Top PDF Intrusion into the computer networks and information systems

Intrusion into the computer networks and information systems

Intrusion into the computer networks and information systems

Još jedna metoda istraživanja je korištenje Linux Kali alata da se napravimo kopija web stranice. HTT rack je besplatan program koji stvara identičnu, off-line kopiju ciljane web stran[r]

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Intelligent Intrusion Detection In Computer Networks Using Fuzzy Systems

Intelligent Intrusion Detection In Computer Networks Using Fuzzy Systems

In this paper, we focused on intrusion detection in computer networks by combination of fuzzy systems and PSO algorithm. The proposed method performs the classification task and extracts required knowledge using fuzzy rule based systems which consists of fuzzy if-then rules. Particle Swarm Optimization algorithm is employed to optimize the obtained set of fuzzy rules. The proposed system has two main features of data mining techniques which are high reliability and adequate interpretability, and is comparable with several well-known algorithms. Results on intrusion detection data set from KDD cup-99 repository show that the proposed approach would be capable of classifying intrusion instances with high accuracy rate in addition to adequate interpretability of extracted rules.
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Efficient Working of Signature Based Intrusion Detection Technique in Computer Networks

Efficient Working of Signature Based Intrusion Detection Technique in Computer Networks

that are stored into the database to detect the attacks in the computer system. Signature based IDS suffer from the huge number of signatures stored in its database [4]. Some researchers provided the concept of frequent signature database to solve database size problem but never discussed how to deal with new signatures and the old signature that became unnecessary. In a signature based detection a predetermined attack patterns in the form of signatures and these signatures are further used to determine the network attacks [5].They usually examine the network traffic with predefined signatures and each time database is updated. An example of Signature based Intrusion Detection System is SNORT.
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Intelligent Intrusion Detection in Computer Networks using Swarm Intelligence

Intelligent Intrusion Detection in Computer Networks using Swarm Intelligence

In the data preparation step, the original data set or input data which consists of collections of processes and their associated system calls is being prepared and transformed into smaller data blocks. Grouping of system calls and processes occurs among system calls which are associated with the same process and thus transformed into one. Along with the frequency of each individual system call in each trace is calculated at the same step. The reduction and feature extraction takes place on this reduced data block of original data and is computed against the trained data with iterative updating algorithm in Eq. (2) and Eq. (3) which is proposed by the NMF to generate a new form of data which represents the features. At the last step, these features are used to tell whether the intrusion is detected a process or not. If the data vector corresponds to normal behaviours, the sum of all the elements in the data vector should be approximately equal to number 1, if not then it is treated as anomalous and it can be said that intrusion has occurred and an anomaly index is generated against the process denoting the deviation it shows from the normal behaviour and to show that intrusion has occurred in it.
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Intrusion and anomaly detection in computer networks using signal processing approaches

Intrusion and anomaly detection in computer networks using signal processing approaches

Another shortcoming network monitoring tools is that very high level information is displayed, which without the detail that creates the information can be of little use. On the other side too much data can be overwhelming for the person inspecting it and potential problems could be missed. A solution for this problem could be applying some signal processing techniques to this data to attempt to extract useful data. There is a large number of commercially available anomaly detection software packages available, but they are both expensive and quite often the inner workings of the system are kept confidential. This in mind, the approach to this paper is to provide the a basic open- source system that could be easily implemented at low cost. Although not covered in this project, a real-time implementation of this system would be the end goal. An open-source system would also allow it to improved over time as well.
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A Comprehensive Teaching Reform Model for a Computer Networks Course Based on Integrated Information Systems

A Comprehensive Teaching Reform Model for a Computer Networks Course Based on Integrated Information Systems

