Biblio

Due to high availability and easy accessibility of information, it has become quite difficult to assure security of data. Even though watermarking seems to be an effective solution to protect data, it is still challenging to be used with relational databases. Moreover, inserting a watermark in database may lead to distortion. As a result, the contents of database can no longer remain useful. Our proposed distortion-free watermarking approach ensures that integrity of database can be preserved by generating an image watermark from its contents. This image is registered with Certification Authority (CA) before the database is distributed for use. In case, the owner suspects any kind of tampering in the database, an image watermark is generated and compared with the registered image watermark. If both do not match, it can be concluded that the integrity of database has been compromised. Experiments are conducted on Forest Cover Type data set to localize tampering to the finest granularity. Results show that our approach can detect all types of attack with 100% accuracy.

With the outgrowth of video editing tools, video information trustworthiness becomes a hypersensitive field. Today many devices have the capability of capturing digital videos such as CCTV, digital cameras and mobile phones and these videos may transmitted over the Internet or any other non secure channel. As digital video can be used to as supporting evidence, it has to be protected against manipulation or tampering. As most video authentication techniques are based on watermarking and digital signatures, these techniques are effectively used in copyright purposes but difficult to implement in other cases such as video surveillance or in videos captured by consumer's cameras. In this paper we propose an intelligent technique for video authentication which uses the video local information which makes it useful for real world applications. The proposed algorithm relies on the video's statistical local information which was applied on a dataset of videos captured by a range of consumer video cameras. The results show that the proposed algorithm has potential to be a reliable intelligent technique in digital video authentication without the need to use for SVM classifier which makes it faster and less computationally expensive in comparing with other intelligent techniques.

Anti-tampering is a form of software protection conceived to detect and avoid the execution of tampered programs. Tamper detection assesses programs' integrity with load or execution-time checks. Avoidance reacts to tampered programs by stopping or rendering them unusable. General purpose reactions (such as halting the execution) stand out like a lighthouse in the code and are quite easy to defeat by an attacker. More sophisticated reactions, which degrade the user experience or the quality of service, are less easy to locate and remove but are too tangled with the program's business logic, and are thus difficult to automate by a general purpose protection tool. In the present paper, we propose a novel approach to anti-tampering that (i) fully automatically applies to a target program, (ii) uses Remote Attestation for detection purposes and (iii) adopts a server-side reaction that is difficult to block by an attacker. By means of Client/Server Code Splitting, a crucial part of the program is removed from the client and executed on a remote trusted server in sync with the client. If a client program provides evidences of its integrity, the part moved to the server is executed. Otherwise, a server-side reaction logic may (temporarily or definitely) decide to stop serving it. Therefore, a tampered client application can not continue its execution. We assessed our automatic protection tool on a case study Android application. Experimental results show that all the original and tampered executions are correctly detected, reactions are promptly applied, and execution overhead is on an acceptable level.