We presented the author's SMCCSE (Social Media Cloud Computing Service Environment) that supports the development and construction of Social Networking Service (SNS) based on large amounts of social media including audio, video and image in earlier publication. The main contributions of this paper are to present how to design and implement Map Reduce-based image conversion module for social media transcoding and transmoding that are the core functions in our SMCCSE as well as to verify performance evaluation results for image conversion module. In this paper, we show a partially functional image conversion module based on Hadoop in SMCCSE except for video and audio. Moreover, we discuss experimental results performed on a 28 node SMCCSE cluster under varying experimental conditions in order to verify the performance for image conversion function.

IEEE 802.22 is the first worldwide Wireless Regional Area Networks (WRAN) standard based on cognitive radios (CR). In IEEE 802.22 WRAN, if a wireless microphone appears in any TV channel, the whole channel should be cleaned. 802.22 WRAN devices probably need to fractionally use the first adjacent channel for improving spectrum efficiency while ensuring no harmful interference is caused to the wireless microphone nearby. To determine the appropriate portion of the TV channel that WRAN can utilize, we firstly need to know the frequency location of wireless microphone. In this paper, we propose a two step DFT filter bank (TS-DFTFB) enhanced with an adaptive threshold method to detect the wireless microphone (WM). Comparing with conventional single step DFTFB, the TS-DFTFB method has low complexity while the detection precision is equal to single step DFTFB under the same condition. And with an adaptive method, the threshold can be kept very close to the noise power, which can increase the detection probability especially in the condition of low SNR.

In the recent years, there has been a growing interest in inferring the total order of genes or markers on a chromosome, since current genetic mapping efforts might only suffice to produce a partial order. Many interesting optimization problems were thus formulated in the framework of genome rearrangement. As an important one among them, the minimum breakpoint linearization (MBL) problem is to find the total order of a partially ordered genome that minimizes its breakpoint distance to a reference genome whose genes are already totally ordered. It was previously shown to be NP-hard, and the algorithms proposed so far are all heuristic. In this paper, we present an {m(2)+m/2}-approximation algorithm for the MBL problem, where m is the number of gene maps that are combined together to form a partial order of the genome under investigation.

Genome rearrangement is an important area in computational biology and bioinformatics. The translocation operation is one of the popular operations for genome rearrangement. It was proved that computing the unsigned translocation distance is NP-hard. In this paper, we present a (1.5 + epsilon)-approximation algorithm for computing unsigned translocation distance which improves upon the best known 1.75-ratio. The running time of our algorithm is O(n2 + (4/epsilon)1.5 square root log(4/epsilon )2(4/epsilon), where n is the total number of genes in the genome.

Traditional intrusion detection systems (IDSs) focus on low-level attacks or anomalies, and raise alerts independently, though there may be logical connections between them. In situations where there are intensive attacks, not only will actual alerts be mixed with false alerts, but the amount of alerts will also become unmanageable. As a result, it is difficult for human users or intrusion response systems to understand the alerts and take appropriate actions. This paper presents a sequence of techniques to address this issue. The first technique constructs attack scenarios by correlating alerts on the basis of prerequisites and consequences of attacks. Intuitively, the prerequisite of an attack is the necessary condition for the attack to be successful, while the consequence of an attack is the possible outcome of the attack. Based on the prerequisites and consequences of different types of attacks, the proposed method correlates alerts by (partially) matching the consequences of some prior alerts with the prerequisites of some later ones. Moreover, to handle large collections of alerts, this paper presents a set of interactive analysis utilities aimed at facilitating the investigation of large sets of intrusion alerts. This paper also presents the development of a toolkit named TIAA, which provides system support for interactive intrusion analysis. This paper finally reports the experiments conducted to validate the proposed techniques with the 2000 DARPA intrusion detection scenario-specific datasets, and the data collected at the DEFCON 8 Capture the Flag event.

Traditional intrusion detection systems (IDSs) focus on low-level attacks or anomalies, and raise alerts independently, though there may be logical connections between them. In situations where there are intensive attacks, not only will actual alerts be mixed with false alerts, but the amount of alerts will also become unmanageable. As a result, it is difficult for human users or intrusion response systems to understand the alerts and take appropriate actions. This paper presents a practical technique to address this issue. The proposed approach constructs attack scenarios by correlating alerts on the basis of prerequisites and consequences of attacks. Intuitively, the prerequisite of an attack is the necessary condition for the attack to be successful, while the consequence of an attack is the possible outcome of the attack. Based on the prerequisites and consequences of different types of attacks, our method correlates alerts by (partially) matching the consequences of some prior alerts with the prerequisites of some later ones. Moreover, to handle large collections of alerts, this paper presents three interactive analysis utilities aimed at reducing the complexity of the constructed attack scenarios without losing the structure of the attacks. This paper also reports the experiments conducted to validate the proposed techniques