The development of "Academic-Practical" teachers characterized by high quality professional standards is an important guarantee contributing to improvement in the quality of education. In practice, in addition to attaching importance to the training and continuing education of existing professional teachers and improving their profes- sional skills at the level of theory and practice, it was also necessary to address the motivation of teachers and stimulate their career enthusiasm. The following four prac- tical cases are provided for reference. First, through the talent introduction policy, senior engineers with extensive experience in network equipment research & devel- opment and IT project management were enrolled and appointed to take charge of laboratory construction and the engineering practice teaching. The addition of these engineers strengthened the applied engineering capabilities of the network engineer- ing teaching and research department. Second, teachers were encouraged to actively apply for teaching reform projects, such as the School-Enterprise Cooperative Educa- tion Project of the Ministry of Education of China, which will offer additional points in the evaluation for academic titles and offer preferential teaching awards. Third, there was a great deal of work done behind the scenes in curriculum reform, such as developing the information system, guiding students, coming up with teaching cases and so on. This part of the behind the scenes work was identified and quantified into the workload. Spiritual encouragement was prioritized, supplemented by appropriate material rewards, so that teachers could be recognized and respected. Finally, teachers were encouraged to take qualification and competency tests related to teaching, such as the Cisco Network Engineer Certification Training and Examination. The fees for training and certification are supported by special funds for teacher development. The enthusiasm of teachers has been stimulated by the above-mentioned methods, and they actively participate in the reforms and engineering practice, so as to improve their teaching at the theoretical level and their capabilities in engineering professional practice.
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Recommended Course Sequence. Computer Information Systems. Computer Information Systems Major. First Semester Credits. Second Semester.

Recommended Course Sequence. Computer Information Systems. Computer Information Systems Major. First Semester Credits. Second Semester.

This course introduces basic concepts, architecture, and widely used protocols of computer networks. Topics include the Open System Interconnection (OSI) model consisting of physical link layer, data layer, network layer, transport layer, session layer, presentation layer, and application layer, the medium access sublayer and LAN, various routing protocols, Transmission Control Protocol (TCP), and Internet Protocol (IP) for internetworking.

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COMPUTER INFORMATION SYSTEMS

COMPUTER INFORMATION SYSTEMS

Immerses IT Professionals in hands-on intensive environment providing in-depth knowledge and experience with current essential security systems. Provides understanding of perimeter defenses and leads to scanning and attacking networks; no real networks are harmed. Students learn how intruders escalate privileges and the steps to be taken to secure a system. Also covers Intrusion Detection, Policy Creation, Social Engineering, DDoS Attacks, Buffer Overflows, and Virtual Creation. Focus includes legal and regulatory requirements, ethical issues, basic methodology and technical tools used for ethical hacking and penetration tests. Students establish a pre-test agreement with the enterprise, discover and exploit vulnerabilities, participate as a member of a pen test team and prepare a penetration test report. (CSU)
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Intrusion Detection in Computer Network

Intrusion Detection in Computer Network

Continuous spreading and growing bandwidth of computer networks brings many security threats. Intrusion Detection System (IDS) is a mean to provide network security. Software IDS aplications gain only low throughput and that is why hardware accelerators are under heavy development. Probe Traffic Scanner is a hardware accelerator developed in Liberouter project with use of FPGA technology. Main core of acceleration is searching packet pay- load for simple suspicious strings. Regular expressions provide complex way of describing strings. This bachelor thesis adds feature of searching according to Perl Compatible Regu- lar Expressions (PCRE) to Traffic Scanner Probe by implemented transformer. In addition design and implementation of control software allowing users to use functions provided by the Probe have been created. Conception of intrusion detection in network utilizing Traffic Scanner is outlined so as possibilities of cooperation with other security devices.
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Intrusion detection systems for IP telephony networks

Intrusion detection systems for IP telephony networks

By using a computer for communication, especially trough a network, identification by wire is lost. Instead a identification by computer or by user ID can take place. Both can be attacked as they are based on transmitted data. Computer networks offer numerous points of attack. Tools for spoofing can be used to act as another calling party. In [ASRS01] security issues are discussed in more detail. Intrusion detection is a widely accepted technology to address security problems in computer networks (see e.g. [SBD+91]). But, compared to most computer networks secured by an intrusion detection system (IDS), a telephony network is much more complex:
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Effectiveness of Intrusion Prevention Systems (IPS) in Fast Networks

