CRYPTOLEQ- A HETEROGENEOUS ABSTRACT MACHINE FOR ENCRYPTED AND UNENCRYPTED COMPUTION

CRYPTOLEQ- A HETEROGENEOUS ABSTRACT MACHINE FOR ENCRYPTED AND UNENCRYPTED COMPUTION

The rapid expansion and increased popularity of cloud computing comes with no shortage of privacy concerns about outsourcing computation to semi-trusted parties. Leveraging the power of encryption, in this paper, we introduce Cryptoleq: an abstract machine based on the concept of one instruction set computer, capable of performing general-purpose computation on encrypted programs. The program operands are protected using the Paillier partially homomorphic cryptosystem, which supports addition on the encrypted domain.

Full homomorphism over addition and multiplication, which is necessary for enabling general-purpose computation, is achieved by inventing a heuristically obfuscated software re-encryption module written using Cryptoleq instructions and blended into the executing program. Cryptoleq is heterogeneous, allowing mixing encrypted and unencrypted instruction operands in the same program memory space.

Programming with Cryptoleq is facilitated using an enhanced assembly language that allows the development of any advanced algorithm on encrypted data sets. In our evaluation, we compare Cryptoleq's performance against a popular fully homomorphic encryption library, and demonstrate correctness using a typical private information retrieval problem.

INTRODUCTION

Heterogeneous abstract machine based on one of virtual machine for encrypted data. Leveraging the power of encryption, in this paper, we introduce Cryptoleq’s: an abstract machine based on the concept of one instruction set computer, capable of performing general-purpose computation on encrypted programs.

The program operands are protected using the Paillier partially homomorphism cryptosystem, which supports addition on the encrypted domain. Full homomorphism over addition and multiplication, which is necessary for enabling general-purpose computation, is achieved by inventing a heuristically obfuscated software re-encryption module written using Cryptoleq’s instructions and blended into the executing program.

Cryptoleq’s heterogeneous allowing mixing encrypted and unencrypted instruction operands in the same program memory space. The sources can create abstract machine. Browse text files of data to send abstract machine. The generation of machine to encrypted data using one set instruction implements multiplication.

The memory consider number of sectors and each sectors contain segment of spaces. When this process is executed by availability of memory process. The text file automatically encrypts and sends to sources. Sources select destination to transmit encrypts data. Destination access key with get original files.

Design and implementation of Cryptoleq’s:

Cryptoleq’s supports programs written without privacy protections, as well as protected execution using encrypted data under full encryption or heuristic obfuscation modes, depending on the need to multiply encrypted values.

A practical frame work for Cryptoleq’s:

With extended assembly language, compiler and emulator for executing cryptoleq’s program on different platforms.Cryptoleq’s is a heterogeneous,allowing mixing encrypted and uncrypted instruction operands in the same program memory space. Programming with cryptoleq’s is facilitated using an enhanced assembly language that allows the development.

ARCHITETURE DIAGRAM

1. Design of abstraction machine encryption files

2. Design of memory using segment

3. Sources select Destination process

4. Destination Decryption of Required Process

Design of abstraction machine encryption files

Abstract machines that model software are usually thought of as having very high-level operations. For example, an abstract machine that models a banking system can have operations like "deposit," "withdraw," "transfer," etc. set computer, capable of performing general-purpose. Computation on encrypted programs.

Design of memory using segment

The design of memory based on segment of sector. In the approach, the memory is organized as a collection of sectors. Each sector is a collection of continuous segments (i.e. sequences of memory cells) and all cell addresses within one sector share the same s value, while all cell addresses within one segment have sequential t values. Incrementing a t value by a unit returns the next cell address.

WORK RELATED WITH CRYPTOLEQ

HT design methodology to achieve the above objective, namely DeTrust. Given an HT design, DeTrust keeps its original malicious behaviour while making the HT resistant to state-of-the-art hardware trust verification techniques by manipulating its trigger designs.

To be specific, De Trust implements stealthy implicit triggers for HTs by carefully spreading the trigger logic into multiple sequential levels and combinational logic blocks and combining the trigger logic with the normal logic, so that they are not easily differentiable from normal logic.

The construction of an access-driven sidechannel attack by which a malicious virtual machine (VM) extracts finegrained information from a victim VM running on the same physical computer. This attack is the first such attack demonstrated on a symmetric multiprocessing sys- tem virtualized using a modern VMM (Xen).

Such systems are very common today, ranging from desktops that use virutilization to sandbox application or OS compromises, to clouds that co-locate the workloads of mutually distrust- ful customers. Constructing such a sidechannel requires overcoming challenges including core migration, numerous sources of channel noise, and the difficulty of pre-empting the victim with sufficient frequency to extract fine-grained information.

ALGORITHM DESCRIPTION

Homomorphic encryption schemes are cryptographic constructions which enable to securely perform operations on encrypted data without ever decrypting them. More precisely, a (group) homomorphism encryption scheme over a group (G, ∗) satisfies that given two encryptions c1 = Ek(m1) and c2 = Ek(m2), where m1, m2 ∈ G and k is the encryption key, one can efficiently compute Ek(m1 ∗ m2) without decrypting c1 and c2. Homomorphic encryption schemes are widely used in many interesting applications, such as private informationretrival

CONCLUSION

 A new computational model based on the concept of single instruction architecture, able to execute programs whose instruction operands have been encrypted using Paillier PHE scheme. Universal computations achieved by introducing a software function, which adds multiplication to the abstract machine’s native addition and subtraction operations. This function is expressed using the only available instruction. We have also developed an enhanced assembly language to facilitate the development of complex programs, in addition to a compiler and an emulator.