Biblio

Cloud computing has included an essential part of its industry and statistics garage is the main service provided, where a huge amount of data can be stored in a virtual server. Storing data in public platforms may be vulnerable to threats. Consequently, the obligation of secure usage and holistic backup of statistics falls upon the corporation providers. Subsequently, an affordable and compliant mechanism of records auditing that permits groups to audit the facts stored in shared clouds whilst acting quick and trouble- unfastened healing might be a fairly sought-after cloud computing task concept. There is a lot of advantage in growing this domain and there is considerable precedence to follow from the examples of dropbox, google power among others.

Digital signature is more appropriate for message security in Wireless Sensors Networks (WSNs), which is energy-limited, than costly encryption. However, it meets with difficulty of verification when a large amount of message-signature pairs swarm into the central node in WSNs. In this paper, a scalable group testing algorithm based on Latin square (SGTLS) is proposed, which focus on both batch verification of signatures and invalid signature identification. To address the problem of long time-delay during individual verification, we adapt aggregate signature for batch verification so as to judge whether there are any invalid signatures among the collection of signatures once. In particular, when batch verification fails, an invalid signature identification algorithm is presented based on scalable OR-checking matrix of Latin square, which can adjust the number of group testing by itself with the variation of invalid signatures. Comprehensive analyses show that SGTLS has more advantages, such as scalability, suitability for parallel computing and flexible design (Latin square is popular), than other algorithm.

Internet of Things (IoT) devices use different types of media and protocols to communicate to Internet, but security is compromised since the devices are not using encryption, authentication and integrity. Virtual Private Network of Things (VPNoT) is a new technology designed to create end to end encrypted tunnels for IoT devices, in this case, the VPNoT device is based on OpenVPN that provides confidentiality and integrity, also based on Raspberry Pi as the hardware and Linux as the operating system, both provide connectivity using different types of media to access Internet and network management. IoT devices and sensors can be connected to the VPNoT device so an encrypted tunnel is created to an IoT Server. VPNoT device uses a profile generated by the server, then all devices form a virtual private network (VPN). VPNoT device can act like a router when necessary and this environment works for IPv6 and IPv4 with a great advantage that OpenVPN traverses NAT permitting private IoT servers be accessible to the VPN. The annual cost of the improvement is about \$455 USD per year for 10 VPNoT devices.

This paper proposes a digital image compression-encryption scheme based on the theory of singular value decomposition, multiple chaos and Beta function, which uses SVD to compress the digital image and utilizes three way protections for encryption viz. logistic and Arnold map along with the beta function. The algorithm has three advantages: First, the compression scheme gives the freedom to a user so that one can select the desired compression level according to the application with the help of singular value. Second, it includes a confusion mechanism wherein the pixel positions of image are scrambled employing Cat Map. The pixel location is shuffled, resulting in a cipher text image that is safe for communication. Third the key is generated with the help of logistic map which is nonlinear and chaotic in nature therefore highly secured. Fourth the beta function used for encryption is symmetric in nature which means the order of its parameters does not change the outcome of the operation, meaning faithful reconstruction of an image. Thus, the algorithm is highly secured and also saving the storage space as well. The experimental results show that the algorithm has the advantages of faithful reconstruction with reasonable PSNR on different singular values.

In order to meet the requirements of secure start-up of embedded devices, this paper designs a secure and trusted circuit to realize the secure and trusted start-up of the system. This paper analyzes the principle and method of the circuit design, and verifies the preset information of the embedded device before the start of the embedded device, so as to ensure that the start process of the embedded device is carried out according to the predetermined way, and then uses the security module to measure the integrity of the data in the start process, so as to realize a trusted embedded system. The experimental results show that the security module has stronger security features and low latency. The integrity measurement is implemented in the trusted embedded system to realize the safe startup of embedded devices.

Zero- Knowledge Proof is a cryptographic protocol exercised to render privacy and data security by securing the identity of users and using services anonymously. It finds numerous applications; authentication is one of them. A Zero-Knowledge Proof-based authentication system is discussed in this paper. Advanced Encryption Standard (AES) and Secure Remote Password (SRP) protocol have been used to design and build the ZKP based authentication system. SRP is a broadly used Password Authenticated Key Exchange (PAKE) protocol. The proposed method overcomes several drawbacks of traditional and commonly used authentication systems such as a simple username and plaintext password-based system, multi-factor authentication system and others.

