Secured Lossless Share Watermarking

Security has gained a lot of importance as information technology is widely used. The main issue in visual cryptography is quality of reconstructed image. This problem is overcome by using “Secured Lossless share Watermarking ”. In this method the quality of reconstructed image is higher and the security of share is high compare with conventional visual cryptographic scheme. The secret image is converted into. Each share is embedded to different carrier images. Invisible watermarking method is used for embedding carrier image and shares. For security, the invisible watermarked shares are then encrypted, AES modified encryption method is used. The encrypted shares are send to other participants. At the receiver end receiving the shares and decrypt the shares, then combining these shares together reveal the secret. The quality of rejoined shares and original secret shares are almost same. DOI: 10.17762/ijritcc2321-8169.15038

Ensuring patients privacy in a cryptographic-based-electronic health records using bio-cryptography

Several recent works have proposed and implemented cryptography as a means to preserve privacy and security of patients health data. Nevertheless, the weakest point of electronic health record (EHR) systems that relied on these cryptographic schemes is key management. Thus, this paper presents the development of privacy and security system for cryptography-based-EHR by taking advantage of the uniqueness of fingerprint and iris characteristic features to secure cryptographic keys in a bio-cryptography framework. The results of the system evaluation showed significant improvements in terms of time efficiency of this approach to cryptographic-based-EHR. Both the fuzzy vault and fuzzy commitment demonstrated false acceptance rate (FAR) of 0%, which reduces the likelihood of imposters gaining successful access to the keys protecting patients protected health information. This result also justifies the feasibility of implementing fuzzy key binding scheme in real applications, especially fuzzy vault which demonstrated a better performance during key reconstruction

AES-CBC Software Execution Optimization

With the proliferation of high-speed wireless networking, the necessity for efficient, robust and secure encryption modes is ever increasing. But, cryptography is primarily a computationally intensive process. This paper investigates the performance and efficiency of IEEE 802.11i approved Advanced Encryption Standard (AES)-Rijndael ciphering/deciphering software in Cipher Block Chaining (CBC) mode. Simulations are used to analyse the speed, resource consumption and robustness of AES-CBC to investigate its viability for image encryption usage on common low power devices. The detailed results presented in this paper provide a basis for performance estimation of AES cryptosystems implemented on wireless devices. The use of optimized AES-CBC software implementation gives a superior encryption speed performance by 12 - 30%, but at the cost of twice more memory for code size.Comment: 8 pages, IEEE 200

Protection of an intrusion detection engine with watermarking in ad hoc networks

Mobile ad hoc networks have received great attention in recent years, mainly due to the evolution of wireless networking and mobile computing hardware. Nevertheless, many inherent vulnerabilities exist in mobile ad hoc networks and their applications that affect the security of wireless transactions. As intrusion prevention mechanisms, such as encryption and authentication, are not sufficient we need a second line of defense, Intrusion Detection. In this pa-per we present an intrusion detection engine based on neural networks and a protection method based on watermarking techniques. In particular, we exploit information visualization and machine learning techniques in order to achieve intrusion detection and we authenticate the maps produced by the application of the intelligent techniques using a novel combined watermarking embedding method. The performance of the proposed model is evaluated under different traffic conditions, mobility patterns and visualization metrics