Seidenberg School of CSIS
Information Technology NY
- @New York City
Goldstein Academic Center 320
New York City
Thu 1:00pm-6:00pm(by appointment)
PhD, Pennsylvania State University at University Park, 1989
MS, University of Tunis, 1979
Computer Information Systems
A.D. , University of Tunis, 1975
Mathematics and Physics
Awards and Honors
The Country of Tunisia,
- Gold Medal for Great Contributions in IS Security
Pace University, School of Computer Science and Information System, December 31, 1998 - CSIS Excellence in Research Award
NULL, June 6, 1998 - Award in Excellence in Research & Scholarship, Pace University
Data Processing Management Association, December 31, 1989 - Data Processing Management Award
NULL, December 31, 1982 - Fulbright Scholarship
CII-Honeywell Bull of Paris, December 31, 1979 - Scholarship
Raggad, B. (2020, January (1st Quarter/Winter) 01). A Security-policy Driven Distributed Incident Response Generator. International Scientific Survey Journal. Vol Vol 2 (Issue 6)
Raggad, B. The State of Big Data.
Raggad, B. Sound Big Data Decision Support Despite its V's Article:Sound Big Data Decision Support Despite its V's.
Raggad, B. & Tappert, C.
Security Risk Learning in Cybersecurity: Evidential Reasoning Model.
Mansouri, S., , . & , . (2017, October (4th Quarter/Autumn) 1). Evidential Modeling for Telemedicine Continual Security. International Journal of Computer Science and Network Security. Vol 6 (Issue 5) , pages 559-564. http://ijcsn.org/publications.html
Mansouri, S. (2017, October (4th Quarter/Autumn) 1). Risk of Telemedicine Infeasibility: An Evidential Reasoning Approach. International Journal of Medical Research & Health Sciences. Vol 6 (Issue 10) http://ijmrhs.com/abstract/risk-of-telemedicine-infeasibility-an-evidential-reasoning-approach-13146.html
Raggad, B. Intelligent Decision Support Capabilities for a Law Enforcement GIS. http://aisel.aisnet.org/siggis2016/2/
Mansouri, S. (2016, October (4th Quarter/Autumn) 30). Enforcing Patient Privacy Assurance Policy: A Privacy Violation Detection and Response System. Vol 2016 http://journals.indexcopernicus.com/
Mansouri, S. Telemedicine: Distributed Decision Support with Partial Compatibility Evidence. Vol 2016 http://seinforms.org
, . & Akermi, A. Evidential Reasoning in Real-time Monitoring of Computing Systems. Vol 2016 http://cisse.info
Raggad, B. Autonomic Computing and Policy Based Systems:.
Raggad, B. Decision Support Treating Partial Compatibility Evidence in Telemedicine. Vol 2015 http://inase.org
Raggad, B. Towards a Science of Cyber Security: A Security Self-Security Generator. Vol 2014
(2018, March 24).
Predictive Analytics in Big Data.
International Conference on Technology, Engineering & Mathematics, Kenitra, Morocco.
(2018, February 22).
Security Risk Learning in Cybersecurity Model.
DSI, Wilmington NC.
Raggad, B. (2017, October 4). Southeast INFORMS. Actioning Big Data. INFORMS, Myrtle Beach, SC.
Raggad, B. (2017, March 9). IIAB 2017. Risk-driven Corporate Security Defense. IIAB, Miami.
Raggad, B. (2016, December 9). GIS. Intelligent Decision Support Capabilities for a Law Enforcement GIS. AIS, Dublin, Ireland.
Management Information Systems (Decision Support Systems); Software Engineering (Information Systems Development); Artificial Intelligence (Approximate Reasoning);.
Grants, Sponsored Research and Contracts
Deep Data: Invisible Analytics
Raggad, B. January 2017 - December 2019. Scholarly Research Papers , Pace University , $3,045.00. Funded. On Internet we only access about 1% of existing Internet data. The rest is called deep data. We need what we call Invisible Analytics to get to some of it. If we are successful in doing this, it is just unbelievable the gains we get. For example, a university can use Invisible Analytics to understand student retention problems and can make corrections to maintain and improve its retention rate. A company can understand the reasons behind its customer attrition and what is behind its business value retention deficiencies. Invisible analytics will be the tool set needed to maintain its customers and enhance their loyalty which will secure its business value generation capabilities. Another example would be to use Invisible Analytics to understand our healthcare deficiencies and act to correct it. Unfortunately, we still spending billions of dollars on data capture from the Internet or from business operational systems to create boundless big data depots that we cannot dig it to produce valuable decision support information. We still have no clear approach to design the platform needed to start designing the analytical tools to generate decision support information to enhance business value in our educational systems, our healthcare systems, and our economy. This research project intends to design a computing platform for the development of Invisible Analytics tools to get into deep data and to explore our big data depots to produce valuable decision support information. We have completed the quantitative analysis and we were successful in building the belief structures needed to construct the needed probabilistic framework for the purpose of building the analytical tools for expanded data analytics. We also have tested our models in telemedicine to detect e-patient attrition and mitigate its impacts. We are currently working to extend the testing to other areas including student retention.
Computational Intelligence for Modelling, Control and Automation
CORS: Canadian Society of Operations Research
Decision Science Institute
E-commerce Security Society
Federal Information Systems Security Educators' Association (FISSEA)
FRANCORO - Francophones de Recherche Opérationnelle
FRANCORO II Conference[Member, Program Committee - 2000 Conference]
IATF: Information Assurance Technical Framework (National Security Agency)
International Association of Business Disciplines
International Association of Computer Information Systems
JOPT - Des Journées de l'Optimisation (Optimization Days of Canada)
Literati Club, Great Britain
NE-DSI: Northeastern Decision Science Institute
SAM - Society for Advances in Management
Int Academy of Bus and Pub Adm Deciplines[Editor of Journal]
The National Colloquium for Information Systems Security Education[Reviewer]
Association of Information Systems[Member]
Information Systems Audit And Control Association[Member]
Seidenberg Dean Performance Evaluation Committee
Desc: Reconfirm the dean
Committee's Key Accomplishments: Evaluate the performance of the dean. Collect evidence from surveying and interviewing student, faculty, and staff.
Pace University, Computer Science & Information Systems
Desc: Travel to provide assistance to developing countries reviewing their Technology Management programs and develop effective strategies to protect against cyber terrorism: about 22 days of lectures, advising, and interventions.