How to prevent the computer system from being interfered by external factors and maintain a strong working state is a problem that needs to be solved at present. At present, encryption and network security defense systems are important technical means of security defense. Based on this research background, the paper proposes an AES data encryption scheme in the Hadoop big data environment. The AES algorithm performs several rounds of plaintext encryption through the steps of round key addition, byte replacement, row displacement, column confusion, etc. Under the MapReduce architecture, the plaintext data is divided into multiple data fragments. The Map function is responsible for the AES algorithm encryption operation, and the Reduce function Combine encrypted data information. Finally, the paper designs a computer network security defense system that can actively discover the security threats in the network and effectively prevent them, so as to ensure the normal and safe operation of the network. At the same time, we use the encryption algorithm on the computer network security defense system. Experimental research has proved that this method can safely transmit network data packets. With the increase of computing cluster nodes, its encryption transmission efficiency continues to improve. This solution not only solves the problem of computer network data security encryption, but also realizes the parallel transmission of encrypted data in the information age.

The Session Initiation Protocol (SIP) is the principal signalling protocol in Voice over IP (VoIP) systems, responsible for initialising, terminating, and maintaining sessions amongst call parties. However, the problem with the SIP protocol is that it was not designed to be secure by nature as the HTTP digest authentication used in SIP is insecure, making it vulnerable to a variety of attacks. The current solutions rely on several standardised encryption protocols, such as TLS and IPsec, to protect SIP registration messages. However, the current centralised solutions do not scale well and cause algorithm overload when encoding and decoding SIP messages. In trying to rectify this issue, we propose in this paper a blockchain-based lightweight authentication mechanism, which involves a decentralised identity model to authenticate the SIP client to the SIP server. Our mechanism uses a smart contract on the Ethereum blockchain to ensure trust, accountability and preserves user privacy. We provided a proof-of-concept implementation to demonstrate our work. Further analysis of this approach's usability, mainly CPU and memory usage, was conducted comparing to IPsec and TLS. Then we discussed our system's security and presented a security analysis. Our analysis proves that our approach satisfies the SIP protocol security requirements.

Network-on-Chip (NoC) fulfills the communication requirements of modern System-on-Chip (SoC) architectures. Due to the resource-constrained nature of NoC-based SoCs, it is a major challenge to secure on-chip communication against eavesdropping attacks using traditional encryption methods. In this paper, we propose a lightweight encryption technique using chaffing and winnowing (C&W) with all-or-nothing transform (AONT) that benefits from the unique NoC traffic characteristics. Our experimental results demonstrate that our proposed encryption technique provides the required security with significantly less area and energy overhead compared to the state-of-the-art approaches.

Nowadays , cloud -based technology has been enlarged depends on the human necessities in the world. A lot of technologies is discovered that serve the people in different ways of cloud -based security and best resource allocation. Cloud-based technology is the essential factor to the resources like hardware, software for effective resource utilization . The securing applications enabled security mechanism enables the vital role for cloud -based web security through the secured password. The violation of data by the unauthorized access of users concerns many web developers and application owners . Web security enables the cloud-based password management system that illustrates the data storage and the web passwords access through the "Cloud framework". Web security, End-to-end passwords , and all the browser -based passwords could belong to the analysis of web security . The aim is to enhance system security. Thus, sensitive data are sustained with security and privacy . In this paper , the proposed Password Management via cloud-based web security gets to attain . An efficient Double Layer Password Encryption (DLPE ) algorithm to enable the secured password management system . Text -based passwords continue to be the most popular method of online user identification . They safeguard internet accounts with important assets against harmful attempts on passwords. The security of passwords is dependent on the development of strong passwords and keeping them from being stolen by intruders . The proposed DLPE algorithm perceived the double - layer encryption system as an effective security concern. When the data user accesses the user Login , the OTP generates via mail /SMS , and the original message is encrypted using public key generation. Then the text of data gets doubly encrypted through the cloud framework . The private key is used to decipher the cipher text . If the OTP gets matched , the text is to be decrypted over the text data . When double encryption happens , the detection of data flaws, malicious attacks , application hackers gets reduced and the strong password enabled double-layer encryption attained the secured data access without any malicious attackers . The data integrity , confidentiality enabled password management . The ability to manage a distributed systems policy like the Double Layer Password encryption technique enables password verification for the data used to highly secure the data or information.

