Data Decryption Research Articles

Design of a software architecture supporting business-to-government information sharing to improve public safety and security

To ensure public safety and security, it is vitally important for governments to collect information from businesses and analyse it. Such information can be used to determine whether transported goods might be suspicious and therefore require physical inspection. Although businesses are obliged to report some information, they are reluctant to share additional information for fear of sharing competitively sensitive information, becoming liable and not being compliant with the law. These reasons are often overlooked in the design of software architectures for information sharing. In the present research, we followed a design science approach to develop a software architecture for business-to-government information sharing. Based on literature and a case study, we elicited the requirements an architecture that provides for the sharing of information should meet to make it acceptable to businesses. We then developed the architecture and evaluated it against the requirements. The architecture consists of a blockchain that stores events and rules for information sharing that are controlled by businesses. For each event, two parties use their private keys to encrypt its Merkle root to confirm that they know the data are correct. This makes it easy to check whether information is reliable and whether an event should be accepted. Access control, metadata and context information enable the context-based sharing of information. This is combined with the encryption and decryption of data to provide access to certain data within an organisation.

A proposal of privacy preserving reinforcement learning for secure multiparty computation

Many studies have been done with the security of cloud computing. Though data encryption is a typical approach, high computing complexity for encryption and decryption of data is needed. Therefore, safe system for distributed processing with secure data attracts attention, and a lot of studies have been done. Secure multiparty computation (SMC) is one of these methods. Specifically, two learning methods for machine learning (ML) with SMC are known. One is to divide learning data into several subsets and perform learning. The other is to divide each item of learning data and perform learning. So far, most of works for ML with SMC are ones with supervised and unsupervised learning such as BP and K-means methods. It seems that there does not exist any studies for reinforcement learning (RL) with SMC. This paper proposes learning methods with SMC for Q-learning which is one of typical methods for RL. The effectiveness of proposed methods is shown by numerical simulation for the maze problem.

An Efficient and Fine-Grained Big Data Access Control Scheme With Privacy-Preserving Policy

How to control the access of the huge amount of big data becomes a very challenging issue, especially when big data are stored in the cloud. Ciphertext-policy attribute-based encryption (CP-ABE) is a promising encryption technique that enables end-users to encrypt their data under the access policies defined over some attributes of data consumers and only allows data consumers whose attributes satisfy the access policies to decrypt the data. In CP-ABE, the access policy is attached to the ciphertext in plaintext form, which may also leak some private information about end-users. Existing methods only partially hide the attribute values in the access policies, while the attribute names are still unprotected. In this paper, we propose an efficient and fine-grained big data access control scheme with privacy-preserving policy. Specifically, we hide the whole attribute (rather than only its values) in the access policies. To assist data decryption, we also design a novel attribute bloom filter to evaluate whether an attribute is in the access policy and locate the exact position in the access policy if it is in the access policy. Security analysis and performance evaluation show that our scheme can preserve the privacy from any linear secret-sharing schemes access policy without employing much overhead.

Luminescence Color Tuning by Regulating Electrostatic Interaction in Light-Emitting Devices and Two-Photon Excited Information Decryption.

It is well-known that the variation of noncovalent interactions of luminophores, such as π-π interaction, metal-to-metal interaction, and hydrogen-bonding interaction, can regulate their emission colors. Electrostatic interaction is also an important noncovalent interaction. However, very few examples of luminescence color tuning induced by electrostatic interaction were reported. Herein, a series of Zn(II)-bis(terpyridine) complexes (Zn-AcO, Zn-BF4, Zn-ClO4, and Zn-PF6) containing different anionic counterions were reported, which exhibit counterion-dependent emission colors from green-yellow to orange-red (549 to 622 nm) in CH2Cl2 solution. More importantly, it was found that the excited states of these Zn(II) complexes can be regulated by changing the electrostatic interaction between Zn2+ and counterions. On the basis of this controllable excited state, white light emission has been achieved by a single molecule, and a white light-emitting device has been fabricated. Moreover, a novel type of data decryption system with Zn-PF6 as the optical recording medium has been developed by the two-photon excitation technique. Our results suggest that rationally controlled excited states of these Zn(II) complexes by regulating electrostatic interaction have promising applications in various optoelectronic fields, such as light-emitting devices, information recording, security protection, and so on.

