Enhanced Compression and Cryptographic Techniques for Securing Images- A Survey

2019 ◽  
Vol 7 (4) ◽  
pp. 344-348
Author(s):  
G.Elavarasi . ◽  
M. Vanitha
Keyword(s):  
Cryptographic Techniques

TEKNIK PENYEMBUNYIAN PESAN TEKS TERENKRIPSI ALGORITMA MERKLE-HELLMAN KNAPSACK MENGGUNAKAN METODE PIXEL VALUE DIFFERENCING KE DALAM CITRA DIGITAL

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Agung Lestari ◽  
Abdul Sani Sembiring ◽  
Taronisokhi Zebua
Keyword(s):  
Digital Image ◽  
Data Security ◽  
Object Based ◽  
Pixel Value ◽  
Attack Data ◽  
Pixel Value Differencing ◽  
Knapsack Algorithm ◽  
Cryptographic Techniques

Optimization of data security techniques is very necessary so that the data or information that is secured is really safe from attack. Data that has been encrypted based on cryptographic techniques very quickly raises suspicion that the data is confidential or important. Therefore, this technique is better combined with steganography techniques. Utilization of steganography techniques can minimize the attacker's suspicion of data that is secured, because by using steganography data techniques can be hidden on certain objects. This study discusses how to encode a text based on the Merkle-Hellman Knapsack algorithm and the resulting password is hidden in a grayscale digital image as a hiding object based on the pixel value differencing algorithm. This is done to minimize suspicion and make it difficult for attackers to find out confidential or important data.Keywords: cryptography,steganography, merkle-hellmankanpsack, PVD, image

A review on various cryptographic techniques & algorithms

2021 ◽  
Author(s):  
Dilip Kumar Sharma ◽  
Ningthoujam Chidananda Singh ◽  
Daneshwari A Noola ◽  
Amala Nirmal Doss ◽  
Janaki Sivakumar
Keyword(s):  
Cryptographic Techniques

Computing Blindfolded on Data Homomorphically Encrypted under Multiple Keys: A Survey

2022 ◽  
Vol 54 (9) ◽  
pp. 1-37
Author(s):  
Asma Aloufi ◽  
Peizhao Hu ◽  
Yongsoo Song ◽  
Kristin Lauter
Keyword(s):  
Homomorphic Encryption ◽  
Lessons Learned ◽  
Secret Key ◽  
Sensitive Data ◽  
Encrypted Data ◽  
Outsourced Computation ◽  
Secret Keys ◽  
Comprehensive Survey ◽  
Multiple Keys ◽  
Cryptographic Techniques

With capability of performing computations on encrypted data without needing the secret key, homomorphic encryption (HE) is a promising cryptographic technique that makes outsourced computations secure and privacy-preserving. A decade after Gentry’s breakthrough discovery of how we might support arbitrary computations on encrypted data, many studies followed and improved various aspects of HE, such as faster bootstrapping and ciphertext packing. However, the topic of how to support secure computations on ciphertexts encrypted under multiple keys does not receive enough attention. This capability is crucial in many application scenarios where data owners want to engage in joint computations and are preferred to protect their sensitive data under their own secret keys. Enabling this capability is a non-trivial task. In this article, we present a comprehensive survey of the state-of-the-art multi-key techniques and schemes that target different systems and threat models. In particular, we review recent constructions based on Threshold Homomorphic Encryption (ThHE) and Multi-Key Homomorphic Encryption (MKHE). We analyze these cryptographic techniques and schemes based on a new secure outsourced computation model and examine their complexities. We share lessons learned and draw observations for designing better schemes with reduced overheads.

