By 2011, the world will be 10 times more instrumented than it was in 2006. Internet connected devices will leap from 500 Million to 1 Trillion. Approximately 70% of the digital universe is created by individuals, but enterprises are responsible for 85% of the security, privacy, reliability, and compliance.
Increasingly, the proliferation of data-generating sensors and mobile computing devices, and the emergence of new forms of communication such as social networking, are driving unprecedented growth in the collection, storage and management of all types of data.
Not surprisingly, this phenomenon has sparked growing demand for the ability to extract intelligence from these massive mountains of information—intelligence that can enable organizations to improve their decision-making and run their businesses more effectively and efficiently.
With this capacity to rapidly sift thru data and gain new insights comes a significant challenge and responsibility when it comes to personal information, or information that relates to identifiable individuals: how to enable the exchange and analysis of data, while protecting privacy.
IBM has long recognized the importance of information privacy and led by example in its own privacy polices and practices: the company was the first multinational to adopt a global privacy policy in the late 1960s, and continued that leadership as recently as 2005 when it was the first company to address genetic privacy.
But policies and practices are not enough on their own to address the privacy challenges of an increasingly smarter planet. Thoughtfully-designed technologies can play a key role here, part of a paradigm that some are calling Privacy by Design.
As the world becomes smarter and more interconnected, the capacity to rapidly sift through data to gain new insights brings with it a significant challenge and responsibility when it comes to personal information. How do we enable the exchange and analysis of data, while protecting privacy? IBM, which in the 1960s because the first multinational to adopt a global privacy policy and in 2005 was the first to address genetic privacy, has long recognized the importance of information privacy. Leading by example in its own privacy polices and practices, IBM has also received many patents for inventions that support our commitment to privacy leadership.
For example, an IBM Researcher has solved a thorny mathematical problem that has confounded scientists since the invention of public-key encryption several decades ago. The breakthrough, called “privacy homomorphism,” or “fully homomorphic encryption,” makes possible the deep and unlimited analysis of encrypted information — data that has been intentionally scrambled — without sacrificing confidentiality.
IBM’s solution, formulated by IBM Researcher Craig Gentry, uses a mathematical object called an “ideal lattice,” and allows people to fully interact with encrypted data in ways previously thought impossible. With the breakthrough, computer vendors storing the confidential, electronic data of others will be able to fully analyze data on their clients’ behalf without expensive interaction with the client, and without seeing any of the private data. With Gentry’s technique, the analysis of encrypted information can yield the same detailed results as if the original data was fully visible to all.
Using the solution could help strengthen the business model of “cloud computing,” where a computer vendor is entrusted to host the confidential data of others in a ubiquitous Internet presence. It might better enable a cloud computing vendor to perform computations on clients’ data at their request, such as analyzing sales patterns, without exposing the original data.
Other potential applications include enabling filters to identify spam, even in encrypted email, or protecting information contained in electronic medical records. The breakthrough might also one day enable computer users to retrieve information from a search engine with more confidentiality
