Data Mining - Concepts and Techniques.

National Institute of Standards and Technology における超伝導研究及び生活

What makes organizations so similar? We contend that the engine of rationalization and bureaucratization has moved from the competitive marketplace to the state and the professions. Once a set of organizations emerges as a field, a paradox arises: rational actors make their organizations increasingly similar as they try to change them. We describe three isomorphic processes-coercive, mimetic, and normative—leading to this outcome. We then specify hypotheses about the impact of resource centralization and dependency, goal ambiguity and technical uncertainty, and professionalization and structuration on isomorphic change. Finally, we suggest implications for theories of organizations and social change.

The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields (Chinese Translation)

https://www.alaakhamis.org/teaching/MCT200/reading/Information%20Fusion.pdf

Multisensor data fusion: A review of the state-of-the-art

/pdf/social-psychology-handbook-of-basic-principles-5cncpuwpen.pdf

Social Psychology: Handbook of Basic Principles

Recent advances in wireless sensor networks (WSNs) have led to many new promising applications including habitat monitoring and target tracking However, data communication between nodes consumes a large portion of the total energy consumption of the WSNs Consequently, data aggregation techniques can greatly help to reduce the energy consumption by eliminating redundant data traveling back to the base station The security issues such as data integrity, confidentiality, and freshness in data aggregation become crucial when the WSN is deployed in a remote or hostile environment where sensors are prone to node failures and compromises There is currently research potential in securing data aggregation in the WSN With this in mind, the security issues in data aggregation for the WSN will be discussed in this paper Then, the adversarial model that can be used in any aggregation scheme will be explained After that, the "state-of-the-art" proposed secure data aggregation schemes will be surveyed and then classified into two categories based on the number of aggregator nodes and the existence of the verification phase Finally, a conceptual framework will be proposed to provide new designs with the minimum security requirements against certain type of adversary This framework gives a better understanding of those schemes and facilitates the evaluation process

Secure data aggregation in wireless sensor network: a survey

Detection and prevention of global navigation satellite system (GNSS) “spoofing” attacks, or the broadcast of false global navigation satellite system services, has recently attracted much research interest. This survey aims to fill three gaps in the literature: first, to assess in detail the exact nature of threat scenarios posed by spoofing against the most commonly cited targets; second, to investigate the many practical impediments, often underplayed, to carrying out GNSS spoofing attacks in the field; and third, to survey and assess the effectiveness of a wide range of proposed defences against GNSS spoofing. Our conclusion lists promising areas of future research.

A Survey and Analysis of the GNSS Spoofing Threat and Countermeasures

An exchange or payment protocol is considered fair if neither of the two parties exchanging items or payment at any time during the protocol has a significant advantage over the other entity. Fairness is an important property for electronic commerce. This paper identifies a design framework based on existing fair protocols which use offline trusted third parties, but with convertible signatures as the underlying mechanism. We show that in principle any convertible signature scheme can be used to design a fair payment protocol. A specific protocol is detailed based on RSA undeniable signatures which is more efficient than other similar fair payment schemes. Furthermore, in this protocol the final signature obtained is always an ordinary RSA signature.

/pdf/off-line-fair-payment-protocols-using-convertible-signatures-4euk4wkqp3.pdf

Off-Line Fair Payment Protocols Using Convertible Signatures

The main task of an intrusion detection system (IDS) is to detect anomalous behaviors from both within and outside the network system, and there have been increasing studies applying machine learning in this area. The limitations of using a single classifier in the classification of normal traffic and anomalies (attacks) led to the idea of building hybrid or ensemble models which are more complicated but provide higher accuracy and lower false alarm rate (FAR). The aim of this paper is to improve the performance of IDS by using ensemble methods and feature selection. The ensemble models were built based on the two ensemble techniques, Bagging and Boosting, with the tree-based algorithms as the base classifier. The proposed models were then evaluated using NSL-KDD datasets. The experimental results showed that the bagging ensemble model with J48 as the base classifier produced the best performance in terms of both classification accuracy and FAR when working with the subset of 35 selected features.

Ernest Foo

Papers

Secure data aggregation in wireless sensor network: a survey

A Survey and Analysis of the GNSS Spoofing Threat and Countermeasures

Off-Line Fair Payment Protocols Using Convertible Signatures

Improving performance of intrusion detection system using ensemble methods and feature selection

Off-line fair payment protocols using convertible signatures