Perancangan Program Aplikasi Kriptografi Menggunakan Algoritma Magenta dengan Panjang Kunci 128 Bit

Along with the development of computer technology, the growing crimes against the computer. Crimes against the computer makes people increasingly competing to make the algorithms-algorithms that can maintain the confidentiality of data. Algorithms algorithm Magenta is one of the many algorithms that exist today. Magenta algorithms have been developed since 1990 by using a simple and transparent technique that can be implemented in hardware and software. First time algorithms are analyzed using the butterfly structure - the structure of the butterfly which was then replaced by a Fast Hadamard Transform (FHT) shuffle structure which has the advantage of providing some structure in each level. In 1994 there was a slight change in the use of hardware that was not processed according to plan so that now the algorithm used by Deutsche Telekom Magenta for secure management of sensitive data with 128-bit key length. These algorithms break the 128-bit key length into 16 blocks with each block containing the 8-bit and one other advantage of this algorithm is the recursive part is calculated repeatedly at each iteration

PEMANFAATAN TEKNOLOGI HONEYPOT DALAM MENINGKATKAN AVAILABILITY PADA SISTEM JARINGAN

Abstrak: Tingkat ketersediaan data (Availability) merupakan hal yg mutlak yang harus disediakan oleh pihak penyedia data/informasi. Apa yang dibutuhkan oleh pengguna layanan IT harus dapat dipenuhi. Sehingga tingkat ketersediaan (availability) ini merupakan salah satu faktor yang harus diperhatikan dalam mencapai tingkat dari keamanan informasi. Honeypot merupakan sebuah teknologi yang bertindak sebagai umpan sehingga penyerang terjebak dalam melakukan serangannya. Hal ini dapat di ilustrasikan bahwa honeypot akan membuat server-server bayangan/palsu (fake) sebagai umpan. Setiap pergerakan dari jenis-jenis serangan tersebut dapat dipantau dan dianalisis hasilnya. Hasil akhir dari penelitian ini merupakan sebuah requirement (kebutuhan) teknologi honeypot yang sesuai dengan kondisi di Jurusan Teknik Informatika UNPAS. Kata kunci: Honeypot, Availability, Serve

Neural network based single index evaluation for SQL injection attack detection in health care data

In recent years, there are a lot of security risks in the network, and there is the combination intersection between the computer network security problems and security evaluation. The scale of computer network is very large with vast information, so there are many loopholes in the system network. At present, many have established a computer network security evaluation system to monitor the network security vulnerabilities, viruses, and defects in healthcare. However, many places simply analyzed the risk assessment of network security, but there is no assessment of network security situation. For the network security evaluation system, there is no complete evaluation system of network information security. Therefore, a network security evaluation system must be constructed to develop an effective and practical simulation model of computer network security evaluation. Through the simulation model, the effect of network security can be improved. Since the reform and opening up, the simulation of computer network security evaluation in our country is a new subject. It can directly study the network security evaluation, build a network security evaluation model, and study the network security in detail. In the computer network simulation system, it can analyze, study, design, and plan various stages, so as to play an important role

A middleware framework for secure mobile grid services.