Currently, data security issues are remaining as a major concern during digital communication. A large amount of crucial data is transmitted through the communication channel. There are many cryptographic algorithms available, which are used for providing data security during communication and storage process. However, the data needs to be decrypted for performing operations, which may lead to elevation of the privilege of data. The pin or passwords used for decryption of data can be easily identified using a brute force attack. This leads to losing the confidentiality of crucial data to an unauthorized user. In the proposed system, a combination of Homomorphic and Honey encryption is used to improve data confidentiality and user authentication problems. Thus, the system provides better data security for the issues related to outsourced databases.

Cost-effective and efficient sequencing technologies have resulted in massive genomic data availability. To compute on a large-scale genomic dataset, it is often required to outsource the dataset to the cloud. To protect data confidentiality, data owners encrypt sensitive data before outsourcing. Outsourcing enhances data owners to eliminate the storage management problem. Since genome data is large in volume, secure execution of researchers query is challenging. In this paper, we propose a method to securely perform count query on datasets containing genotype, phenotype, and numeric data. Our method modifies the prefix-tree proposed by Hasan et al. [1] to incorporate numerical data. The proposed method guarantees data privacy, output privacy, and query privacy. We preserve the security through encryption and garbled circuits. For a query of 100 single-nucleotide polymorphism (SNPs) sequence, we achieve query execution time approximately 3.5 minutes in a database of 1500 records. To the best of our knowledge, this is the first proposed secure framework that addresses heterogeneous biomedical data including numeric attributes.

The advance of smart eHealthcare and cloud computing techniques has propelled an increasing number of healthcare centers to outsource their healthcare data to the cloud. Meanwhile, in order to preserve the privacy of the sensitive information, healthcare centers tend to encrypt the data before outsourcing them to the cloud. Although the data encryption technique can preserve the privacy of the data, it inevitably hinders the query functionalities over the outsourced data. Among all practical query functionalities, the similarity range query is one of the most popular ones. However, to our best knowledge, many existing studies on the similarity range query over outsourced data still suffer from the efficiency issue in the query process. Therefore, in this paper, aiming at improving the query efficiency, we propose an efficient privacy-preserving similarity range query scheme based on the precomputed distance technique. In specific, we first introduce a pre-computed distance based similarity range query (PreDSQ) algorithm, which can improve the query efficiency by precomputing some distances. Then, we propose our privacy-preserving similarity query scheme by applying an asymmetric scalar-product-preserving encryption technique to preserve the privacy of the PreDSQ algorithm. Both security analysis and performance evaluation are conducted, and the results show that our proposed scheme is efficient and can well preserve the privacy of data records and query requests.

With the increasing popularity of geo-positioning technologies and mobile Internet, spatial keyword data services have attracted growing interest from both the industrial and academic communities in recent years. Meanwhile, a massive amount of data is increasingly being outsourced to cloud in the encrypted form for enjoying the advantages of cloud computing while without compromising data privacy. Most existing works primarily focus on the privacy-preserving schemes for either spatial or keyword queries, and they cannot be directly applied to solve the spatial keyword query problem over encrypted data. In this paper, we study the challenging problem of Privacy-preserving Boolean Range Query (PBRQ) over encrypted spatial databases. In particular, we propose two novel PBRQ schemes. Firstly, we present a scheme with linear search complexity based on the space-filling curve code and Symmetric-key Hidden Vector Encryption (SHVE). Then, we use tree structures to achieve faster-than-linear search complexity. Thorough security analysis shows that data security and query privacy can be guaranteed during the query process. Experimental results using real-world datasets show that the proposed schemes are efficient and feasible for practical applications, which is at least ×70 faster than existing techniques in the literature.

With the proliferation of cloud services, cloud-based image retrieval services enable large-scale image outsourcing and ubiquitous image searching. While enjoying the benefits of the cloud-based image retrieval services, critical privacy concerns may arise in such services since they may contain sensitive personal information. In this paper, we propose an efficient and Privacy-Preserving Image Retrieval scheme with Key Switching Technique (PPIRS). PPIRS utilizes the inner product encryption for measuring Euclidean distances between image feature vectors and query vectors in a privacy-preserving manner. Due to the high dimension of the image feature vectors and the large scale of the image databases, traditional secure Euclidean distance comparison methods provide insufficient search efficiency. To prune the search space of image retrieval, PPIRS tailors key switching technique (KST) for reducing the dimension of the encrypted image feature vectors and further achieves low communication overhead. Meanwhile, by introducing locality sensitive hashing (LSH), PPIRS builds efficient searchable indexes for image retrieval by organizing similar images into a bucket. Security analysis shows that the privacy of both outsourced images and queries are guaranteed. Extensive experiments on a real-world dataset demonstrate that PPIRS achieves efficient image retrieval in terms of computational cost.

