Biblio
Multi-tag identification technique has been applied widely in the RFID system to increase flexibility of the system. However, it also brings serious tags collision issues, which demands the efficient anti-collision schemes. In this paper, we propose a Multi-target tags assignment slots algorithm based on Hash function (MTSH) for efficient multi-tag identification. The proposed algorithm can estimate the number of tags and dynamically adjust the frame length. Specifically, according to the number of tags, the proposed algorithm is composed of two cases. when the number of tags is small, a hash function is constructed to map the tags into corresponding slots. When the number of tags is large, the tags are grouped and randomly mapped into slots. During the tag identification, tags will be paired with a certain matching rate and then some tags will exit to improve the efficiency of the system. The simulation results indicate that the proposed algorithm outperforms the traditional anti-collision algorithms in terms of the system throughput, stability and identification efficiency.
The storage efficiency of hash codes and their application in the fast approximate nearest neighbor search, along with the explosion in the size of available labeled image datasets caused an intensive interest in developing learning based hash algorithms recently. In this paper, we present a learning based hash algorithm that utilize ordinal information of feature vectors. We have proposed a novel mathematically differentiable approximation of argmax function for this hash algorithm. It has enabled seamless integration of hash function with deep neural network architecture which can exploit the rich feature vectors generated by convolutional neural networks. We have also proposed a loss function for the case that the hash code is not binary and its entries are digits of arbitrary k-ary base. The resultant model comprised of feature vector generation and hashing layer is amenable to end-to-end training using gradient descent methods. In contrast to the majority of current hashing algorithms that are either not learning based or use hand-crafted feature vectors as input, simultaneous training of the components of our system results in better optimization. Extensive evaluations on NUS-WIDE, CIFAR-10 and MIRFlickr benchmarks show that the proposed algorithm outperforms state-of-art and classical data agnostic, unsupervised and supervised hashing methods by 2.6% to 19.8% mean average precision under various settings.
Video Steganography is an extension of image steganography where any kind of file in any extension is hidden into a digital video. The video content is dynamic in nature and this makes the detection of hidden data difficult than other steganographic techniques. The main motive of using video steganography is that the videos can store large amount of data in it. This paper focuses on security using the combination of hybrid neural networks and hash function for determining the best bits in the cover video to embed the secret data. For the embedding process, the cover video and the data to be hidden is uploaded. Then the hash algorithm and neural networks are applied to form the stego video. For the extraction process, the reverse process is applied and the secret data is obtained. All experiments are done using MatLab2016a software.
Fog computing has emerged due to the problem that it becomes difficult to store every data to the cloud system as the number of Internet of Things increases. In this fog computing, a vast amount of data generated from the Internet of Things is transmitted to the cloud system located at a remote place, and is processed by a fog computer such as a sensor or a router located nearby, so that only the necessary data is transmitted to the cloud system. However, the above-mentioned fog computer has some drawbacks like being shut down due to an attack by a malicious user in advance, and a method of processing when a fog computer is down or restored. In this paper we describe a fog computing with blockchain that enables fog computers to share transaction generated by processing transaction information of a device controlled by a blockchain method to a security and device control method of a fog computer utilizing the technology. Furthemore by using security properties of blockchain such as authentication, non-repudiation and data integrity, fog computing using blockchain has advantage of security comparing to previous Cloud and fog computing system using centralized database or P2P networks.
Mobile Ad-hoc Network (MANET) is an autonomous collection of mobile nodes and communicate among them in their radio range. It is an infrastructure less, bandwidth constraint multi-hop wireless network. A various routing protocol is being evolved for MANET routing and also provide security mechanism to avoid security threads. Dynamic Source Routing (DSR), one of the popular reactive routing protocols for MANET, establishes path between source to destination before data communication take place using route request (RREQ) and route reply (RREP) control messages. Although in [1] authors propose to prevent route diversion due to a malicious node in the network using group Diffie-Hellman (GDH) key management applied over source address, but if any intermediate trusted node start to misbehave then there is no prevention mechanism. Here in this paper, we applied Hash function scheme over destination address to identify the misbehaving intermediate node that can provide wrong destination address. The path information towards the destination sent by the intermediate node through RREP is exactly for the intended required destination or not, here we can identified according to our proposed algorithm and pretend for further data transmission. Our proposed algorithm proves the authenticity of the destination and also prevent from misbehaving intermediate nodes.
Existing data management and searching system for Internet of Things uses centralized database. For this reason, security vulnerabilities are found in this system which consists of server such as IP spoofing, single point of failure and Sybil attack. This paper proposes data management system is based on blockchain which ensures security by using ECDSA digital signature and SHA-256 hash function. Location that is indicated as IP address of data owner and data name are transcribed in block which is included in the blockchain. Furthermore, we devise data manegement and searching method through analyzing block hash value. By using security properties of blockchain such as authentication, non-repudiation and data integrity, this system has advantage of security comparing to previous data management and searching system using centralized database or P2P networks.
In the RFID technology, the privacy of low-cost tag is a hot issue in recent years. A new mutual authentication protocol is achieved with the time stamps, hash function and PRNG. This paper analyzes some common attack against RFID and the relevant solutions. We also make the security performance comparison with original security authentication protocol. This protocol can not only speed up the proof procedure but also save cost and it can prevent the RFID system from being attacked by replay, clone and DOS, etc..
Security of secret data has been a major issue of concern from ancient time. Steganography and cryptography are the two techniques which are used to reduce the security threat. Cryptography is an art of converting secret message in other than human readable form. Steganography is an art of hiding the existence of secret message. These techniques are required to protect the data theft over rapidly growing network. To achieve this there is a need of such a system which is very less susceptible to human visual system. In this paper a new technique is going to be introducing for data transmission over an unsecure channel. In this paper secret data is compressed first using LZW algorithm before embedding it behind any cover media. Data is compressed to reduce its size. After compression data encryption is performed to increase the security. Encryption is performed with the help of a key which make it difficult to get the secret message even if the existence of the secret message is reveled. Now the edge of secret message is detected by using canny edge detector and then embedded secret data is stored there with the help of a hash function. Proposed technique is implemented in MATLAB and key strength of this project is its huge data hiding capacity and least distortion in Stego image. This technique is applied over various images and the results show least distortion in altered image.
Lo et al. (2011) proposed an efficient key assignment scheme for access control in a large leaf class hierarchy where the alternations in leaf classes are more frequent than in non-leaf classes in the hierarchy. Their scheme is based on the public-key cryptosystem and hash function where operations like modular exponentiations are very much costly compared to symmetric-key encryptions and decryptions, and hash computations. Their scheme performs better than the previously proposed schemes. However, in this paper, we show that Lo et al.’s scheme fails to preserve the forward security property where a security class can also derive the secret keys of its successor classes ’s even after deleting the security class from the hierarchy. We aim to propose a new key management scheme for dynamic access control in a large leaf class hierarchy, which makes use of symmetric-key cryptosystem and one-way hash function. We show that our scheme requires significantly less storage and computational overheads as compared to Lo et al.’s scheme and other related schemes. Through the informal and formal security analysis, we further show that our scheme is secure against all possible attacks including the forward security. In addition, our scheme supports efficiently dynamic access control problems compared to Lo et al.’s scheme and other related schemes. Thus, higher security along with low storage and computational costs make our scheme more suitable for practical applications compared to other schemes.