Wong, Sze Wing.Thesis submitted in: October 2007.Thesis (M.Phil.)--Chinese University of Hong Kong, 2008.Includes bibliographical references (leaves 176-180).Abstracts in English and Chinese.Abstract --- p.i論文摘要 --- p.iiiAcknowledgements --- p.ivChapter 1 --- Introduction --- p.1Chapter 1.1 --- Contributions of this thesis --- p.3Chapter 1.2 --- Thesis structure --- p.4Chapter 2 --- Background --- p.6Chapter 2.1 --- Web Services --- p.6Chapter 2.2 --- Grid Computing --- p.8Chapter 2.2.1 --- Open Grid Services Architecture (OGSA) --- p.9Chapter 2.2.2 --- Grid Services --- p.9Chapter 2.3 --- Globus Toolkit --- p.10Chapter 2.3.1 --- Components of Globus Toolkit 4 --- p.11Chapter 2.3.2 --- Grid Security Infrastructure (GSI) --- p.13Chapter 2.4 --- Mobile Agent --- p.13Chapter 2.4.1 --- Foundation for Intelligent Physical Agents (FIPA) --- p.14Chapter 2.5 --- Java Agent Development Framework (JADE) --- p.15Chapter 2.5.1 --- JADE-S --- p.17Chapter 3 --- Research Issues in Mobile Grid Services --- p.18Chapter 3.1 --- Mobile Grid Services --- p.18Chapter 3.2 --- Service Migration --- p.20Chapter 3.2.1 --- Using Mobile Agent with Weak Mobility --- p.20Chapter 3.2.2 --- Using Mobile Agent with Strong Mobility --- p.21Chapter 3.2.3 --- Using Snapshots --- p.22Chapter 3.2.4 --- Summary --- p.23Chapter 3.3 --- Service Sharing and Discovery --- p.24Chapter 3.3.1 --- Centralized Model --- p.24Chapter 3.3.2 --- Division into clusters --- p.25Chapter 3.3.3 --- Using Web Services Protocols --- p.26Chapter 3.3.4 --- Summary --- p.27Chapter 3.4 --- Security --- p.28Chapter 3.4.1 --- Resource control and accounting --- p.28Chapter 3.4.2 --- Using delegation document --- p.30Chapter 3.4.3 --- Summary --- p.31Chapter 4 --- Mobile Grid Service Framework --- p.32Chapter 4.1 --- Proposed Framework Overview --- p.32Chapter 4.1.1 --- Service Migration --- p.33Chapter 4.1.2 --- Service Sharing and Discovery --- p.34Chapter 4.1.3 --- Security --- p.34Chapter 4.2 --- Overall architecture --- p.35Chapter 4.3 --- Components of Mobile Grid Services --- p.36Chapter 4.3.1 --- Agent Manager --- p.37Chapter 4.3.2 --- Task Agent --- p.38Chapter 4.3.3 --- Monitor Agent --- p.39Chapter 4.4 --- Resource Information Service --- p.40Chapter 4.5 --- Scenario of Mobile Grid Service Execution --- p.41Chapter 5 --- MGSAPI --- p.43Chapter 5.1 --- API design --- p.43Chapter 5.2 --- API Implementation --- p.45Chapter 5.2.1 --- Overview --- p.45Chapter 5.2.2 --- Agent Manager Class --- p.46Chapter 5.2.3 --- Task Agent Templates --- p.52Chapter 5.2.4 --- Configurable Monitor Agent --- p.57Chapter 5.2.5 --- Resource Information Service --- p.61Chapter 5.2.6 --- Example Application --- p.66Chapter 6 --- Security Support for Mobile Grid Services --- p.68Chapter 6.1 --- Overview --- p.68Chapter 6.2 --- Authentication and Authorization --- p.70Chapter 6.3 --- Message Integrity and Confidentiality --- p.72Chapter 6.4 --- Permissions on Agents --- p.74Chapter 6.5 --- Security facilities in MGS API --- p.76Chapter 6.5.1 --- Major modifications for MGS components --- p.77Chapter 6.5.2 --- MGS Security Libraries --- p.79Chapter 6.5.3 --- MGS Security Configuration --- p.81Chapter 7 --- Agent Protection for Mobile Grid Services --- p.83Chapter 7.1 --- Overview --- p.83Chapter 7.2 --- Major modifications --- p.86Chapter 7.2.1 --- Exempting checking for executions on home host --- p.86Chapter 7.2.2 --- New definition of stage --- p.87Chapter 7.2.3 --- Extra operations in Task Agent and Agent Manager --- p.88Chapter 7.2.4 --- Handling of attack --- p.88Chapter 7.3 --- Implementation details --- p.91Chapter 7.3.1 --- Agent Manager --- p.91Chapter 7.3.2 --- Task Agent --- p.97Chapter 7.3.3 --- Monitor Agent --- p.101Chapter 7.3.4 --- Checker --- p.102Chapter 7.4 --- Discussions --- p.108Chapter 7.4.1 --- Against modification of code and data --- p.108Chapter 7.4.2 --- Against masquerade --- p.108Chapter 7.4.3 --- Against fake information in trace --- p.109Chapter 7.4.4 --- Against escape from re-execution --- p.109Chapter 7.4.5 --- Against collaboration of different hosts --- p.109Chapter 7.4.6 --- Detection of malicious host --- p.110Chapter 7.4.7 --- Weaknesses --- p.110Chapter 8 --- Performance Evaluation --- p.111Chapter 8.1 --- Experimental Setup --- p.111Chapter 8.2 --- MGS Performance --- p.117Chapter 8.2.1 --- Experiment details --- p.112Chapter 8.2.2 --- Experiment results --- p.113Chapter 8.2.3 --- Discussions --- p.116Chapter 8.3 --- MGS Overheads --- p.117Chapter 8.3.1 --- Experiment details --- p.117Chapter 8.3.2 --- Experiment results --- p.119Chapter 8.3.3 --- Discussions --- p.123Chapter 8.4 --- Agent Protection Overheads --- p.124Chapter 8.4.1 --- Experiment details --- p.124Chapter 8.4.2 --- Experiment results --- p.125Chapter 8.4.3 --- Discussions --- p.128Chapter 9 --- Conclusion and Future Works --- p.130Appendix A Administrator Guide for MGS API --- p.132Chapter A.l --- Installation of MGS API --- p.132Chapter A.1.1 --- Installation of pre-requisites --- p.132Chapter A.1.2 --- Installation of MGS API library --- p.135Chapter A.2 --- Setup of MGS platform --- p.135Chapter A.2.1 --- Setup of JADE platform --- p.135Chapter A.2.2 --- Setup of Globus containers --- p.136Appendix B Developer Guide for MGS API --- p.137Chapter B.1 --- Steps of developing a Mobile Grid Service --- p.137Chapter B.1.1 --- Design Mobile Grid Service --- p.137Chapter B.1.2 --- Define WSDL --- p.138Chapter B.1.3 --- Implement the service --- p.138Chapter B.1.4 --- Configure deployment in WSDD --- p.138Chapter B.1.5 --- Compile and deploy the service --- p.139Chapter B.2 --- Mobile Grid Service Implementation --- p.140Chapter B.2.1 --- Implement Task Agent --- p.140Chapter B.2.2 --- Implement Monitor Agent (optional) --- p.143Chapter B.2.3 --- Implement Agent Manager --- p.144Chapter B.3 --- Convert tool --- p.146Chapter B.4 --- Service configuration --- p.147Chapter B.4.1 --- TaskSetting object --- p.147Chapter B.4.2 --- MonitorSetting object --- p.147Chapter B.4.3 --- MGS Configuration file --- p.148Chapter B.4.4 --- Configuration for Resource Information Service --- p.149Chapter B.4.5 --- Globus-side security configuration of the service --- p.151Chapter B.5 --- MGS Configuration Helper --- p.151Chapter B.5.1 --- “Main Container´ح Panel --- p.152Chapter B.5.2 --- “Container´ح Panel --- p.154Chapter B.5.3 --- “Service´ح Panel --- p.156Chapter B.6 --- Interface details --- p.158Chapter B.6.1 --- Package mgs.manager --- p.158Chapter B.6.2 --- Package mgs.monitor --- p.165Chapter B.6.3 --- Package mgs.task --- p.167Chapter B.6.4 --- Package mgs.ftsFramework --- p.174Bibliography --- p.176Publications --- p.18

