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Haque, Shaheryar Ehsan I, Saleem, Shahzad.  2020.  Augmented reality based criminal investigation system (ARCRIME). 2020 8th International Symposium on Digital Forensics and Security (ISDFS). :1—6.
Crime scene investigation and preservation are fundamentally the pillars of forensics. Numerous cases have been discussed in this paper where mishandling of evidence or improper investigation leads to lengthy trials and even worse incorrect verdicts. Whether the problem is lack of training of first responders or any other scenario, it is essential for police officers to properly preserve the evidence. Second problem is the criminal profiling where each district department has its own method of storing information about criminals. ARCRIME intends to digitally transform the way police combat crime. It will allow police officers to create a copy of the scene of crime so that it can be presented in courts or in forensics labs. It will be in the form of wearable glasses for officers on site whereas officers during training will be wearing a headset. The trainee officers will be provided with simulations of cases which have already been resolved. Officers on scene would be provided with intelligence about the crime and the suspect they are interviewing. They would be able to create a case file with audio recording and images which can be digitally sent to a prosecution lawyer. This paper also explores the risks involved with ARCRIME and also weighs in their impact and likelihood of happening. Certain contingency plans have been highlighted in the same section as well to respond to emergency situations.
Sudozai, M. A. K., Saleem, Shahzad.  2018.  Profiling of secure chat and calling apps from encrypted traffic. 2018 15th International Bhurban Conference on Applied Sciences and Technology (IBCAST). :502–508.
Increased use of secure chat and voice/ video apps has transformed the social life. While the benefits and facilitations are seemingly limitless, so are the asscoiacted vulnerabilities and threats. Besides ensuring confidentiality requirements for common users, known facts of non-readable contents over the network make these apps more attractive for criminals. Though access to contents of cryptograhically secure sessions is not possible, network forensics of secure apps can provide interesting information which can be of great help during criminal invetigations. In this paper, we presented a novel framework of profiling the secure chat and voice/ video calling apps which can be employed to extract hidden patterns about the app, information of involved parties, activities of chatting, voice/ video calls, status indications and notifications while having no information of communication protocol of the app and its security architecture. Signatures of any secure app can be developed though our framework and can become base of a large scale solution. Our methodology is considered very important for different cases of criminal investigations and bussiness intelligence solutions for service provider networks. Our results are applicable to any mobile platform of iOS, android and windows.