An Energy Efficient Fast and Secure Data Aggregation Scheme for Wireless Sensor Network

Energy efficiency and secured data collection are two important performance metrics for critical event monitoring in wireless sensor network. Current state-of-the-art research is limited to either maximizing security under redundant radix-based approach or security through adversary model while satisfying throughput requirement. Although many prior research efforts resulted in optimized solutions, but how to optimize both objectives simultaneously has to be addressed. In this paper, an integrated framework called Secured Marvin and Adaptive Derivative Scheduler (SM-ADS) is presented to improve the fastness of data collection of sensed data event in the sink. To focus on secure data collection of sensed data events, the encryption and decryption of sensor data is simplified using Marvin Message Authentication Codes. We show that the solution to the integrated framework problem characterizes the secured energy efficient data collection through XOR ing operations. Next, an Adaptive Derivative Scheduler based on Steiner Tree is presented with the objective of reducing the energy consumption of sensed data collection at the sink. By applying the Steiner tree, minimum hops between source and sink nodes are identified satisfying the energy conservation principal. An extensive simulation analysis to demonstrate the security aspect and energy conservation principal with time taken for data collection is presented. The obtained results show that SM-ADS provide comparatively better performance than the state-of-the-art works in terms of both security and energy efficiency. Experimental analysis shows that SM-ADS is able to reduce the time for data collection by 25.72% and energy consumption by 18.48% compared to the state-of-the-art works.

Performance Study of Key Developer Data Encryption and Decryption Algorithm (KDDEDA) with AES, DES and BLOWFISH

Performance Study of Key Developer Data Encryption and Decryption Algorithm (KDDEDA) with AES, DES and BLOWFISH

A Survey on Secret Data Transmission Using Various Steganographic Aspects

The security of Transmission of data becomes a huge issue in information and communication Technology. So ,to ensure the security of data during transmission, Two major techniques are adopted. They are Cryptography and Steganography. In these, the input data is encrypted using encryption algorithms and embedded into carrier image then transmitted through a communication channel, at the receiver side, data decrypted using data decryption algorithms is restored with error free. We are conducting a survey in this paper based on different steganographic and cryptographic methods for Data security.

Secure pay-TV for chained hotels

There is an increasing demand of securely selling pay-TV channels to large organizations such as chained hotels. Most solutions usually employ a key generation authority to distribute secret access credentials for all users, which would cause the single-point problem of inefficient key management. Further, there is a risk of the leakage of users' access credentials while countermeasures to find out the leaked credentials are lacking. To address such issues, we propose a leakage traceable hierarchical key distribution (LTHKD) framework with the key delegation and the key-leakage tracing. The key delegation allows the key generation authority to apportion the tasks of access credential generation to a number of group authorities; the tracing mechanism provides an efficient method to find out the leaked access credentials. We present a concrete LTHKD scheme by extending hierarchical identity-based encryption to groups with users' access credentials elegantly encoded by unique fingerprint codes. We formally prove the security of the proposed scheme in a rigorous definition and conduct thorough theoretical and experimental analyses to evaluate the system performance. Surprisingly, the results show that the added key-leakage tracing mechanism has little affection on data encryption and decryption procedures.

부분 암호화를 위한 해쉬 트리 체인 기반 키 생성 및 관리 알고리즘

본 논문에서는 부분 암호화를 위한 키 생성 및 관리 알고리즘의 연구한다. 제안하는 알고리즘에서는 해쉬 트리 구조를 이용하여 적은 양의 해쉬키로부터 다양한 암호화 키를 생성하는 기능을 제공하고 있다. 본 논문에서는 새로운 키 생성 알고리즘을 이용하여 부분 암호화 및 부분 복호화하는 방법을 제시하고 시뮬레이션을 통하여 그 성능을 분석한다. A new key generation scheme is proposed to support partial encryption and partial decryption of data in cloud computing environment with a minimal key-related traffic overhead. Our proposed scheme employs a concept of hash tree chain to reduce the number of keys that need to be delivered to the decryption node. The performance of the proposed scheme is evaluated through simulation.

Data Security in Cloud using Multi Modal Biocryptographic Authentication

Objectives: Higher data security can be achieved by using Multimodal bio cryptographic technique for data encryption and decryption to avoid the intruders to access the data. Methods: Iris and fingerprint are used as a key for both data encryption and decryption in Multimodal biometric based blowfish algorithm. The data stored in cloud environment after encryption. Findings: The problem with storing the data in cloud environment using password system is, it is not secured, forgotten and easily stolen. Hackers can able to trace the password through keystroke loggers and spyware. In multimodel biometric system it is not possible to hack the data by the intruders. For both data decryption and encryption blowfish algorithm is used. Combined biometric of both fingerprint and iris uses as a secret key for a blowfish algorithm. Applications: To run the middleware for connecting the cloud system no need of advanced hardware system. High data security is enough.

