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Sanaa Kaddoura holds a Ph.D. in computer science from Beirut Arab University, Lebanon. She is currently employed as an assistant professor of information security at the Department of Computing and Applied Technology, College of Technological Innovation, Zayed University, United Arab Emirates. She is a fellow of Higher Education Academy, Advance HE (FHEA) since 2019. In addition to her research interests in cybersecurity, social networks, machine learning and natural language processing, she is an active researcher in higher education teaching and learning related to enhancing the quality of instructional delivery to facilitate students' acquirement of skills and smooth transition to the workplace.
The immense improvements in the latest internet inventions encouraged the adaptation of technology within the healthcare sector. The healthcare systems storing highly sensitive information can be targeted by attackers aiming to insert, delete, or modify the data stored. These malicious activities may cause severe damage to the database accessibility and lead to catastrophic long-term harm to the patients’ health. The adaptation of the most advanced security paradigm does not guarantee full protection. It is possible that the attack is not directly detected. This highlights the need to assess the widespread damage scale before starting the repair of the inconsistent medical database. Within the scope of the damage assessment and recovery, several matrices-based, cluster-based, and graph-based models were introduced. The objective of this work is to correctly assess the damage and recover the database within a suitable time frame and efficient utilization of memory. We use a lightweight structure based on hash tables to gauge the incurred damage and recuperate quickly following an attack. The presented approach is contrasted with other existing ones and demonstrated superior performance.
Ramzi A. Haraty; Bahia Boukhari; Sanaa Kaddoura. An Effective Hash-Based Assessment and Recovery Algorithm for Healthcare Systems. Arabian Journal for Science and Engineering 2021, 1 -14.
AMA StyleRamzi A. Haraty, Bahia Boukhari, Sanaa Kaddoura. An Effective Hash-Based Assessment and Recovery Algorithm for Healthcare Systems. Arabian Journal for Science and Engineering. 2021; ():1-14.
Chicago/Turabian StyleRamzi A. Haraty; Bahia Boukhari; Sanaa Kaddoura. 2021. "An Effective Hash-Based Assessment and Recovery Algorithm for Healthcare Systems." Arabian Journal for Science and Engineering , no. : 1-14.
With the increase in the number of users on social networks, sentiment analysis has been gaining attention. Sentiment analysis establishes the aggregation of these opinions to inform researchers about attitudes towards products or topics. Social network data commonly contain authors’ opinions about specific subjects, such as people’s opinions towards steps taken to manage the COVID-19 pandemic. Usually, people use dialectal language in their posts on social networks. Dialectal language has obstacles that make opinion analysis a challenging process compared to working with standard language. For the Arabic language, Modern Standard Arabic tools (MSA) cannot be employed with social network data that contain dialectal language. Another challenge of the dialectal Arabic language is the polarity of opinionated words affected by inverters, such as negation, that tend to change the word’s polarity from positive to negative and vice versa. This work analyzes the effect of inverters on sentiment analysis of social network dialectal Arabic posts. It discusses the different reasons that hinder the trivial resolution of inverters. An experiment is conducted on a corpus of data collected from Facebook. However, the same work can be applied to other social network posts. The results show the impact that resolution of negation may have on the classification accuracy. The results show that the F1 score increases by 20% if negation is treated in the text.
Sanaa Kaddoura; Maher Itani; Chris Roast. Analyzing the Effect of Negation in Sentiment Polarity of Facebook Dialectal Arabic Text. Applied Sciences 2021, 11, 4768 .
AMA StyleSanaa Kaddoura, Maher Itani, Chris Roast. Analyzing the Effect of Negation in Sentiment Polarity of Facebook Dialectal Arabic Text. Applied Sciences. 2021; 11 (11):4768.
Chicago/Turabian StyleSanaa Kaddoura; Maher Itani; Chris Roast. 2021. "Analyzing the Effect of Negation in Sentiment Polarity of Facebook Dialectal Arabic Text." Applied Sciences 11, no. 11: 4768.
In the current Internet of things era, all companies shifted from paper-based data to the electronic format. Although this shift increased the efficiency of data processing, it has security drawbacks. Healthcare databases are a precious target for attackers because they facilitate identity theft and cybercrime. This paper presents an approach for database damage assessment for healthcare systems. Inspired by the current behavior of COVID-19 infections, our approach views the damage assessment problem the same way. The malicious transactions will be viewed as if they are COVID-19 viruses, taken from infection onward. The challenge of this research is to discover the infected transactions in a minimal time. The proposed parallel algorithm is based on the transaction dependency paradigm, with a time complexity O((M+NQ+N^3)/L) (M = total number of transactions under scrutiny, N = number of malicious and affected transactions in the testing list, Q = time for dependency check, and L = number of threads used). The memory complexity of the algorithm is O(N+KL) (N = number of malicious and affected transactions, K = number of transactions in one area handled by one thread, and L = number of threads). Since the damage assessment time is directly proportional to the denial-of-service time, the proposed algorithm provides a minimized execution time. Our algorithm is a novel approach that outperforms other existing algorithms in this domain in terms of both time and memory, working up to four times faster in terms of time and with 120,000 fewer bytes in terms of memory.
