A Protocol Test Generation Procedure.

This first chapter intends to review and analyze the powerful new Harmony Search (HS) algorithm in the context of metaheuristic algorithms. We will first outline the fundamental steps of HS, and show how it works. We then try to identify the characteristics of metaheuristics and analyze why HS is a good metaheuristic algorithm. We then review briefly other popular metaheuristics such as particle swarm optimization so as to find their similarities and differences with HS. Finally, we will discuss the ways to improve and develop new variants of HS, and make suggestions for further research including open questions.

Music-Inspired Harmony Search Algorithm

A survey of combinatorial optimization problems in multicast routing

Harmony search based algorithms for bandwidth-delay-constrained least-cost multicast routing

Wiresharkパケット解析リファレンス : Network Protocol Analyzer

With the proliferation of multimedia group applications, the construction of multicast trees satisfying quality of service (QoS) requirements is becoming a problem of prime importance. Many of the multicast applications (such as video broadcasts and teleconferencing) require the network to support dynamic multicast sessions wherein the membership of the multicast group changes with time. In this paper, we propose and evaluate an algorithm called CRCDM (controlled rearrangement for constrained dynamic multicasting) for on-line update of multicast trees to adjust to changes in group membership. The CRCDM algorithm is based on a concept called quality factor (QF) that represents the usefulness of a portion of the multicast tree to the overall multicast session. When the usefulness of a particular region of the tree drops below a threshold, a rearrangement technique is used to suitably modify the tree. Our algorithm aims to satisfy the delay constraints of all current group members, at the same time minimizing the cost of the constructed tree. We compare the performance of our algorithm, by simulation, with that of an off-line Steiner heuristic; with ARIES, a previously published algorithm for on-line update of unconstrained trees; and with the algorithm proposed by Hong, Lee and Park (see Proc. IEEE INFOCOM, p.1433-40, 1998) for on-line update of delay-constrained trees. The simulation results indicate that our algorithm provides excellent cost-competitiveness that is better than that provided by the algorithm described by Hong et al., minimizes changes in the multicast tree after each update, and performs favorably even when compared with the unconstrained ARIES heuristic.

A rearrangeable algorithm for the construction of delay-constrained dynamic multicast trees

Traditionally, sources of digital evidence are analyzed by individually examining the various artifacts contained therein and using the artifact metadata to validate authenticity and sequence them. However, when artifacts from forensic images, folders, log files, and network packet dumps have to be analyzed, the examination of the artifacts and the metadata in isolation presents a significant challenge. Ideally, when a source is examined, it is a valuable task to determine correlations between the artifacts and group the related artifacts. Such a grouping can simplify the task of analysis by minimizing the need for human intervention. By virtue of the value that metadata bring to an investigation and its ubiquitous nature, metadata based associations is the first step in realizing such correlations automatically during analysis. In this paper, we present the AssocGEN analysis engine which uses the metadata to determine associations between artifacts that belong to files, logs and network packet dumps, and identifies metadata associations to group the related artifacts. A metadata association can represent any type of value match 1 or relationship that is deemed relevant in the context of an investigation. We have conducted preliminary evaluation of AssocGEN on the classical ownership problem to highlight the benefits of incorporating this

https://securecyberspace.org/yahoo_site_admin/assets/docs/DF_5998_Paper_IEEE.232152223.pdf

AssocGEN: Engine for analyzing metadata based associations in digital evidence

There are a wide range of forensic and analysis tools to examine digital evidence in existence today. Traditional tool design examines each source of digital evidence as a BLOB (binary large object) and it is up to the examiner to identify the relevant items from evidence. In the face of rapid technological advancements we are increasingly confronted with a diverse set of digital evidence and being able to identify a particular tool for conducting a specific analysis is an essential task. In this paper, we present a systematic study of contemporary forensic and analysis tools using a hypothesis based review to identify the different functionalities supported by these tools. We highlight the limitations of the forensic tools in regards to evidence corroboration and develop a case for building evidence correlation functionalities into these tools. Keywords— Digital evidence, Binary abstraction, File system and schema support, Metadata, Evidence composition

https://securecyberspace.org/yahoo_site_admin/assets/docs/DF_5994_Paper_IEEE.232152154.pdf

A study of forensic & analysis tools

In the conventional system of analysis that is concerned with digital forensics, content is analyzed to describe the state of files in digital evidence and ascertain their relevance. Such content analysis is carried out using “searching”. When searching a file or for a file, use of keywords is the norm. When the exact words are not known, one may use regular expression search which uses a more flexible language for describing a set of keywords that fit a pattern. During analysis, there is also a need to identify all types of associations that exist between the files to answer the six fundamental questions of what, when, where, how, who and why. If the keywords and pattern have limited scope, an examiner often has very little to go on. Metadata contains information that represents the state of a file, even if partially. Besides, metadata based search is amenable to automation by virtue of the ubiquitous nature of metadata. During analysis, metadata can be used to ascertain the nature of digital photographs that were processed using software and identify digitally generated images that resemble original photographs. Metadata can also be used to identify word processing documents that were derived from other documents and stored as a duplicate or after modification in such a way that traditional techniques cannot detect. Often what is needed is the ability to identify section(s) of the evidence where relevant information appears to reside. Metadata based matches give rise to file relationships that encapsulate the event sequence among related files aiding in the discovery. This paper proposes a method to automatically identify associations among the files in digital evidence at the syntactic and semantic levels using metadata. We apply this method to identify metadata associations from collections of image files and word processing documents and elicit inter-file relationships for the purpose of identifying interesting or relevant files from large file collections in digital evidence. We demonstrate that the file relationships identified using metadata help in the identification of doctored photographs and copied documents.

/pdf/eliciting-file-relationships-using-metadata-based-1qkix33h4q.pdf

Eliciting file relationships using metadata based associations for digital forensics

Internet browsers support multiple browser tabs, each browser tab capable of initiating and maintaining a separate web session, accessing multiple uniform resource identifiers (URIs) simultaneously. As a consequence, network traffic generated as part of a web request becomes indistinguishable across tabbed sessions. However, it is possible to find the specificity of attribution in the session-related context information recorded as metadata in log files (in servers and clients) and as network traffic related logs in routers and firewalls, along with their metadata. The forensic questions of “who,” “what” and “how” are easily answered using the metadata-based approach presented in this chapter. The same questions can help systems administrators decide on monitoring and prevention strategies. Metadata, by definition, records context information related to a session; such metadata recordings transcend sources.

/pdf/reconstructing-tabbed-browser-sessions-using-metadata-ct9jo0eai5.pdf

S. V. Raghavan

Papers

A rearrangeable algorithm for the construction of delay-constrained dynamic multicast trees

AssocGEN: Engine for analyzing metadata based associations in digital evidence

A study of forensic & analysis tools

Eliciting file relationships using metadata based associations for digital forensics

Reconstructing Tabbed Browser Sessions Using Metadata Associations