State of the art – Part 1 Xin Jin Multimedia Security State of the art – Part 1 Xin Jin

OutLine Emerging Cryptographic Challenges in Image And Video Processing –ICIP 2012 Real-time privacy-preserving moving object detection in the cloud. ACM MM 2013 An Efficient Image Homomorphic Encryption Scheme with Small Ciphertext Expansion ACM MM2013

Emerging Cryptographic Challenges in Image And Video Processing System Add-ons Deeply embedded Attacker Outside Inside

Applications paid-for video services biometric systems …… Secure Face Recognition Secure Fingerprints Recognition ……

Applications

Challenges The utility and limitations of cryptography are not very well known to the community, which hampers the widespread consideration of cryptographic solutions for security problems in image and video processing Cryptographic operations are often computationally expensive. Efficient usage of cryptographic protocols is therefore imperative. Certain cryptographic techniques cause iphertext expansion of two orders of magnitude, such as public-key encryption of image pixels. Efficient data packing strategies and operations are then needed.

云计算 同态加密 Kuan-Yu Chu, Yin-Hsi Kuo, and Winston H. Hsu. 2013. Real-time privacy-preserving moving object detection in the cloud. In Proceedings of the 21st ACM international conference on Multimedia (MM '13). ACM

云计算 同态加密 With the advance of cloud computing, growing applications have been migrating to the cloud for its robustness and scalability. However, sending raw data to the cloud-based service providers will generally risk our privacy; especially for cloud-based surveillance system, where privacy is one of the major concerns as continuously recording daily life. Thus, privacy-preserving intelligent analytics are in dire needs. In this preliminary research, we investigate real-time privacy-preserving moving object detection in the encrypted cloud-based surveillance videos. Moving object detection is one of the core techniques and can further enable other applications (e.g., object tracking, action recognition, etc.). One possible approach is using homomorphic encryption which provides corresponding operations between unencrypted and encrypted data. However, homomorphic encryption is impractical in real case because of formidable computations and bulky storage consumption. In this paper, we propose an efficient and secure encryption framework, which entails real-time analytics (e.g., moving object detection) in encrypted video streams. Experiments confirm that the proposed method can achieve similar accuracy as detection on original raw frames.

An Efficient Image Homomorphic Encryption Scheme with Small Ciphertext Expansion Secure signal processing (SSP), also referred to as signal processing in the encrypted domain (s.p.e.d.) privacy-preserving face recognition privacy-preserving fingercode authentication privacy-preserving electrocardiogram (ECG) classification

An Efficient Image Homomorphic Encryption Scheme with Small Ciphertext Expansion the homomorphic cryptosystems, are able to keep certain algebraic structures from the plaintext space to the ciphertext space. Partially homomorphic cryptosystems keep the relation of addition or multiplication between plaintexts and ciphertexts, such Fully homomorphic cryptosystems permit to compute additions and multiplications homomorphically, and therefore allows the computation of any polynomials in the encrypted domain. Probabilistic cryptosystems, one can obtain different ciphertexts after different encryption procedures, no matter the input plaintexts are identical or not.

two data encryption methods widely used in the field of s.p.e.d.. Element-Wise Encryption Scheme The Packing Method

New Direction- Xin Jin Homomorphic Encryption based Privacy-preserving Image Processing in Encrypted Domain (with Cloud Computing) Content based Image Retrieval in Encrypted Domain

KeyWords Homomorphic Encryption Privacy-preserving Multimedia (Image/Video) Processing Encrypted Domain Cloud Computing Big Data