Multimedia recommendation and transmission system based on cloud platform

This paper presents a movie recommendation system according to scores that the users provide. In view of the movie evaluation system, the impacts of access control and multimedia security are analyzed, and a secure hybrid cloud storage architecture is presented. Mobile-Edge Computing (MEC) technology is used in the public cloud which guarantees the high efficiency requirements of the transmission of the multimedia content. The processes of the system including registration, user login, role assignment, data encryption and data decryption are also described. At last, the performance of the proposed scheme is analyzed which further shows that the various possible attacks can be mitigated via the proposed system.

CERTIFICATELESS ENCRYPTION FOR SECURE DATA SHARING IN PUBLIC CLOUD

Cloud computing is more popular in organizations and institutions because it provides storage and computing services at low cost. Cloud computing provide users and enterprises with various capabilities to store and process their data in third-party data centers that may be located far from the user ranging in distance from across a city to across the world. However, it also introduces new challenges for ensuring the confidentiality, integrity and access control of the data. Some approaches are given to ensure these security requirements but they are lacked in some ways such as violation of data confidentiality due to collusion attack and heavy computation (due to large no keys).To address these issues we propose a scheme that uses efficient certificate less in which data owner divides users in groups and gives single key to each user group for decryption of data and, each user in the group shares parts of the key. Certificateless cryptography is a Capricious of ID-based cryptography intended to prevent the key escrow problem. Ordinarily, keys are generated by a certificate authority or a key generation center (KGC) who is given complete power and is implicitly trusted. For prevention of a complete breakdown of the system in the case of a compromised KGC, the key generation process (KGP) is split between the KGC and the user. In this paper, we use capability list and access list to control the access. Authentication and access control are often merged into a single operation, so that access is approved based on successful authentication or based on an anonymous access token. This scheme not only provides the strong data confidentiality but also reduces the number of keys. Key words- capability list, authentication, certificateless cryptography, confidentiality, access control, malicious outsiders

Secure Data Storage in Cloud by Decentralized Access Control

Cloud computing is recently developed new emerging technology for complex systems with massive-scale services sharing among numerous users, where user can rent the storage and computing resources of server provided by a company. Users only require a terminal, a smart phone or tablet connected to the internet. Cloud can store huge amount of data, so the mobile users do not have to carry their data. Therefore, security of data, privacy of user and authentication of both users and services is a significant issue for the trust and security of cloud computing. In order to achieve safe storage, we proposed a secure cloud storage scheme providing access to the data using RSA publickey encryption algorithm and digital signature scheme. In this scheme, the cloud verifies the authenticity of the series without knowing the user’s identity before storing data. Access control feature is also added by which only a valid users are able to decrypt the stored information. This scheme also prevents replay attack and supports creation, modification, and reading data stored in cloud. Time based user Revocation scheme is also used. Also we compared performance of our system with the 3DES system on the basis of encryption and decryption of data.

Analysis of EnDeCloudReports for Encrypting and Decrypting Data in Cloud

In the midst of the last decades, information security has become an important issue. Encryption and decryption of data have recently been universally researched and developed as there is a need for a secure encryption and decryption which is very difficult to break. Cryptography offers main functions to meet these demands. Today, researchers have proposed several encryption and decryption algorithms such as AES, DES, RSA, and others. But most of the proposed algorithms encountered some problems such as lack of robustness and significant amount of time taken in encryption/decryption of data residing on server in cloud to maintain the security in cloud. In this paper, the cloud security enhanced by EnDeCloudReports simulator tool is analyzed on various parameters and attacks which in turn enhance the data security in Cloud by making it difficult for attacker to predicate a pattern as well as speed of the encryption / decryption scheme.

High throughput FPGA Implementation of Data Encryption Standard with time variable sub-keys

<span lang="EN-US">The Data Encryption Standard (DES) was the first modern and the most popular symmetric key algorithm used for encryption and decryption of digital data. Even though it is nowadays not considered secure against a determined attacker, it is still used in legacy applications. This paper presents a secure and high-throughput Field Programming Gate Arrays (FPGA) implementation of the Data Encryption Standard algorithm. This is achieved by combining 16 pipelining concept with time variable sub-keys and compared with previous illustrated encryption algorithms. The sub-keys vary over time by changing the key schedule permutation choice 1. Therefore, every time the plaintexts are encrypted by different sub-keys. The proposed algorithm is implemented on Xilinx Spartan-3e (XC3s500e) FPGA. Our DES design achieved a data encryption rate of 10305.95 Mbit/s and 2625 number of occupied CLB slices. These results showed that the proposed implementation is one of the fastest hardware implementations with much greater security.</span>

