Toward Taming the Overhead Monster for Data-flow Integrity

Data-Flow Integrity (DFI) is a well-known approach to effectively detecting a wide range of software attacks. However, its real-world application has been quite limited so far because of the prohibitive performance overhead it incurs. Moreover, the overhead is enormously difficult to overcome without substantially lowering the DFI criterion. In this work, an analysis is performed to understand the main factors contributing to the overhead. Accordingly, a hardware-assisted parallel approach is proposed to tackle the overhead challenge. Simulations on SPEC CPU 2006 benchmark show that the proposed approach can completely enforce the DFI defined in the original seminal work while reducing performance overhead by 4×, on average.

SISTEM INFORMASI ASET ORGANISASI MUHAMMADIYAH CABANG MINGGIR YOGYAKARTA BERBASIS WEBSITE

Kebutuhan Informasi aset Organisasi Muhammadiyah Cabang Minggir saat ini dilakukan dengan meminta kepada pengelola amal usaha untuk aset data. Akibatnya Pimpinan Cabang tidak bisa mendapatkan informasi aset secara langsung saat dibutuhkan. Untuk mengatasi masalah tersebut, peneliti mencoba menganalisis dan membangun sistem informasi organisasi aset menggunakan metode pengembangan sistem informasi SDLC (Systems Development Life Cycle) dengan model Waterfall, desain model proses DFD (Data Flow Diagram), desain model data ERD (Entity Relationship Diagram), desain antarmuka, dan desain database. Aplikasi yang dihasilkan berupa prototype sistem informasi aset yang akan digunakan Pimpinan Cabang untuk inventarisasi aset. Aplikasi berbasis website responsif yang fleksibel untuk diakses dari segi waktu dan tempat serta mampu menghadirkan antarmuka yang dapat beradaptasi dengan perangkat pengguna.

A forensic-driven data model for automatic vehicles events analysis

Digital vision technologies emerged exponentially in all living areas to watch, play, control, or track events. Security checkpoints have benefited also from those technologies by integrating dedicated cameras in studied locations. The aim is to manage the vehicles accessing the inspection security point and fetching for any suspected ones. However, the gathered data volume continuously increases each day, making their analysis very hard and time-consuming. This paper uses semantic-based techniques to model the data flow between the cameras, checkpoints, and administrators. It uses ontologies to deal with the increased data size and its automatic analysis. It considers forensics requirements throughout the creation of the ontology modules to ensure the records’ admissibility for any possible investigation purposes. Ontology-based data modeling will help in the automatic events search and correlation to track suspicious vehicles efficiently.

A Detection Method for Abnormal Transactions in E-Commerce Based on Extended Data Flow Conformance Checking

With the development of smart devices and mobile communication technologies, e-commerce has spread over all aspects of life. Abnormal transaction detection is important in e-commerce since abnormal transactions can result in large losses. Additionally, integrating data flow and control flow is important in the research of process modeling and data analysis since it plays an important role in the correctness and security of business processes. This paper proposes a novel method of detecting abnormal transactions via an integration model of data and control flows. Our model, called Extended Data Petri net (DPNE), integrates the data interaction and behavior of the whole process from the user logging into the e-commerce platform to the end of the payment, which also covers the mobile transaction process. We analyse the structure of the model, design the anomaly detection algorithm of relevant data, and illustrate the rationality and effectiveness of the whole system model. Through a case study, it is proved that each part of the system can respond well, and the system can judge each activity of every mobile transaction. Finally, the anomaly detection results are obtained by some comprehensive analysis.

From Information Search to the Loss of Personality: The Phenomenon of Dataism

Purpose. The research is devoted to the analysis of the urgent problem of the information society: the overload of a person with information and, as a result, the impossibility of adequate formation and development of the personality; as well as the problem of "digitization" of human existence and the formation of a new reality of dataism. Theoretical basis. A lot of modern scientific works are devoted to the analysis of the information society, its problems and features. The information society is a logical continuation of the scientific and technological revolution, which led to the rapid growth of scientific knowledge and the technology development. In the 20th century, technologies have touched the sphere of knowledge and information, as a result of which the formation and development of the information society, or "knowledge society", takes place. Information becomes the main resource in it, and, one way or another, a person’s life is inextricably connected with the information space. With the information society formation, the problem of information search and processing becomes one of the most urgent. It turns out that despite the abundance and availability of information, it is very difficult to determine its relevance. A lot of effort is spent on developing information retrieval algorithms. Another problem is related to the person’s inability to process large amounts of data. This situation begins to influence not only the education process and professional activity, but also the formation of a person’s personality. A person is "lost" in the information space and gradually loses his/her "I". Algorithms for data analysis come to the rescue, but gradually, instead of giving a person material for thought, they begin to make decisions on their own, and therefore, live life instead of a person. With the advent of Big Data processing algorithms, a new ideological paradigm appears – dataism, which predicts the merger of a person with the general data flow. Originality. The authors make assumptions that the dataistic future is "natural". A lot of works, including in the framework of philosophy, are focused on the problem of "dissolving" a person in the information space and finding ways to overcome it. But, in our opinion, this process is a completely logical continuation of human evolution. Conclusions. Existence of a person as a data flow is not a problem and a threat, but a new dimension of his/her being, and, therefore, requires a careful study and formulation of the main principles of this form of existence.