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1. CEIVE: Combating Caller ID Spoofing on 4G Mobile Phones Via Callee-Only Inference and Verification

   https://doi.org/10.1145/3241539.3241573  

   Deng, Haotian; Wang, Weicheng; Peng, Chunyi (January 2018, Proceedings of the 24th Annual International Conference on Mobile Computing and Networking)

   Caller ID spoofing forges the authentic caller identity, thus making the call appear to originate from another user. This seemingly simple attack technique has been used in the growing telephony frauds and scam calls, resulting in substantial monetary loss and victim complaints. Unfortunately, caller ID spoofing is easy to launch, yet hard to defend; no effective and practical defense solutions are in place to date. In this paper, we propose CEIVE (Callee-only inference and verification), an effective and practical defense against caller ID spoofing. It is a victim callee only solution without requiring additional infrastructure support or changes on telephony systems. We formulate the design as an inference and verification problem. Given an incoming call, CEIVE leverages a callback session and its associated call signaling observed at the phone to infer the call state of the other party. It further compares with the anticipated call state, thus quickly verifying whether the incoming call comes from the originating number. We exploit the standardized call signaling messages to extract useful features, and devise call-specific verification and learning to handle diversity and extensibility. We implement CEIVE on Android phones and test it with all top four US mobile carriers, one landline and two small carriers. It shows 100% accuracy in almost all tested spoofing scenarios except one special, targeted attack case. 

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2. Nascent: Tackling Caller-ID Spoofing in 4G Networks via Efficient Network-Assisted Validation

   https://doi.org/10.1109/INFOCOM.2019.8737567  

   Sheoran, Amit; Fahmy, Sonia; Peng, Chunyi; Modi, Navin (April 2019, IEEE INFOCOM 2019 - IEEE Conference on Computer Communications)

   Caller-ID spoofing deceives the callee into believing a call is originating from another user. Spoofing has been strategically used in the now-pervasive telephone fraud, causing substantial monetary loss and sensitive data leakage. Unfortunately, caller-ID spoofing is feasible even when user authentication is in place. State-of-the-art solutions either exhibit high overhead or require extensive upgrades, and thus are unlikely to be deployed in the near future. In this paper, we seek an effective and efficient solution for 4G (and conceptually 5G) carrier networks to detect (and block) caller-ID spoofing. Specifically, we propose Nascent, Network-assisted caller ID authentication, to validate the caller-ID used during call setup which may not match the previously-authenticated ID. Nascent functionality is split between data-plane gateways and call control session functions. By leveraging existing communication interfaces between the two and authentication data already available at the gateways, Nascent only requires small, standard-compatible patches to the existing 4G infrastructure. We prototype and experimentally evaluate three variants of Nascent in traditional and Network Functions Virtualization (NFV) deployments. We demonstrate that Nascent significantly reduces overhead compared to the state-of-the-art, without sacrificing effectiveness. 

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3. ANONYCALL: Enabling Native Private Calling in Mobile Networks

   Yu, Hexuan; Zhang, Chaoyu; Xiao, Yang; Keromytis, Angelos D; Hou, Y Thomas; Lou, Wenjing (February 2026, Network and Distributed System Security (NDSS) Symposium 2026)

   Mobile Network Operators (MNOs) are known to leak or sell subscribers’ sensitive information, including geolocation and communication histories. Anonymous mobile user authentication methods, such as [48] (USENIX Sec’21), [55] (NDSS’24), [13] (CCS’24), [54] (S&P’25), enable users to access mobile networks without revealing long-term identifiers like phone numbers or Subscription Permanent Identifiers (SUPI). However, the absence of identity transparency and location awareness poses significant challenges to implementing the above anonymous access methods in real-world mobile networks, particularly for supporting essential functions such as call routing, usage measurement, and charging. To overcome these limitations, we propose ANONYCALL, a privacy-preserving call management architecture that supports anonymous mobile network access while enabling two essential functions: anonymous callee discovery and usage-based charging. The anonymous callee discovery function incorporates an out-of-band authentication mechanism to securely share temporary callee identifiers with the caller, allowing the latter to establish native calls without obtaining the callee’s permanent information. The usage-based charging function introduces an anonymous and accountable balance credential that enables accurate charging and prevents double-spending while preserving mobile user anonymity. Fully compatible with existing mobile networks, ANONYCALL introduces minimal overhead, adding less than 200 ms to call establishment. Evaluations with smartphones and standard calling systems demonstrate its practicality, offering a viable solution for privacy-preserving yet functional mobile communication. 

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4. Generating and Analyzing Program Call Graphs using Ontology

   https://doi.org/10.1109/ProTools56701.2022.00008  

   Dorta, Ethan; Yan, Yonghong; Liao, Chunhua (November 2022, 2022 IEEE/ACM Workshop on Programming and Performance Visualization Tools (ProTools))

   Call graph or caller-callee relationships have been used for various kinds of static program analysis, performance analysis and profiling, and for program safety or security analysis such as detecting anomalies of program execution or code injection attacks. However, different tools generate call graphs in different formats, which prevents efficient reuse of call graph results. In this paper, we present an approach of using ontology and resource description framework (RDF) to create knowledge graphs for specifying call graphs to facilitate the construction of full-fledged and complex call graphs of computer programs, realizing more interoperable and scalable program analyses than conventional approaches. We create a formal ontology-based specification of call graph information to capture concepts and properties of both static and dynamic call graphs so different tools can collaboratively contribute to more comprehensive analysis results. Our experiments show that ontology enables merging of call graphs generated from different tools and flexible queries using a standard query interface. 

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5. UCBlocker: Unwanted Call Blocking Using Anonymous Authentication

   Du, Changlai; Yu, Hexuan; Xiao, Yang; Hou, Y. Thomas; Keromytis, Angelos D.; Lou, Wenjing (August 2023, 32nd USENIX Security Symposium (USENIX Security 23))

   Telephone users are receiving more and more unwanted calls including spam and scam calls because of the transfer-without-verification nature of global telephone networks, which allows anyone to call any other numbers. To avoid unwanted calls, telephone users often ignore or block all incoming calls from unknown numbers, resulting in the missing of legitimate calls from new callers. This paper takes an end-to-end perspective to present a solution to block unwanted calls while allowing users to define the policies of acceptable calls. The proposed solution involves a new infrastructure based on anonymous credentials, which enables anonymous caller authentication and policy definition. Our design decouples caller authentication and call session initiation and introduces a verification code to interface and bind the two processes. This design minimizes changes to telephone networks, reduces latency to call initiation, and eliminates the need for a call-time data channel. A prototype of the system is implemented to evaluate its feasibility. 

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