SBIR Phase II: A Robust Caller-ID Alternative for Securing Telephony Based Transactions

SBIR 第二阶段：用于保护基于电话的交易的强大来电显示替代方案

• 批准号: 1256637
• 负责人: Vijay Balasubramaniyan
• 金额: $ 50万
• 依托单位: Telineage, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-04-01 至 2015-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1256637&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Robust; Caller

The innovation in this project comes from the novel call audio analysis techniques that can be used to create a fingerprint of the source of a telephone call. Such fingerprints can reveal valuable information about the call source, including the type of the calling device (landline, Voice-over IP or mobile), its geographical location and the networks over which the call audio may have been transported prior to it reaching the called party. To detect potentially fraudulent calls in real-time with such fingerprints, this proposal plans to extend the identification of the geography of a call source and the creation of an active call analyzer that performs audio analysis in real-time. The focus of this Phase II project is on exploring design options for an active call analyzer; including accuracy, scalability and timeliness tradeoffs and its integration in call center infrastructures. The call analyzer will also be used to build a phone fraud intelligence service that proactively detects phone numbers used for committing fraud. Such a service, including mechanisms for sharing of intelligence with partners and customers, can help secure the telephony channel from a variety of attacks.The broader impact and commercialization potential of this project can be seen readily from the observation that phone fraud is already a serious problem for multiple sectors, including banking, healthcare and even law enforcement. Also, because fraudulent calls are already responsible for considerable financial loss, customer agents in call centers are asking multiple knowledge-based questions to authenticate a caller. This leads to higher costs for call handling and also degrades customer experience. A successful active call analyzer solution that can automatically generate a risk score for caller authentication will have broad impact because the entire service sector relies on call centers for customer contact and it could reduce costs and improve customer experience. The project will also enable Pindrop to play a leadership role in organizing the broader community to launch a phone anti-fraud alliance similar to the anti-phishing working group. The thought leadership provided by such a group will be necessary to define the telephony security challenges and approaches for addressing them. Again, this will ensure broad impact of the project across several industries.

该项目的创新来自于新颖的通话音频分析技术，可用于创建电话来源的指纹。这种指纹可以揭示关于呼叫源的有价值的信息，包括呼叫设备的类型（固定电话、IP语音或移动的）、其地理位置以及呼叫音频在到达被叫方之前可能已经通过其传输的网络。为了利用这种指纹实时检测潜在的欺诈性呼叫，该提案计划扩展对呼叫源地理位置的识别，并创建一个实时执行音频分析的主动呼叫分析器。该项目第二阶段的重点是探索主动呼叫分析器的设计方案，包括准确性、可扩展性和及时性的权衡，以及其在呼叫中心基础设施中的集成。呼叫分析器还将用于建立电话欺诈情报服务，主动检测用于实施欺诈的电话号码。这种服务包括与合作伙伴和客户共享情报的机制，可以帮助保护电话渠道免受各种攻击。从观察到电话欺诈已经是包括银行、医疗保健甚至执法部门在内的多个部门的严重问题，可以很容易地看出该项目的更广泛影响和商业化潜力。此外，由于欺诈性呼叫已经造成了相当大的经济损失，呼叫中心的客户代理正在询问多个基于知识的问题来验证呼叫者。这导致呼叫处理成本更高，也降低了客户体验。一个成功的主动呼叫分析器解决方案可以自动生成呼叫者身份验证的风险评分，这将产生广泛的影响，因为整个服务行业都依赖于呼叫中心进行客户联系，它可以降低成本并改善客户体验。该项目还将使Pindrop在组织更广泛的社区方面发挥领导作用，以发起类似于反钓鱼工作组的电话反欺诈联盟。这样一个小组提供的思想领导对于确定电话安全挑战和解决这些挑战的方法是必要的。 同样，这将确保该项目在多个行业的广泛影响。