Misuse detection for information retrieval systems

Cathey, Rebecca; Li, Ma; Goharian, Nazli; Grossman, David C.

doi:10.1145/956900.956901

Cited by 6 publications

(5 citation statements)

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“…There are also some attempts to detect the template of the web pages [10] for content extraction. The approach employed supervised classification models and needed a collection of training documents in order to train the classification models.…”

Section: Content Extraction Techniquesmentioning

confidence: 99%

Extracting Content in Regional Web Documents With Text Variations

Prakash¹,

Rangaswamy²

2014

Int. Jour. Info. Sci. Comp.

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The growth of the World Wide Web has led to a dramatic increase in accessible information. Today, people use Web for a large variety of activities including travel planning, comparison shopping, entertainment, and research. However, the tools available for collecting, organizing, and sharing Web content have not kept pace with the rapid growth in information. Today people continue to use bookmarks, email, and printers for managing Web content. Use of mobile phones has transformed the culture of communication with even villagers using sophisticated computer-related words like SMS and MBBS. But the major complexity arises when web documents in regional languages are displayed. Understanding the content of the document and later communication through oral or text means becomes difficult and this is the area the current paper addresses and in the process tries a generic concept-based mining model is proposed, for how the knowledge is created in the minds of illiterate user. The paper first presents how letters and words which form the basis of text-based communication can be used for content. The objective of this task is to achieve a concept-based term analysis on sentence and document levels rather than a single-term analysis in the document set only.

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Section: Content Extraction Techniquesmentioning

confidence: 99%

Extracting Content in Regional Web Documents With Text Variations

Prakash¹,

Rangaswamy²

2014

Int. Jour. Info. Sci. Comp.

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“…Such IDSes are the most widely used approach in the commercial IDS technology today. Moreover, abundant research efforts such as [17,30,3,6,24,21] also fall into this category.…”

Section: Limitations Of Existing Approachesmentioning

confidence: 99%

Enhancing Intrusion Detection System with proximity information

Zhuang¹,

Li²,

Chen³

2010

IJSN

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Abstract:The wide spread of worms poses serious challenges to today's Internet. Various IDSes (Intrusion Detection Systems) have been proposed to identify or prevent such spread. These IDSes can be largely classified as signature-based or anomaly-based ones depending on what type of knowledge the system knows. Signature-based IDSes are unable to detect the outbreak of new and unidentified worms when the worms' characteristic patterns are unknown. In addition, new worms are often sufficiently intelligent to hide their activities and evade anomaly detection. Moreover, modern worms tend to spread more quickly, and the outbreak period lasts in the order of hours or even minutes. Such characteristics render existing detection mechanisms less effective.In this work, we consider the drawbacks of current detection approaches and propose PAIDS, a proximity-assisted IDS approach for identifying the outbreak of unknown worms. PAIDS does not rely on signatures. Instead, it takes advantage of the proximity information of compromised hosts. PAIDS operates on an orthogonal dimension with existing IDS approaches and can thus work collaboratively with existing IDSes to achieve better performance. We test the effectiveness of PAIDS with trace-driven simulations and observe that PAIDS has a high detection rate and a low false positive rate. We also build a proof-of-concept prototype using Google Maps APIs and libpcap library.

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“…User profiles are of interest to many areas of research, including personalization [15,16,18], peer-to-peer information retrieval [9], malicious data access detection [4], and off-topic search detection [2]. The user profile may be represented in various ways, including (but not limited to) bag of words derived from persumably valid user queries [5,6], bag of words that map to the legitimate user behavior or organizational tasks [7,11], or topics (categories) mapping to the legitimate user interests [13,14].…”

Section: Prior Workmentioning

confidence: 99%

Improving classification based off-topic search detection via category relationships

Platt

Mengle

Goharian

2009

Proceedings of the 2009 ACM Symposium on Applied Computing

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The illegitimate access of documents by insiders (also known as off-topic search) is an increasingly prevalent and largely ignored problem. We propose an approach that uses text classification for off-topic search detection. Our empirical results indicate that offtopic search detection effectiveness improves by considering only a subset of documents that are retrieved for a given user query. Furthermore, we also show that the effectiveness of off-topic search detection improves by using the ontological information of document categories. Our empirical results demonstrate that utilizing sibling relationship information and relationships derived from misclassification information statistically significantly improves the results over the baseline in most cases.

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Misuse detection for information retrieval systems

Cited by 6 publications

References 0 publications

Extracting Content in Regional Web Documents With Text Variations

Extracting Content in Regional Web Documents With Text Variations

Enhancing Intrusion Detection System with proximity information

Improving classification based off-topic search detection via category relationships

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