Abstract—One of the serious threats to cyberspace is the Bot networks or Botnets. Bots are malicious software that acts as a network and allows hackers to remotely manage and control infected computer victims. Given the fact that DNS is one of the most common protocols in the network and is essential for the proper functioning of the network, it is very useful for monitoring, detecting and redu...

The DNS structure discloses useful information about the organization and the operation of an enterprise network, which can be used for designing attacks as well as monitoring domains supporting malicious activities. Thus, this paper introduces a new method for exploring the DNS domains. Although our previous work described a tool to generate existing DNS names accurately in order to probe a do...

Covert Channel are the methods to conceal a message in the volatile medium carrier such as radio signal and network packets. Until now, covert channels based on the packet length produce abnormal packet length when the length of the message is long. Abnormal packet length, especially in the normal network will expose the covert channels to network security perimeter. Therefore, it motivates the...

Objective: To evaluate the alpha amylase inhibitory activity of different extract of bark of Albizia lebbeck (L.) Benth. Methods: Bark of A. lebbeck was collected and air dried. Extraction of flavonoid, alkaloid and steroid carried out using standard methods. Extracts in different polar and non polar solvents were extracted using soxhlet method. Filtered extracts were subsequently tested for al...

In this study novel immunoconjugates were designed, synthesized and then used to develop a rapid, specific and sensitive indirect ELISA method to directly detect residues of 3,5-dinitrosalicyclic acid hydrazide (DNSH), a toxic metabolite of nifursol present in chicken tissues. The hapten DNSHA was first designed and used to covalently couple to BSA to form an immunogen which was immunized to ra...

Markov networks (MNs) are a powerful way to compactly represent a joint probability distribution, but most MN structure learning methods are very slow, due to the high cost of evaluating candidates structures. Dependency networks (DNs) represent a probability distribution as a set of conditional probability distributions. DNs are very fast to learn, but the conditional distributions may be inco...