No abstract

Steganography is the technique for hiding data and aims to hide data in such a way that any eavesdropper cannot observe any changes in the original media. The least significant bit (LSB) is one of the most public techniques in steganography. The classical technique is LSB substitution. The main idea of this technique is to directly alter some LSB of the cover image with the secret data. The essential drawback of the available LSB techniques is that increasing the capacity of the stego image leads to decreasing its quality. Therefore, the goal of the proposed method is to enhance the capacity taking high visual quality into consideration. To achieve this goal, some LSB of the cover image are inverted depending on the secret data for embedding instead of replacing LSB with the secret data. First, the maximum and minimum values in the secret data are determined then subtract all values of the secret data from this maximum value. Finally, make a division for the results and embed the new results into the cover image to obtain the stego image. The results show that the proposed method gives high capacity and good imperceptibility in comparison with the previous methods.

The need to design an optimally distributed database is increasingly important with the growth of information technology and computer networks. However, designing a distributed database is an extremely complex process due to a large number of geographically distributed sites and database relations. Moreover, decreasing communication costs and query response time should be taken into consideration. There are three main techniques applied to design a distributed database, namely Fragmentation, Data allocation, and Replication. It is notable that these techniques are often treated separately and rarely processed together. Some available allocation methods are applied regardless of how the fragmentation technique is performed or replication process is adopted. In contrast, other fragmentation techniques do not consider the allocation or the replication techniques. Therefore, the first and foremost step for designing an optimal database is to develop a comprehensive understanding of the current fragmentation, replication, and allocation techniques and their disadvantages. This article presents an attempt to fulfill this step by proposing a comprehensive taxonomy of the available fragmentation and allocation techniques in distributed database design. The article also discusses some case studies of these techniques for a deeper understanding of its achievements and limitations.

SUMMARY The Distributed Denial of Service attack (DDoS) is one of the major threats to network security that exhausts network bandwidth and resources. Recently, an efficient approach Live Baiting was proposed for detecting the identities of DDoS attackers in web service using low state overhead without requiring either the models of legitimate requests nor anomalous behavior. However, Live Baiting has two limitations. First, the detection algorithm adopted in Live Baiting starts with a suspects list containing all clients, which leads to a high false positive probability especially for large web service with a huge number of clients. Second, Live Baiting adopts a fixed threshold based on the expected number of requests in each bucket during the detection interval without the consideration of daily and weekly traffic variations. In order to address the above limitations, we first distinguish the clients activities (Active and Non-Active clients during the detection interval) in the detection process and then further propose a new adaptive threshold based on the Change Point Detection method, such that we can improve the false positive probability and avoid the dependence of detection on sites and access patterns. Extensive trace-driven simulation has been conducted on real Web trace to demonstrate the detection efficiency of the proposed scheme in comparison with the Live Baiting detection scheme.

The TCP SYN flooding attack is the most prevalent type of DDoS attacks that exhaust network resources. The current detection schemes only work well for the detection of high-rate flooding sources. It is notable, however, that in the current DDoS attacks, the flooding rate is usually distributed among many low-rate flooding agents to make the detection more difficult. Therefore, a more sensitive and fast detection scheme is highly desirable for the efficient detection of these low-rate flooding sources. In this paper, we focus on the low-rate agent and propose a router-based detection scheme for it. The proposed scheme is based on the TCP SYN-SYN/ACK protocol pair with the consideration of packet header information (both sequence and Ack. numbers). To make our scheme more sensitive and generally applicable, the Counting Bloom Filter is used to avoid the effect of SYNIACK retransmission and the Change Point Detection method is applied to avoid the dependence of detection on sites and access patterns. Extensive trace-driven simulation has been conducted to demonstrate the efficiency of the proposed scheme in terms of its detection probability and also average detection time.