Sanaa Kaddoura; Ramzi Haraty; Karam Al Kontar; Omar Alfandi. A Parallelized Database Damage Assessment Approach after Cyberattack for Healthcare Systems. Future Internet 2021, 13, 90 .
AMA StyleSanaa Kaddoura, Ramzi Haraty, Karam Al Kontar, Omar Alfandi. A Parallelized Database Damage Assessment Approach after Cyberattack for Healthcare Systems. Future Internet. 2021; 13 (4):90.
Chicago/Turabian StyleSanaa Kaddoura; Ramzi Haraty; Karam Al Kontar; Omar Alfandi. 2021. "A Parallelized Database Damage Assessment Approach after Cyberattack for Healthcare Systems." Future Internet 13, no. 4: 90.
Lecture-based classes became an old strategy of teaching even in higher education. Education now focuses on student-centered strategies that actively engage students in their learning and how teacher can design classes to facilitate learning process. This paper presents some practices for teaching in higher education.
Sanaa Kaddoura; Rima Grati. Promoting Teaching Practices in IT Higher Education. Proceedings of the 21st Annual Conference on Information Technology Education 2020, 1 .
AMA StyleSanaa Kaddoura, Rima Grati. Promoting Teaching Practices in IT Higher Education. Proceedings of the 21st Annual Conference on Information Technology Education. 2020; ():1.
Chicago/Turabian StyleSanaa Kaddoura; Rima Grati. 2020. "Promoting Teaching Practices in IT Higher Education." Proceedings of the 21st Annual Conference on Information Technology Education , no. : 1.
No one can deny that information technology courses can be an excellent initiative for increasing the awareness of environmental and health problems. Hence, information technology instructors play a critical role in spreading awareness of green technology and reinforcing sustainability. The Introduction to Information Technology (IIT) course contains many topics that can be directed in an intelligent way to spread awareness about sustainability. In this paper, we suggest a detailed curriculum for the IT course that converts a standard curriculum into a green one. The goal of this curriculum is to produce a new generation that is aware enough about the role of technology in our life and its impact on the environment. The course topics will be the answers to the following questions. First, how to avoid the negative impact of technology on health and the environment. Second, how to decrease the negative impact that cannot be avoided or find a solution for it. Finally, what are the alternative green computing techniques that can be used to increase sustainability? The proposed curriculum should involve the instructor and the students. Both should collaborate in a set of activities that will give society a generation with high awareness of green computing and sustainability.
Sanaa Kaddoura. Developing a Green Curriculum for Introduction to Information Technology Course. Plant-Microbes-Engineered Nano-particles (PM-ENPs) Nexus in Agro-Ecosystems 2020, 49 -52.
AMA StyleSanaa Kaddoura. Developing a Green Curriculum for Introduction to Information Technology Course. Plant-Microbes-Engineered Nano-particles (PM-ENPs) Nexus in Agro-Ecosystems. 2020; ():49-52.
Chicago/Turabian StyleSanaa Kaddoura. 2020. "Developing a Green Curriculum for Introduction to Information Technology Course." Plant-Microbes-Engineered Nano-particles (PM-ENPs) Nexus in Agro-Ecosystems , no. : 49-52.
Ramzi Haraty; Sanaa Kaddoura; Ahmed Zekri. Recovery of business intelligence systems: Towards guaranteed continuity of patient centric healthcare systems through a matrix-based recovery approach. Telematics and Informatics 2018, 35, 801 -814.
AMA StyleRamzi Haraty, Sanaa Kaddoura, Ahmed Zekri. Recovery of business intelligence systems: Towards guaranteed continuity of patient centric healthcare systems through a matrix-based recovery approach. Telematics and Informatics. 2018; 35 (4):801-814.
Chicago/Turabian StyleRamzi Haraty; Sanaa Kaddoura; Ahmed Zekri. 2018. "Recovery of business intelligence systems: Towards guaranteed continuity of patient centric healthcare systems through a matrix-based recovery approach." Telematics and Informatics 35, no. 4: 801-814.
One of the critical concerns in the current era is information security. Companies are sharing vast online critical data, which exposes their databases to malicious attacks. When protection techniques fail to prevent an attack, recovery is needed. Database recovery is not a straightforward procedure, since the transactions are highly interconnected. Traditional recovery techniques do not consider the interconnection between transactions because this information is not saved anywhere in the log file. Thus, they rollback all the transactions starting from the detected malicious transaction to the end of the log file. Hence, both affected and benign transactions will be rolled back, which is a waste of time. This paper presents an algorithm that works efficiently to assess the damage caused in the database by malicious transaction and recovers it. The proposed algorithm keeps track of the transactions that read from one another and store this information in a single matrix. The experimental results prove that the algorithm is faster than any other existing algorithm in this domain.
