Public-Key Encryption with Delegated Search

In public-key setting, Alice encrypts email with public key of Bob, so that only Bob will be able to learn contents of email. Consider scenario when computer of Alice is infected and unbeknown to Alice it also embeds malware into message. Bob's company, Carol, cannot scan his email for malicious content as it is encrypted so burden is on Bob to do scan. This is not efficient. We construct mechanism that enables Bob to provide trapdoors to Carol such that Carol, given encrypted data and malware signature, is able to check whether encrypted data contains malware signature, without decrypting it. We refer to this mechanism as Public-Key Encryption with Delegated Search SPKE.\ud \ud We formalize SPKE and give construction based on ElGamal public-key encryption (PKE). proposed scheme has ciphertexts which are both searchable and decryptable. This property of scheme is crucial since entity can search entire content of message, in contrast to existing searchable public-key encryption schemes where search is done only in metadata part. We prove in standard model that scheme is ciphertext indistinguishable and trapdoor indistinguishable under Symmetric External Diffie-Hellman (sxdh) assumption. We prove also ciphertext one-wayness of scheme under modified Computational Diffie-Hellman (mcdh) assumption. We show that our PKEDS scheme can be used in different applications such as detecting encrypted malwares and forwarding encrypted emails

Understanding Android Obfuscation Techniques: A Large-Scale Investigation in the Wild

In this paper, we seek to better understand Android obfuscation and depict a holistic view of the usage of obfuscation through a large-scale investigation in the wild. In particular, we focus on four popular obfuscation approaches: identifier renaming, string encryption, Java reflection, and packing. To obtain the meaningful statistical results, we designed efficient and lightweight detection models for each obfuscation technique and applied them to our massive APK datasets (collected from Google Play, multiple third-party markets, and malware databases). We have learned several interesting facts from the result. For example, malware authors use string encryption more frequently, and more apps on third-party markets than Google Play are packed. We are also interested in the explanation of each finding. Therefore we carry out in-depth code analysis on some Android apps after sampling. We believe our study will help developers select the most suitable obfuscation approach, and in the meantime help researchers improve code analysis systems in the right direction