SOFT COMPUTING APPROACHES IN FORENSICS: AN INTELLIGENT SYSTEM APPROACH

It has been increasingly difficult to ignore the prevailing situation of crime, law & order and dominantly terrorism acts in Pakistan and the simultaneous use of mobile phone and other related equipment in the criminal activities. The prevailing situation motivated us to study digital forensics of mobile phones using soft computing techniques. In this thesis, we have developed intelligent system approach to explore the causes and effects of this menace keeping in view mobile information system, service providers and cyber laws of Pakistan. The soft computing approaches are useful to study the patterns emerging in forensic crimes prevailing in developing countries especially in Pakistan. We have studied mobile related crimes such as law & order, home land security and street crimes and presented a review on ICT and mobile phone crimes in Pakistan. In this research, we have investigated forensic crimes technologies in mobile phone system concentrating on essential mobile phone technology, crime evidence, crime investigation framework and related laws in developed and developing countries especially in Pakistan. I have explored soft computing methods / techniques using fuzzy logic, probabilistic reasoning, Bayesian network and rough set theory with the approach of intelligent systems and artificial intelligence. In fuzzy logic, I have dealt with subjective/ expert approach to analyze forensic crimes especially related with mobile phones. I have discussed fuzzy time series approach in detail to study mobile phone crimes over time with examples of rough set theory discussed in detail for developing information system related with forensic crimes especially related with the use of mobile phones and suggested the use of a rule based system when knowledge on attributes related with mobile phone crimes is imprecise. I found that rough set theory is very much helpful in taking decisions and improving information/ evidence on mobile phone crimes. I have also used Naive Bayesian approach for classification of crimes and study the approach on the available dataset on Pakistan. I have studied the location based approach for mobile phone crimes using geo-fencing technique with special emphasis on data available from service providers and called it tower data analysis. Tower data analysis is done in detail and found it very much helpful in detecting criminals and their networks especially in the context of Pakistan. I have also concentrated on objective approach on customer side of the mobile phone use and studied in detail call details record (CDR) data available/provided by service providers with special permission and suggested an abstract data model of CDR which may be extended to data warehouse technology. The approach will be helpful for behavior analysis of mobile users and especially criminals while using mobile phones and suggested that such data marts/ data warehouse should be developed by the government authorities along with the information available from service providers. I have provided suggestions and directions for future work in the context of soft computing for developing framework of evidence in Pakistan. We also feel that there is a need to improve the government agencies' record which should be maintained independent of service providers CDR data and Location based data of mobile users with their activities. This will be helpful for investigation, evidence analysis without dependence on the service providers' data. In the last, I feel that this effort is the very first attempt to study forensic crimes related to mobile and therefore need more attention and more research work on ICT to overcome the misuse of the technologies to reduce crimes and improve law & order, homeland security for the country and a common citizen of Pakistan. There is a good coordination and cooperation among the researchers and the consultants of law enforcement agencies which has culminated into this work and hope that this will open new venues for research and development in this area in the future.