Effectiveness of Intrusion Prevention Systems (IPS) in Fast Networks

ASIER connectivity to different networks of comput- ers is a major reason of recent advancements in net- works and communication infrastructures. More and more companies are making huge investments into online applications and services. People are also keen to make use of these online systems for getting more convenience and ease of use. In addition of easier and cheaper availa- bility of Internet, research and heavy financial invest- ments have made networks very fast. Fast networks and highly available Internet facility is a best combination for online business activities. More bandwidth is available now for online applications making them faster and offer- ing higher data rates. Heavy volume of network can con- tain any kind of malicious contents that can destroy inte- grity and credibility of our information systems. Accord- ing to [3], for any business organization; information is as important as capital and loss or theft of information can bring unbearable financial consequences to the organiza- tion.
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Using the Pattern-of-Life in Networks to Improve the Effectiveness of Intrusion Detection Systems

Using the Pattern-of-Life in Networks to Improve the Effectiveness of Intrusion Detection Systems

In [15], we proposed a novel BPA methodology able to automatically adapt the assignment of its evidence to the current characteristics of the network traffic, without intervention from an IDS administrator. The proposed BPA methodology exploits a Sliding Window (SW) scheme to compute statistical parameters from the data and generate the different BPA values. Three independent statistical approaches provide, for each analysed metric, the belief values on the different hypotheses. The approach that assigns BPA values to the hypothesis Normal uses the distribution of the network traffic within the SW. The approach that assigns BPA values to the hypothesis Attack uses the Euclidean distance from a defined reference of normality (i.e. mean of information within the SW). Meanwhile, the BPA in the hypothesis Uncertainty is assigned based on the belief values assigned to Normal and Attack in the current SW. Once these values have been generated, the different BPA values are fused using D-S theory. The BPA in Normal and BPA in Attack indicate how strong the belief is that the current analysed data is non-malicious and malicious, respectively, whereas, the BPA in
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Intrusion Detection Systems for Community Wireless Mesh Networks

Intrusion Detection Systems for Community Wireless Mesh Networks

It is relatively straightforward to introduce new infras- tructure to a WMN that could be used for malicious pur- poses, for example, to instigate a phishing attack [17]. There are protocols that can be deployed to make this more difficult to achieve (e.g., WPA2 Enterprise Mode [4]), but they are rarely enabled. Furthermore, providing account- ability is challenging because it is easy for a user to join or add infrastructure to the network. Even authenticated users may be difficult or prohibitively expensive to trace. This lack of accountability and traceability reduces the risk of behaving maliciously, suggesting that information from dis- tributed sensors regarding malicious activity (or a suggested lack of activity) cannot be inherently trusted. For example, false information about the existence of an attack could be used to orchestrate a Denial of Service (DoS) attack as a re- sult of a remediation activity (e.g., modifications to firewall rules could block access to legitimate services as a result of bogus information). In summary, a developer of an IDS for a community WMN cannot inherently trust the information it will receive for detection activities, and measures should be taken to address this problem.
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Security of Computer Systems and Networks Book Preview

Security of Computer Systems and Networks Book Preview

cryptographic tunnels will protect your network from outsiders. But you still have a problem with semi-outsiders and insiders including their mutual collaboration. And with the hackers that will exploit any known vulnerability in your security configuration. So what shall you do? You set up an intrusion detection/prevention system (IDS/IPS) that sends alerts on suspicious activities that are invisible to firewalls. This chapter covers these systems – their basics and classification according to different criteria (what and where they do their job and how they detect intrusions) and the theory behind them (true/false positives/negatives, sensitivity, specificity, accuracy, ROC and predictive values). Snort is briefly explained (its structure and configuration) as an open-source solution and the de-facto IDS standard. Aside from Snort, Fortego All-Seeing Eye is also briefly described as a very strict after-the fact Windows IDS that requires some initial training. This chapter introduces a new IDS system for wireless networks (WIDS) that has been developed by one of authors. The use of artificial intelligence in IDS/IPS systems is briefly discussed in this chapter and is, in parts, a novelty of authors.
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Neural networks in intrusion detection systems