In light of the progress achieved by the technology sector in the areas of internet speed and cloud services development, and in addition to other advantages provided by the cloud such as reliability and easy access from anywhere and anytime, most data owners find an opportunity to take advantage of the cloud to store data. However, data owners find a challenge that was and is still facing them in the field of outsourcing, which is protecting sensitive data from leakage. Researchers found that partitioning data into partitions, based on data sensitivity, can be used to protect data from leakage and to increase performance by storing the partition, which contains sensitive data in an encrypted form. In this paper, we review the methods used in designing partitions and dividing data approaches. A hybrid data partitioning approach is proposed to improve these techniques. We consider the frequency attack types used to guess the sensitive data and the most important properties that must be available in order for the encryption to be strong against frequency attacks.

Tor is a famous routing overlay network based on the Onion multi-layered encryption to support communication anonymity in a threat model in which some network nodes are malicious. However, Tor does not provide any protection against the global passive adversary. In this threat model, an idea to obtain recipient anonymity, which is enough to have relationship anonymity, is to hide the recipient among a sufficiently large anonymity set. However, this would lead to high latency both in the set-up phase (which has a quadratic cost in the number of involved nodes) and in the successive communication. In this paper, we propose a way to arrange a Tor circuit with a tree-like topology, in which the anonymity set consists of all its nodes, whereas set-up and communication latency depends on the number of the sole branch nodes (which is a small fraction of all the nodes). Basically, the cost goes down from quadratic to linear. Anonymity is obtained by applying a broadcast-based technique for the forward message, and cover traffic (generated by the terminal-chain nodes) plus mixing over branch nodes, for the response.

Security plays a paradigmatic role in the area of networking. The main goal of security is to protect these networks which contains confidential data against various kinds of attacks. By changing parameters like key size, increasing the rounds of iteration and finally using confusion box as the S-box, the strength of the cryptographic algorithms can be incremented. By using the Data Encryption Standard (DES), the images can be secured with the help of Dynamic S-boxes. Each of these 8 S-boxes contain 64 elements. Each row contains elements in the range 0–15 and are unique. Our proposed system generates these S-boxes dynamically depending on the key. The evaluation of this Dynamic S-box and DES shows much fruitful results over factors like Non-linearity, Strict Avalanche criterion, Balance, memory and time required for implementation using images.

The impact of malware grows for IT (information technology) systems day by day. The number, the complexity, and the cost of them increase rapidly. While researchers are developing new and better detection algorithms, attackers are also evolving malware to fail the current detection techniques. Therefore malware detection becomes one of the most challenging tasks in cyber security. To increase the performance of the detection techniques, researchers benefit from different approaches. But some of them might cost a lot both in time and hardware resources. This situation puts forward fast and cheap detection methods. In this context, static analysis provides these utilities but it is important to keep detection accuracy high while reducing resource consumption. Opcodes (operational codes) are commonly used in static analysis but sometimes feature extraction from opcodes might be difficult since an opcode sequence might have a great length. Furthermore, most of the malware developers use obfuscation and encryption techniques to avoid detection methods based on static analysis. This kind of malware is called packed malware and according to common belief, packed malware should be either unpacked or analyzed dynamically in order to detect them. In this study, a graph-based malware detection method has been proposed to overcome these problems. The proposed method relies on obtaining the opcode graph of every executable file in the dataset and using them for future extraction. In this way, the proposed method reaches up to 98% detection accuracy. In addition to the accuracy rate, the proposed method makes it possible to detect packed malware without the need for unpacking or dynamic analysis.

