Biblio

When biometric databases grow larger, a security breach or leak can affect millions. In order to protect against such a threat, the use of encryption is a natural choice. However, a biometric identification attempt then requires the decryption of a potential huge database, making a traditional approach potentially unfeasible. The use of selective JPEG2000 encryption can reduce the encryption’s computational load and enable a secure storage of biometric sample data. In this paper we will show that selective encryption of face biometric samples is secure. We analyze various encoding settings of JPEG2000, selective encryption parameters on the "Labeled Faces in the Wild" database and apply several traditional and deep learning based face recognition methods.

With the wide application of video information, the protection of video information from illegal access has been widely investigated recently. An efficient selective encryption scheme for high efficiency video coding (HEVC) based on hyperchaotic Lorenz system is proposed. Firstly, the hyperchaotic Lorenz system is discretized and the generated chaotic state values are converted into chaotic pseudorandom sequences for encryption. The important syntax elements in HEVC are then selectively encrypted with the generated stream cipher. The experimental results show that the encrypted video is highly disturbed and the video information cannot be recognized. Through the analysis of objective index results, it is shown that the scheme is both efficient and security.

Context-based adaptive binary arithmetic coding (CABAC) is the only entropy coding method in HEVC. According to statistics, CABAC encoders account for more than 25% of the high efficiency video coding (HEVC) coding time. Therefore, the improved CABAC algorithm can effectively improve the coding speed of HEVC. On this basis, a selective encryption scheme based on the improved CABAC algorithm is proposed. Firstly, the improved CABAC algorithm is used to optimize the regular mode encoding, and then the cryptographic algorithm is used to selectively encrypt the syntax elements in bypass mode encoding. The experimental results show that the encoding time is reduced by nearly 10% when there is great interference to the video information. The scheme is both safe and effective.

More and more organizations are today using the cloud for their business as a quite convenient alternative to in-house solutions for storing, processing, and managing data. Cloud-based solutions are then permeating almost all aspects of business organizations, resulting appealing also for functions that, already in-house, may result sensitive or security critical, and whose enforcement in the cloud requires then particular care. In this paper, we provide an approach for securely relying on cloud-based services for the enforcement of Internal Controls and Audit (ICA) functions for corporate governance. Our approach is based on the use of selective encryption and of tags to provide a level of self-protection to data and for enabling only authorized parties to access data and perform operations on them, providing privacy and integrity guarantees, as well as accountability and non-repudiation.

Biometric system security requires cryptographic protection of sample data under certain circumstances. We assess low complexity selective encryption schemes applied to JPEG2000 compressed iris data by conducting iris recognition on the selectively encrypted data. This paper specifically compares the effects of a recently proposed approach, i.e. applying selective encryption to normalised texture data, to encrypting classical sample data. We assess achieved protection level as well as computational cost of the considered schemes, and particularly highlight the role of segmentation in obtaining surprising results.

Mobile ad hoc network is a group of mobile nodes which have no centralized administrator. MANETs have dynamic topology since the nodes are moving. For this reason it is more prone to attacks that any node may be a misbehaving node. Every node acts as a router thereby it may lead the network with wrong routing. For these reasons MANETs have to be more protected than the wired networks. The mobile nodes will lavishly consume energy and so a security scheme that consumes less energy still provides ample protection to the messages have to be introduced. Here we propose an encryption scheme for the messages passing through MANET. The security scheme is based on selective encryption that is very robust, simple and with less computational capability.

The transmission of medical image data in an open network environment is subject to privacy issues including patient privacy and data leakage. In the past, image encryption and information-hiding technology have been used to solve such security problems. But these methodologies, in general, suffered from difficulties in retrieving original images. We present in this paper an algorithm to protect key regions in medical images. First, coefficient of variation is used to locate the key regions, a.k.a. the lesion areas, of an image; other areas are then processed in blocks and analyzed for texture complexity. Next, our reversible data-hiding algorithm is used to embed the contents from the lesion areas into a high-texture area, and the Arnold transformation is performed to protect the original lesion information. In addition to this, we use the ciphertext of the basic information about the image and the decryption parameter to generate the Quick Response (QR) Code to replace the original key regions. Consequently, only authorized customers can obtain the encryption key to extract information from encrypted images. Experimental results show that our algorithm can not only restore the original image without information loss, but also safely transfer the medical image copyright and patient-sensitive information.

We propose an approach for allowing data owners to trade their data in digital data market scenarios, while keeping control over them. Our solution is based on a combination of selective encryption and smart contracts deployed on a blockchain, and ensures that only authorized users who paid an agreed amount can access a data item. We propose a safe interaction protocol for regulating the interplay between a data owner and subjects wishing to purchase (a subset of) her data, and an audit process for counteracting possible misbehaviors by any of the interacting parties. Our solution aims to make a step towards the realization of data market platforms where owners can benefit from trading their data while maintaining control.

With the wide use of smart device made huge amount of information arise. This information needed new methods to deal with it from that perspective big data concept arise. Most of the concerns on big data are given to handle data without concentrating on its security. Encryption is the best use to keep data safe from malicious users. However, ordinary encryption methods are not suitable for big data. Selective encryption is an encryption method that encrypts only the important part of the message. However, we deal with uncertainty to evaluate the important part of the message. The problem arises when the important part is not encrypted. This is the motivation of the paper. In this paper we propose security framework to secure important and unimportant portion of the message to overcome the uncertainty. However, each will take a different encryption technique for better performance without losing security. The framework selects the important parts of the message to be encrypted with a strong algorithm and the weak part with a medium algorithm. The important of the word is defined according to how its origin frequently appears. This framework is applied on amazon EC2 (elastic compute cloud). A comparison between the proposed framework, the full encryption method and Toss-A-Coin method are performed according to encryption time and throughput. The results showed that the proposed method gives better performance according to encryption time, throughput than full encryption.

Multimedia transmission in wireless multimedia sensor networks is often energy constraints. In practice the bit rate resulting from all the multimedia digitization formats are substantially larger than the bit rates of transmission channels that are available with the networks associated with these applications. For the purpose of efficient of storage and transmission of the content, the popular compression technique MPEG4/H.264 has been made used. To achieve better coding efficiency video streaming protocols MPEG4/H.264 uses several techniques which is increasing the complexity involved in computation at the encoder prominently for wireless sensor network devices having lesser power abilities. In this paper we propose energy consumption reduction framework for transmission in wireless networks so that well-balanced quality of service (QoS) in multimedia network can be maintained. The experiment result demonstrate that the effectiveness of the proposed approach in energy efficiency in wireless sensor network where the energy is the critical parameter.

Selective encryption designates a technique that aims at scrambling a message content while preserving its syntax. Such an approach allows encryption to be transparent towards middle-box and/or end user devices, and to easily fit within existing pipelines. In this paper, we propose to apply this property to a real-time diffusion scenario - or broadcast - over a RTP session. The main challenge of such problematic is the preservation of the synchronization between encryption and decryption. Our solution is based on the Advanced Encryption Standard in counter mode which has been modified to fit our auto-synchronization requirement. Setting up the proposed synchronization scheme does not induce any latency, and requires no additional bandwidth in the RTP session (no additional information is sent). Moreover, its parallel structure allows to start decryption on any given frame of the video while leaving a lot of room for further optimization purposes.