Disruption and Deception in Crowdsourcing: Towards a Crowdsourcing Risk Framework

While crowdsourcing has become increasingly popular among organizations, it also has become increasingly susceptible to unethical and malicious activities. This paper discusses recent examples of disruptive and deceptive efforts on crowdsourcing sites, which impacted the confidentiality, integrity, and availability of the crowdsourcing efforts’ service, stakeholders, and data. From these examples, we derive an organizing framework of risk types associated with disruption and deception in crowdsourcing based on commonalities among incidents. The framework includes prank activities, the intentional placement of false information, hacking attempts, DDoS attacks, botnet attacks, privacy violation attempts, and data breaches. Finally, we discuss example controls that can assist in identifying and mitigating disruption and deception risks in crowdsourcing

Architectural model for crowdsourcing for human security threats situation information

Crowdsourcing for Human Security Threats Situation Information and Response System (CHSTSIRS) is proposed in this paper to report Human Security (HS) threats. Crowds are used as HS threats surveillance/ human sensor that provide real-time information about a threatened area and receive appropriate response or feedback as a preventive measure through appropriate HS agency. With an ever-increasing popularity of mobile applications in our day-to-day activities, it shows that its deployment to HS threatened situation is highly desirable. The model deployed an architecture using php and mysql for the server-end and Android SDK for the mobile aspect of the system using a developed algorithm. An android application is preferred in this system, because of the push notifications and flexibility of the platform. However, Google Cloud Messaging (GCM) for android was used in the delivery of threat/disaster feedbacks from HS agencies; it also allows the HS agencies to send data from the server to crowd and also receives feedback immediately. In conclusion, it shows that android-based CHSTSIRS could be implemented, and it worked efficientlyKeywords: Human security, Crowdsourcing, Threats, Situation Information, Agency, Google, Cloud Messagin