A Novel Idea on Multimedia Encryption Using Hybrid Crypto Approach

Data security is of utmost importance in today's world. Especially when the data is travelling through an insecure communication network. There are symmetric key encryption techniques which use only one key for both encryption and decryption of the data. They are simple in design but can be easily cracked using brute force attacks. The entire security of such a cipher could be compromised if the attacker anyhow gets access to the keys. On the other hand, there are asymmetric key based algorithms which use a pair of keys, one for encryption, and the other for decryption, whose security is higher as compared to the symmetric ones but lack in time efficiency. It is also difficult to manage such a huge base of key-pairs efficiently and safely. This paper mainly focusses on the implementation of a system capable of encryption and decryption of multimedia data (Text, Images, Videos, Audio etc.) using a hybrid model based on the amalgamation of symmetric encryption techniques such as AES and asymmetric techniques such as ECC. ECC is based on the toughness of the discrete logarithm problem (DLP), whose public key is short, network bandwidth is little and ability to resist to attack is strong which makes it really difficult to guess the keys. Even if the attacker gets access to any of the keys, he or she won’t be in a position to decipher it in a relatively finite amount of man-years.

Secured Web Service Communication using Attribute based Encryption and Outsource Decryption with Trusted Certificate Authorities (ABE-TCA)

Web services are one of the most aspired technologies in IT industry and more companies are adopting concepts and strategies used in web services for their businesses. User‘s set of attributes paves way for encryption and decryption of data by employing impregnable Attribute Based Encryption (ABE) for defended web service communication, which intensifies its privacy and security. In the existing ABE scheme, decryption involves an expensive process and increase the complexity of the access policy. To overcome the decryption overhead, outsourced decryption is used to authenticate the untrusted servers. The transformation key is responsible for reducing the decryption overhead by translating the complex ciphertext into simple ciphertext based on the user‘s attributes, and the overhead for the conversion of ciphertext to plaintext is acceptably minimal. Kerberos is incorporated to generate a ticket granting service that is used to verify authentication database and after verification of both parties, replies to the requested user for authentication. Furthermore to secure outsourcing agents, Certificate Authority is used to segregate unauthorized users. During data transmission integrity of the data can be verified by hashing algorithms.

A Highly Secured Mathematical Model for Data Encryption Using Fingerprint Data

In this research we tried to find out a new, unique and efficient way for converting plain-text to numbers or other values which can be used both in Symmetric and Public Key Cryptography, Stenography and others related with data security. It is just a developed and highly secured model for just converting plain-text to cipher text. We proposed a new data encryption and decryption method here which can help anyone for encrypting and decrypting data more securely.

Enhanced Schmidt-Samoa cryptosystem for data confidentiality in cloud computing

Cloud computing provides IT services like computation, storage, networking, and software to the users. Cloud storage services allows users to access the data anywhere and at anytime, under the supervision of cloud service provider CSP. Protecting the data against data breaches in the cloud is still a challenging issue for CSP. Public key cryptographic techniques are widely used to ensure authenticity, confidentiality, and non-repudiation. Schmidt-Samoa cryptosystem SSC is a public key cryptosystem, which depends on the resistance of integer factorisation. While implementing SSC in the cloud, the cryptosystem consumes more time for performing encryption and decryption. In this paper, we propose an enhanced Schmidt-Samoa ESS public key cryptosystem to address this problem. The ESS cryptosystem composes with four prime numbers, which increase the complexity to break the cryptosystem compared to SSC. The experimental results with variable file size and key size also proved that the time required to perform the data encryption and decryption in ESS is lower and the time required to perform cryptanalysis in ESS is higher compared with SSC. Thus, the ESS cryptosystem is highly secured, and improves data confidentiality.

Block Level Data Integrity Assurance Using Matrix Dialing Method towards High Performance Data Security on Cloud Storage

Data outsourcing through cloud storage enables the users to share on-demand resources with cost effective IT services but several security issues arise like confidentiality, integrity and authentication. Each of them plays an important role in the successful achievement of the other. In cloud computing data integrity assurance is one of the major challenges because the user has no control over the security mechanism to protect the data. Data integrity insures that data received are the same as data stored. It is a result of data security but data integrity refers to validity and accuracy of data rather than protect the data. Data security refers to protection of data against unauthorized access, modification or corruption and it is necessary to ensure data integrity. This paper proposed a new approach using Matrix Dialing Method in block level to enhance the performance of both data integrity and data security without using Third Party Auditor (TPA). In this approach, the data are partitioned into number of blocks and each block converted into a square matrix. Determinant factor of each matrix is generated dynamically to ensure data integrity. This model also implements a combination of AES algorithm and SHA-1 algorithm for digital signature generation. Data coloring on digital signature is applied to ensure data security with better performance. The performance analysis using cloud simulator shows that the proposed scheme is highly efficient and secure as it overcomes the limitations of previous approaches of data security using encryption and decryption algorithms and data integrity assurance using TPA due to server computation time and accuracy.