Securing data is more important than ever. As the Internet has become more pervasive, security attacks have

Abstract — Tampering of a database can be detected through the use of cryptographically-strong hash functions. Subsequently-applied forensic analysis algorithms can help determine when, what, and perhaps ultimately who and why. This paper presents a novel forensic analysis algorithm, the Tiled Bitmap Algorithm, which is more efficient than prior forensic analysis algorithms. It introduces the notion of a candidate set (all possible locations of detected tampering(s)) and provides a complete characterization of the candidate set and its cardinality. An optimal algorithm for computing the candidate set is also presented. Finally, the implementation of the Tiled Bitmap Algorithm is discussed, along with a comparison to other forensic algorithms in terms of space/time complexity and cost. An example of candidate set generation and proofs of the theorems and lemmata and of algorithm correctness can be found in the appendix.

Abstract — Spurred by financial scandals and privacy concerns, governments worldwide have moved to ensure confidence in digital records by regulating their retention and deletion. These requirements have led to a huge market for compliance storage servers, which ensure that data are not shredded or altered before the end of their mandatory retention period. These servers preserve unstructured and semi-structured data at a file-level granularity: email, spreadsheets, reports, instant messages. In this paper, we extend this level of protection to structured data residing in relational databases. We propose a compliant DBMS architecture and two refinements that illustrate the additional security that one can gain with only a slight performance penalty, with almost no modifications to the DBMS kernel. We evaluate our proposed architecture through experiments with TPC-C on a high-performance DBMS, and show that the runtime overhead for transaction processing is approximately 10 % in typical configurations. I.

Abstract. We introduce WORM-ORAM, a first mechanism that combines Oblivious RAM (ORAM) access privacy and data confidentiality with Write Once Read Many (WORM) regulatory data retention guarantees. Clients can outsource their database to a server with full confidentiality and data access privacy, and, for data retention, the server ensures client access WORM semantics. In general simple confidentiality and WORM assurances are easily achievable e.g., via an encrypted outsourced data repository with server-enforced read-only access to existing records (albeit encrypted). However, this becomes hard when also access privacy is to be ensured – when client access patterns are necessarily hidden and the server cannot enforce access control directly. WORM-ORAM overcomes this by deploying a set of zero-knowledge proofs to convince the server that all stages of the protocol are WORM-compliant. 1

We introduce a Write-Once Read-Many (WORM) storage system providing strong assurances of data retention and compliant migration, by leveraging trusted secure hardware in close data proximity. This is important because existing compliance storage products and research prototypes are fundamentally vulnerable to faulty or malicious behavior, as they rely on simple enforcement primitives illsuited for their threat model. This is hard because tamperproof processing elements are significantly constrained in both computation ability and memory capacity – as heat dissipation concerns under tamper-resistant requirements limit their maximum allowable spatial gate-density. We achieve efficiency by (i) ensuring the secure hardware is accessed sparsely, minimizing the associated overhead for expected transaction loads, and (ii) using adaptive overheadamortized constructs to enforce WORM semantics at the throughput rate of the storage servers ordinary processors during burst periods. With a single secure co-processor, on single-CPU commodity x86 hardware, our architecture can support over 2500 transactions per second. 1

Summary. Digital societies and markets increasingly mandate consistent procedures for the access, processing and storage of information. In the United States alone, over 10,000 such regulations can be found in financial, life sciences, healthcare and government sectors, including the Gramm-

Regulatory frameworks impose a wide range of policies in finance, life sciences, health-care and the government.

Abstract- The need for secure data storage has become a necessity of our time. Medical records, financial records, and legal information are all in need of secure storage. In the era of globalization and dynamic world economies, data outsourcing is inevitable. Security is major concern in data outsourcing environment, since data is under the custody of third party service provider. In present systems, third party can access & view data even though they are not authorized to do so or even when the data is outsourced to the auditors or allow the employee of the organization to do the updating in the database. This may lead to the serious data theft, data tampering & even data leakages causing severe business impact to data owner. There are certain many such cases occurred in financial & insurance sector where the data is been tampered by the auditors or by the employees of the organization itself. In this paper we have proposed a novel solution to overcome the problem of tamper detection by notarizing the original data. A heuristics approach is presented in our model where a validator system always authenticate the data for its originality using strong one way hash key functions like MD5 with authorized notarizer. By providing different digital signatures for different data owners, the proposed system provides a strong notarization & validation schemes to maintain high data security and integrity requirements.

The set of policies and the group of people need to access the valuable database by the authorized inter mediator, still the organizational employee also go through the authorized inter mediator. Cryptographic hashing is one of the best approach and work as a inter mediator. This paper show how to resolve when tampering arises in Database, what data was tampered and the identification of the person to tamper the data. These things are detected by using the forensic analysis. This paper presents a new forensic analysis algorithm, the tiled bitmap algorithm, which is more capable then the previous algorithm. It introduces the concept of a candidate set (all possible place of detected tampering(s)) and gives a full classification of the candidate set and its cardinality and prevent the intruder, the computing of the candidate set is also presented. There are certain cases happened in BANK and other sector where the data has been tamper by the assessor, outsider or by the employees of the organizations. The separate audit logs validate to observe and inspect the database along with the extra information and state of the data. Audit log play a central role in database. The space and time complexity is less in this forensic analysis algorithm.