SBIR Phase I: St. Gabriel's ROBOCALL Blocker

这项提议的更广泛的影响/商业影响是减少电信欺诈。根据美国联邦通信委员会的数据，去年美国人收到了大约260亿个所谓的机器人电话，2019年3月，创下了每月50亿个机器人电话的新纪录。联邦贸易委员会(FTC)报告称，该机构2019年将收到500多万起关于机器人通话的投诉，比2018年增长30%。机器人电话诈骗者依赖于相对便宜的大规模工作的技术，新的计划正变得越来越聪明，构成越来越大的威胁。值得注意的是，机器人呼叫者利用人工智能(AI)、合成语音(所谓的“深度虚假”)和来电显示欺骗，每年造成超过220亿美元的欺诈。这个拟议的项目将致力于通过在电信设备级别进行过滤来减少机器人通话和相关欺诈。拟议的创新利用新的去中心化分类帐技术和区块链加密、实时记录解析和实时机器算法来阻止机器人通话并减少连接延迟。拟议中的创新的目标是大幅减少欺诈性电话的数量。此SBIR建议侧重于设备级别的过滤；最初应用于阻止机器人呼叫，但可能与其他安全应用程序相关。这项创新利用了区块链的共享存储和内存，在“不信任环境”中运行的能力(由于缺乏跨电信网络在集中式机器人通话列表上的协作)，以及区块链加密、人工智能和机器学习方面的进步，以及记录和机器算法的实时解析，以阻止机器人通话并减少连接延迟。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial impact of this proposal is to reduce fraud in telecommunications. Americans received approximately 26 billion so-called "robocalls" last year, and in March 2019, a new monthly record of 5 billion robocalls was reached, according to the FCC. The Federal Trade Commission (FTC) reports the agency is on pace to receive 5+ million complaints about robocalls in 2019, a 30% increase over 2018. Robocalling scammers rely on relatively cheap technology that works on a large scale, and new schemes are getting smarter and pose a growing threat. Significantly, robocallers leverage artificial intelligence (A.I.), synthesized voice (so-called "deep fakes"), and caller ID spoofing, creating fraud of over $22 billion annually. This proposed project will work to reduce robocalls and associated fraud by filtering at the telecommunications device level.The proposed innovation leverages new decentralized ledger technology with blockchain encryption, real-time parsing of records, and real-time machine algorithms to block robocalls and reduce connection delays. The goal of the proposed innovation is to dramatically reduce the volume of fraudulent phone calls. This SBIR proposal focuses on filtering at the device level; initially applied to prevent robocalls, but potentially relevant for other secure applications. The innovation leverages blockchain's shared storage and memory, ability to operate in a "trustless environment" (due to lack of cross-telecom network collaboration on centralized robocall lists), as well as advances in blockchain encryption, artificial intelligence and machine learning, and real-time parsing of records and machine algorithms to block robocalls and reduce connection delays.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.