Neural networks in intrusion detection systems

Abstract: Security of an information system is its very important property, especially today, when computers are interconnected via internet. Because no system can be absolutely secure, the timely and accurate detection of intrusions is necessary. For this purpose, Intrusion Detection Systems (IDS) were designed. There are two basic models of IDS: misuse IDS and anomaly IDS. Misuse systems detect intrusions by looking for activity that corresponds to the known signatures of intrusions or vulnerabilities. Anomaly systems detect intrusions by searching for an abnormal system activity. Most IDS commercial tools are misuse systems with rule-based expert system structure. However, these techniques are less successful when attack characteristics vary from built-in signatures. Artificial neural networks offer the potential to resolve these problems. As far as anomaly systems are concerned, it is very difficult to build them, because it is difficult to define the normal and abnormal behaviour of a system. Also for building anomaly system, neural networks can be used, because they can learn to discriminate the normal and abnormal behaviour of a system from examples. Therefore, they offer a promising technique for building anomaly systems. This paper presents an overview of the applicability of neural networks in building intrusion systems and discusses advantages and draw- backs of neural network technology.
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Computer & Intrusion Forensics pdf

Computer & Intrusion Forensics pdf

tools required at various stages of an examination which do not fall neatly into one or other of these categories. Earlier sections focused upon imaging and analysis, here we list briefly some of the important additional capabilities that need to be provided, capabilities such as link analysis which relates data from separate files or sources, and provides an effective visualization of that information. These tools rely in turn upon time-lining tools and sophisti- cated search engines with fuzzy logic capability (e.g., NTI’s IPFilter program, which can identify patterns of text associated with prior Internet activities). Link analysis explores and visualizes the key nodes and structures within a data network (i.e., a collection of related data). It is an important tool for exploring relationships in data when investigating complex cases such as fraud that involve large volumes of data such as e-mail or audit data. Link analysis examines a large number of potentially dissimilar records of data and establishes links among those records based on data fields with identical or related values using artificial intelligence (AI) techniques such as heuristic methods to find the links between the records [45]. This bottom-up approach to constructing networks is quite different to techniques that rely on statistical methods. A good introduction to the concept of link analysis can be found at [46]. One of the best known link analysis tools used in computer forensics is the Analyst’s Notebook from i2 Inc. [47]. Analyst’s Notebook is a link analysis and data visualization product that has been used in criminal and fraud investigations worldwide. It consists of two main tools, one for link analysis and one for case management. The latter also provides a time-line analysis capability, a capability whose importance cannot be over- estimated. Time-lining is a recurring theme in this chapter (Section 2.4.1) and Chapters 3, 4, and 6. Both EnCase [32] and CFIT [48] examined in Section 2.3 support time-lining. The case studies listed on the i2 site include New Scotland Yard and the Gloucester Police as two users of the Analyst’s Notebook [49]; in addition, the FBI has recently signed a $2 million contract with i2 while the U.S. Postal Inspection Service is also a user of this tool. Netmap is a link analysis tool widely used by LE in the United States [50] while Watson from Xanalys [51] is also widely used for link analysis and data visualization in both LE and in the finance sector. The latter was successfully used recently by the Durham Police (United Kingdom) to analyze over 4,000 e-mail messages as part of a child pornography investigation, leading to a heavier conviction against the offender.
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Intrusion Detection Systems for the Availability  Attacks in Ad-Hoc Networks

Intrusion Detection Systems for the Availability Attacks in Ad-Hoc Networks

An Ad hoc network is an independent system where in routers are connected by wireless links-the union of which form an arbitrary graph. The routers are free to move randomly and organize themselves arbitrarily; thus, the network’s wireless topology may change rapidly and unpredictably. Such network may operate independently or may be connected to larger internet operating as a Ad hoc network [1].It is an infrastructure-less network [2]. In this, individual network is constructed and nodes of this network forward packets to and from each other. Due to node mobility, network topology changes frequently So it is important to manage routing information efficiently. To make cooperation between nodes procedure feasible, Trust between nodes is necessary. This network is flexible so it introduces new security risks. Intrusion detection System (IDS), which is an essential part of a security system, also presents challenges due to the dynamic nature of Ad hoc networks. Here in this paper we have mentioned details of availability attacks in Ad hoc networks.
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Intrusion detection systems for intra vehicle networks : a review

