman University, UAE, in 2023, and Jordan University of Science and Technology, Jordan, in 2020. Additionally, he has contributed as a cybersecurity expert, serving as a member of the HEAC Committee for the Cybersecurity Accreditation Program at Petra University, Jordan, in 2020, and at Yarmouk University, Jordan, in 2019. Furthermore, he has showcased his expertise as a guest editor for the Special Issue on Big Data and Applications in the Cloud for the International Journal of Cloud Applications and Computing (IJCAC) in Volume 7: 4 Issues (2017). Through these leadership and editorial roles, he has demonstrated his commitment to advancing cybersecurity education and research on a global scale.

Awards and Honors:

He has a rich history of academic engagements, including serving as a Visiting Professor at the University of West Attica in Greece through the Erasmus+ Program in September 2018 and at the University of Piraeus, also in Greece, under the Erasmus+ Program in September 2017. Additionally, he contributed as a Visiting Researcher at the University of Minho in Portugal through the ERASMUS MUNDUS program from May to June 2017. Earlier in his career, he held a Graduate Assistantship at the University of Arkansas, USA, from August 2008 to May 2012, where he furthered his studies in cybersecurity. His academic achievements have been recognized with prestigious awards, including the Earl Beling Doctoral Fellowship from the College of Engineering at the University of Arkansas in 2011 and a Bachelor Education Fellowship at Yarmouk University in Jordan from 1998 to 2002.

Publications:

  1. An Android Malware Detection Approach Based on Static Feature Analysis Using Machine Learning Algorithms Cited By : 16, Published By : 2022
  2. A Novel Machine Learning Approach for Android Malware Detection Based on the Co-Existence of Features Cited By : 9, Published By : 2024
  3. A Comparative Analysis of Machine Learning Algorithms for Android Malware Detection Cited By : 8, Published By : 2023
  4. The Effect of the Ransomware Dataset Age on the Detection Accuracy of Machine Learning Models Cited By : 3, Published By : 2023
  5. A Context-Aware Android Malware Detection Approach Using Machine Learning  Cited By : 6, Published By : 2022
  6. A CNN and Image-Based Approach for Malware Analysis Cited By : 2, Published By : 2022
  7. Spam Email Detection Using Deep Learning Techniques Cited By : 93, Published By : 2021
  8. ReDroidDet: Android Malware Detection Based on Recurrent Neural Network Cited By : 28, Published By : 2021
  9. Machine learning for traffic analysis: a review Cited By : 50, Published By : 2020
  10. Detecting Spam Email with Machine Learning Optimized with Harris Hawks optimizer (HHO) Algorithm Cited By : 20, Published By : 2022