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A Cloud-Computing Middleware for Providing Proximity Information to Mobile Geo-Social Networks

DEPARTMENT:

Department of Computer Science

CONYTRIBUTOR / SPEAKER:

HU, Hai-bo

RELEASE DATE:

2012

LENGTH:

9 Minutes

VIDEO TYPE:

Other Videos

Mobile geo-social networking and location-based services are believed to be the killing application for the next generation mobile computing industry. However, privacy and security concern raised by both end-users and government authorities have been hindering the deployment and acceptance of these services. As recognised by the Presidents of China and the U.S. in their recent meeting in June 2013, cyber-security becomes a key priority in the administration. In addition, the recent incidents related to privacy or security breaches in IT domain, such as Snowden, PRISM programme and Heartbleed have given us strong signals that IT not only brought convenience to us as regular users, but also to parties on the opposite side. No one should take privacy for granted and blindly trust in any service providers.

This invention has brought the resolution of the issue of the privacy and security in IT. In particular, it gives an innovative quantitative solution on continuous proximity detection among peers without disclosing their location information to the server. It adopts the grid-and-hashing paradigm, and designs optimal grid overlay and multi-level dynamic grid schemes to increase the detection accuracy while saving the wireless bandwidth and CPU costs.

A Cloud-Computing Middleware for Providing Proximity Information to Mobile Geo-Social Networks

部門:

計算機科學系

講者:

HU, Hai-bo

發佈日期:

2012

影片長度:

9 分鐘

影片類型:

其他影片

Mobile geo-social networking and location-based services are believed to be the killing application for the next generation mobile computing industry. However, privacy and security concern raised by both end-users and government authorities have been hindering the deployment and acceptance of these services. As recognised by the Presidents of China and the U.S. in their recent meeting in June 2013, cyber-security becomes a key priority in the administration. In addition, the recent incidents related to privacy or security breaches in IT domain, such as Snowden, PRISM programme and Heartbleed have given us strong signals that IT not only brought convenience to us as regular users, but also to parties on the opposite side. No one should take privacy for granted and blindly trust in any service providers.

This invention has brought the resolution of the issue of the privacy and security in IT. In particular, it gives an innovative quantitative solution on continuous proximity detection among peers without disclosing their location information to the server. It adopts the grid-and-hashing paradigm, and designs optimal grid overlay and multi-level dynamic grid schemes to increase the detection accuracy while saving the wireless bandwidth and CPU costs.

A Cloud-Computing Middleware for Providing Proximity Information to Mobile Geo-Social Networks

部门:

计算机科学系

讲者:

HU, Hai-bo

发布日期:

2012

影片长度:

9 分钟

影片类型:

其他影片

Mobile geo-social networking and location-based services are believed to be the killing application for the next generation mobile computing industry. However, privacy and security concern raised by both end-users and government authorities have been hindering the deployment and acceptance of these services. As recognised by the Presidents of China and the U.S. in their recent meeting in June 2013, cyber-security becomes a key priority in the administration. In addition, the recent incidents related to privacy or security breaches in IT domain, such as Snowden, PRISM programme and Heartbleed have given us strong signals that IT not only brought convenience to us as regular users, but also to parties on the opposite side. No one should take privacy for granted and blindly trust in any service providers.

This invention has brought the resolution of the issue of the privacy and security in IT. In particular, it gives an innovative quantitative solution on continuous proximity detection among peers without disclosing their location information to the server. It adopts the grid-and-hashing paradigm, and designs optimal grid overlay and multi-level dynamic grid schemes to increase the detection accuracy while saving the wireless bandwidth and CPU costs.

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