Modeling a multi-layered blockchain framework for digital services that governments can implement

2021 ◽  
pp. 1-13
Author(s):  
Fernando Rebollar ◽  
Rocío Aldeco-Perez ◽  
Marco A. Ramos
Keyword(s):  
Statistical Analysis ◽  
General Population ◽  
Information Security ◽  
High Rate ◽  
The Internet ◽  
Sufficient Information ◽  
Electronic Network ◽  
Digital Services ◽  
Different Types ◽  
Cryptographic Techniques

The general population increasingly uses digital services, meaning services which are delivered over the internet or an electronic network, and events such as pandemics have accelerated the need of using new digital services. Governments have also increased their number of digital services, however, these digital services still lack of sufficient information security, particularly integrity. Blockchain uses cryptographic techniques that allow decentralization and increase the integrity of the information it handles, but it still has disadvantages in terms of efficiency, making it incapable of implementing some digital services where a high rate of transactions are required. In order to increase its efficient, a multi-layer proposal based on blockchain is presented. It has four layers, where each layer specializes in a different type of information and uses properties of public blockchain and private blockchain. An statistical analysis is performed and the proposal is modeled showing that it maintains and even increases the integrity of the information while preserving the efficiency of transactions. Besides, the proposal can be flexible and adapt to different types of digital services. It also considers that voluntary nodes participate in the decentralization of information making it more secure, verifiable, transparent and reliable.

scholarly journals Adaptive Secure Cross-Cloud Data Collaboration with Identity-Based Cryptography and Conditional Proxy Re-Encryption

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Qinlong Huang ◽  
Yue He ◽  
Wei Yue ◽  
Yixian Yang
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
Security And Privacy ◽  
Broadcast Encryption ◽  
Cloud Data ◽  
Identity Based ◽  
Identity Based Cryptography ◽  
And Performance ◽  
Cryptographic Techniques ◽  
Data Collaboration

Data collaboration in cloud computing is more and more popular nowadays, and proxy deployment schemes are employed to realize cross-cloud data collaboration. However, data security and privacy are the most serious issues that would raise great concerns from users when they adopt cloud systems to handle data collaboration. Different cryptographic techniques are deployed in different cloud service providers, which makes cross-cloud data collaboration to be a deeper challenge. In this paper, we propose an adaptive secure cross-cloud data collaboration scheme with identity-based cryptography (IBC) and proxy re-encryption (PRE) techniques. We first present a secure cross-cloud data collaboration framework, which protects data confidentiality with IBC technique and transfers the collaborated data in an encrypted form by deploying a proxy close to the clouds. We then provide an adaptive conditional PRE protocol with the designed full identity-based broadcast conditional PRE algorithm, which can achieve flexible and conditional data re-encryption among ciphertexts encrypted in identity-based encryption manner and ciphertexts encrypted in identity-based broadcast encryption manner. The extensive analysis and experimental evaluations demonstrate the well security and performance of our scheme, which meets the secure data collaboration requirements in cross-cloud scenarios.

scholarly journals Manipulation Attacks in Local Differential Privacy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Albert Cheu ◽  
Adam Smith ◽  
Jonathan Ullman
Keyword(s):  
Systematic Study ◽  
Differential Privacy ◽  
Domain Size ◽  
User Data ◽  
Large Systems ◽  
Cryptographic Techniques ◽  
Fundamental Limitation ◽  
Theoretical Results ◽  
Different Levels ◽  
Privacy Level

Local differential privacy is a widely studied restriction on distributed algorithms that collect aggregates about sensitive user data, and is now deployed in several large systems. We initiate a systematic study of a fundamental limitation of locally differentially private protocols: they are highly vulnerable to adversarial manipulation. While any algorithm can be manipulated by adversaries who lie about their inputs, we show that any noninteractive locally differentially private protocol can be manipulated to a much greater extent---when the privacy level is high, or the domain size is large, a small fraction of users in the protocol can completely obscure the distribution of the honest users' input. We also construct protocols that are optimally robust to manipulation for a variety of common tasks in local differential privacy. Finally, we give simple experiments validating our  theoretical results, and demonstrating that protocols that are optimal without manipulation can have dramatically different levels of robustness to manipulation. Our results suggest caution when deploying local differential privacy and reinforce the importance of efficient cryptographic  techniques for the distributed emulation of centrally differentially private mechanisms.

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