Intrusion detection systems for intra vehicle networks : a review

Young et al. [24] introduced a road map towards a security solution for intra-vehicle networks. The pro- posed solution can detect anomalies, identify failed states of the network, and adaptively respond in real- time to maintain a fail-operational system. The authors argued that observing message sequences is essential to detect semantic attacks that span multiple state transi- tion. Based on the observation that control messages are high priority, periodic and predictable messages, the proposed IDS partitions incoming messages into control and non-control messages. It then uses an algo- rithm to examine the control messages exploiting the high predictability of such messages and a kernel-based Machine Learning (ML) algorithm to detect sequential anomalies. However, generally speaking, kernel-based models have a substantial time complexity, deterio- rating their efficiency for intrusion detection tasks in vehicular systems. In addition, such an approach is not applicable to aperiodic messages (e.g., even-driven messages), as the high variability of such messages might lead to a high number of false positives. Cho and Shin [25] built an effective IDS called Clock- based Intrusion Detection System (CIDS), which can detect various types of attack including the masquer- ade attack. Since the CAN protocol does not provide the identity of the transmitter in the CAN message, the authors fingerprinted ECUs with other ‘‘leaked’’ information. The authors exploited message periodic- ity to extract and estimate transmitters’ clock skews, which can be used to fingerprint the transmitter ECUs. The total amount of offset (the accumulated clock off- set) is obtained by summing up the absolute values of the average clock offsets. By definition, the slope of the accumulated clock offset would thus represent the clock skew, which is constant. This enables the proposed CIDS to estimate the clock skew from arrival timestamps and thus fingerprint the message transmit- ter for intrusion detection.
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Characterizing violations in computer and information security systems

Characterizing violations in computer and information security systems

Although these expert opinions and studies observe the role of violations by CIS end users, network administrators, and managers, they have not fully taken into account how the work system or work environment contributes to the behavior or decisions. For example, network administrators may have to work with and satisfy many user groups. Kraemer and Carayon [11] studied how various work system elements propagate human error and violations and consequently, CIS vulnerabilities. They interviewed 10 network administrators and 10 CIS managers to obtain descriptions of the types of violations committed by end users and network administrators. For example, network administrators intentionally reconfigure firewalls in ways that may introduce vulnerabilities, so that outsiders who are collaborating on projects can have access to their networks. They may do this because of the lack of set procedures or rules that have been agreed upon by the user groups, or, they may be so overworked and pressed for time that allowing holes in the firewalls is the quickest and easiest way to complete their tasks. Further, network administrators tended to view errors created by end users as more intentional than unintentional (i.e. end users commit more violations than unintentional error), while errors created by network administrators as more unintentional than intentional (i.e. network administrators commit more unintentional errors than violations). Lastly, organizational factors, such as communication, security culture, policy, and organizational structure, were the most frequently cited work system factors associated with CIS.
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Seidenberg School of Computer Science and Information Systems

Seidenberg School of Computer Science and Information Systems

Every day something new happens in the field of telecommunica- tions. In an increasingly interconnected world, telecommunications professionals need both a strong foundation and the skills and knowledge to foster innovation. No program provides a greater understanding of the field of telecommunications than the Pace Master of Science in Telecommunications Systems and Networks. Specifically designed to offer students a comprehensive and multifaceted education in computer networking and telecommuni- cations, this curriculum covers all the significant aspects including technology, management, and policy. It emphasizes current and emerging Internet-related technologies and applications. The broad nature of the program is ideal for those who wish to enter the field of telecommunications, or current professionals looking for that edge to stay ahead in this ever-changing industry.
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