Code-reuse attacks pose a threat to embedded devices since they are able to defeat common security defenses such as non-executable stacks. To succeed in his code-reuse attack, the attacker has to gain knowledge of some or all of the instructions of the target firmware/software. In case of a bare-metal firmware that is protected from being dumped out of a device, it is hard to know the running instructions of the target firmware. This consequently makes code-reuse attacks more difficult to achieve. This paper shows how an attacker can gain knowledge of some of these instructions by sniffing the unencrypted incremental updates. These updates exist to reduce the radio reception power for resource-constrained devices. Based on the literature, these updates are checked against authentication and integrity, but they are sometimes sent unencrypted. Therefore, it will be demonstrated how a Return-Oriented Programming (ROP) attack can be accomplished using only the passively sniffed incremental updates. The generated updates of the R3diff and Delta Generator (DG) differencing algorithms will be under assessment. The evaluation reveals that both of them can be exploited by the attacker. It also shows that the DG generated updates leak more information than the R3diff generated updates. To defend against this attack, different countermeasures that consider different power consumption scenarios are proposed, but yet to be evaluated.

To ensure the safe operation of power system, this paper studies two technologies of data encryption and digital signature, and designs a real-time data encryption system based on DES algorithm, which improves the security of data network communication. The real-time data encryption system of power system is optimized by the hybrid encryption system based on DES algorithm. The real-time data encryption of power system adopts triple DES algorithm, and double DES encryption algorithm of RSA algorithm to ensure the security of triple DES encryption key, which solves the problem of real-time data encryption management of power system. Java security packages are used to implement digital signatures that guarantee data integrity and non-repudiation. Experimental results show that the data encryption system is safe and effective.

Signcryption is a sophisticated cryptographic tool that combines the benefits of digital signature and data encryption in a single step, resulting in reduced computation and storage cost. However, the existing signcryption techniques do not account for a scenario in which a company must escrow an employee's private encryption key so that the corporation does not lose the capacity to decrypt a ciphertext when the employee or user is no longer available. To circumvent the issue of non-repudiation, the private signing key does not need to be escrowed. As a result, this paper presents an implicit certificate-based signcryption technique with private encryption key escrow, which can assist an organization in preventing the loss of private encryption. A certificate, or more broadly, a digital signature, protects users' public encryption and signature keys from man-in-the-middle attacks under our proposed approach.

As the rapid development of information technology and networks, there have been several new challenges to data security. For security needs in the process of data transmission and storage, the data security protection mechanism based on SM algorithm is studied. In addition, data cryptographic security protection system model composed of cryptographic infrastructure, cryptographic service nodes and cryptographic modules is proposed. As the core of the mechanism, SM algorithm not only brings about efficient data encryption and decryption, but ensures the security, integrity and non-repudiation of data transmission and storage. Secure and controllable key management is implemented by this model, which provides easy-to-expandable cryptographic services, and brings efficient cryptographic capabilities applicable for multiple scenarios.

Research on post-quantum cryptography (PQC) to improve the security against quantum computers has been actively conducted. In 2020, NIST announced the final PQC candidates whose design rationales rely on NP-hard or NP-complete problems. It is believed that cryptography based on NP-hard problem might be secure against attacks using quantum computers. N. Koblitz introduced the concept of public-key cryptography using a 3-regular graph with a perfect dominating set in the 1990s. The proposed cryptosystem is based on NP-complete problem to find a perfect dominating set in the given graph. Later, S. Yoon proposed a variant scheme using a perfect minus dominating function. However, their works have not received much attention since these schemes produce huge ciphertexts and are hard to implement efficiently. Also, the security parameters such as key size and plaintext-ciphertext size have not been proposed yet. We conduct security and performance analysis of their schemes and discuss the practical range of security parameters. As an application, the scheme with one-wayness property can be used as an encoding method in the white-box cryptography (WBC).

Structural analysis is the study of finding component functions for a given function. In this paper, we proceed with structural analysis of structures consisting of the S (nonlinear Substitution) layer and the A (Affine or linear) layer. Our main interest is the S1AS2 structure with different substitution layers and large input/output sizes. The purpose of our structural analysis is to find the functionally equivalent oracle F* and its component functions for a given encryption oracle F(= S2 ∘ A ∘ S1). As a result, we can construct the decryption oracle F*−1 explicitly and break the one-wayness of the building blocks used in a White-box implementation. Our attack consists of two steps: S layer recovery using multiset properties and A layer recovery using differential properties. We present the attack algorithm for each step and estimate the time complexity. Finally, we discuss the applicability of S1AS2 structural analysis in a White-box Cryptography environment.