Standards and practices necessary to implement a successful security review program for intrusion management systems

Thesis (Master)--Izmir Institute of Technology, Computer Engineering, Izmir, 2002Includes bibliographical references (leaves: 84-85)Text in English; Abstract: Turkish and Englishviii, 91 leavesIntrusion Management Systems are being used to prevent the information systems from successful intrusions and their consequences. They also have detection features. They try to detect intrusions, which have passed the implemented measures. Also the recovery of the system after a successful intrusion is made by the Intrusion Management Systems. The investigation of the intrusion is made by Intrusion Management Systems also. These functions can be existent in an intrusion management system model, which has a four layers architecture. The layers of the model are avoidance, assurance, detection and recovery. At the avoidance layer necessary policies, standards and practices are implemented to prevent the information system from successful intrusions. At the avoidance layer, the effectiveness of implemented measures are measured by some test and reviews. At the detection layer the identification of an intrusion or intrusion attempt is made in the real time. The recovery layer is responsible from restoring the information system after a successful intrusion. It has also functions to investigate the intrusion. Intrusion Management Systems are used to protect information and computer assets from intrusions. An organization aiming to protect its assets must use such a system. After the implementation of the system, continuous reviews must be conducted in order to ensure the effectiveness of the measures taken. Such a review can achieve its goal by using principles and standards. In this thesis, the principles necessary to implement a successful review program for Intrusion Management Systems have been developed in the guidance of Generally Accepted System Security Principles (GASSP). These example principles are developed for tools of each Intrusion Management System layer. These tools are firewalls for avoidance layer, vulnerability scanners for assurance layer, intrusion detection systems for detection layer and integrity checkers for recovery layer of Intrusion Management Systems

Automation of a Remote Telescope Imaging System

SRI International is working with the High Frequency Active Auroral Research Project to develop instrumentation for researching the properties of the ionosphere. The project team developed a web-based interface that allows remote control of an optical imaging system located in Alaska. The interface provides control of the on-site cameras, optics, and mount for researchers at SRI. Data that is collected by the system is returned to SRI autonomously. The project concluded with on-site testing of the system

Analysis Of Aircraft Arrival Delay And Airport On-time Performance

While existing grid environments cater to specific needs of a particular user community, we need to go beyond them and consider general-purpose large-scale distributed systems consisting of large collections of heterogeneous computers and communication systems shared by a large user population with very diverse requirements. Coordination, matchmaking, and resource allocation are among the essential functions of large-scale distributed systems. Although deterministic approaches for coordination, matchmaking, and resource allocation have been well studied, they are not suitable for large-scale distributed systems due to the large-scale, the autonomy, and the dynamics of the systems. We have to seek for nondeterministic solutions for large-scale distributed systems. In this dissertation we describe our work on a coordination service, a matchmaking service, and a macro-economic resource allocation model for large-scale distributed systems. The coordination service coordinates the execution of complex tasks in a dynamic environment, the matchmaking service supports finding the appropriate resources for users, and the macro-economic resource allocation model allows a broker to mediate resource providers who want to maximize their revenues and resource consumers who want to get the best resources at the lowest possible price, with some global objectives, e.g., to maximize the resource utilization of the system