Ramzi Haraty; Sanaa Kaddoura; Ahmed Zekri. Transaction Dependency Based Approach for Database Damage Assessment Using a Matrix. International Journal on Semantic Web and Information Systems 2017, 13, 74 -86.
AMA StyleRamzi Haraty, Sanaa Kaddoura, Ahmed Zekri. Transaction Dependency Based Approach for Database Damage Assessment Using a Matrix. International Journal on Semantic Web and Information Systems. 2017; 13 (2):74-86.
Chicago/Turabian StyleRamzi Haraty; Sanaa Kaddoura; Ahmed Zekri. 2017. "Transaction Dependency Based Approach for Database Damage Assessment Using a Matrix." International Journal on Semantic Web and Information Systems 13, no. 2: 74-86.
Databases are always the main target of attackers because they contain the critical data of organizations. Although prevention techniques are available, the history of system break-ins guarantees that there is no foolproof technique that totally eliminates security loopholes in a computer system. Hence, efficient damage assessment and recovery techniques are needed. Traditional methods require scanning the entire log from the point of attack to the end which is a slow procedure. In this paper, we present an efficient damage assessment and recovery algorithm to recover the database from malicious transactions. The algorithm is based on data dependency and uses a single matrix that will be later used during recovery.
Ramzi Haraty; Sanaa Kaddoura; Ahmed Zekri. Information Warfare: Fighting Back Through the Matrix. 2015 IEEE Symposium Series on Computational Intelligence 2015, 449 -454.
AMA StyleRamzi Haraty, Sanaa Kaddoura, Ahmed Zekri. Information Warfare: Fighting Back Through the Matrix. 2015 IEEE Symposium Series on Computational Intelligence. 2015; ():449-454.
Chicago/Turabian StyleRamzi Haraty; Sanaa Kaddoura; Ahmed Zekri. 2015. "Information Warfare: Fighting Back Through the Matrix." 2015 IEEE Symposium Series on Computational Intelligence , no. : 449-454.
In a distributed mobile e-health care system, e-health service providers exchange data on the fly in response to user queries without any centralized control. Local databases in e-health service providers might be intercepted during the exchange of data and read by intruders; and malicious transactions may damage data that is highly confidential. In this case any centralized control for securing data cannot be assumed to protect confidential data. Therefore, securing health information from malicious attacks has become a major concern. Although prevention techniques are available, the history of system break-ins guarantees that there is no foolproof technique that totally eliminates security loopholes in a computer system. Hence, efficient damage assessment and recovery techniques are needed. Traditional methods require scanning the entire log from the point of attack to the end which is a slow procedure. In this paper, we present an efficient damage assessment and recovery algorithm to recover the database from malicious transactions. The algorithm is based on data dependency and uses a single matrix. The results of this work prove that our algorithm performs better than the other algorithms in both the damage assessment and the recovery stages.
Sanaa Kaddoura; Ramzi A. Haraty; Ahmed Zekri; Mehedi Masud. Tracking and Repairing Damaged Healthcare Databases Using the Matrix. International Journal of Distributed Sensor Networks 2015, 11, 1 .
AMA StyleSanaa Kaddoura, Ramzi A. Haraty, Ahmed Zekri, Mehedi Masud. Tracking and Repairing Damaged Healthcare Databases Using the Matrix. International Journal of Distributed Sensor Networks. 2015; 11 (11):1.
Chicago/Turabian StyleSanaa Kaddoura; Ramzi A. Haraty; Ahmed Zekri; Mehedi Masud. 2015. "Tracking and Repairing Damaged Healthcare Databases Using the Matrix." International Journal of Distributed Sensor Networks 11, no. 11: 1.
Databases are always the main target of attackers because they contain the critical data of organizations. Although prevention techniques are available, the history of system break-ins guarantees that there is no foolproof technique that totally eliminates security loopholes in a computer system. Hence, efficient damage assessment and recovery techniques are needed. Traditional methods require scanning the entire log from the point of attack to the end which is a slow procedure. In this paper, we present an efficient damage assessment and recovery algorithm to recover the database from malicious transactions. The algorithm is based on data dependency and uses a single matrix.
Sanaa Kaddoura. Information matrix: Fighting back using a matrix. 2015 IEEE/ACS 12th International Conference of Computer Systems and Applications (AICCSA) 2015, 1 -6.
AMA StyleSanaa Kaddoura. Information matrix: Fighting back using a matrix. 2015 IEEE/ACS 12th International Conference of Computer Systems and Applications (AICCSA). 2015; ():1-6.
Chicago/Turabian StyleSanaa Kaddoura. 2015. "Information matrix: Fighting back using a matrix." 2015 IEEE/ACS 12th International Conference of Computer Systems and Applications (AICCSA) , no. : 1-6.