Statistical fingerprint‐based intrusion detection system (SF‐IDS)

Boero, Luca; Cello, Marco; Marchese, Mario; Mariconti, Enrico; Naqash, Talha; Zappatore, Sandro

doi:10.1002/dac.3225

Cited by 23 publications

(16 citation statements)

References 37 publications

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“…Rule-based detection system can be divided into rule-based [19], data mining [20], model-based/profile-based [21], and support vector machine (SVM) [22]. The system based on statistics is divided into statistics [23,24], distance-based [25], Bayesian [26], and game theory. State-based systems include state transition analysis [27], user intent recognition [28], Markov process model [29], and stateful protocol analysis (SPA) [30].…”

Section: Related Workmentioning

confidence: 99%

Temporal Logic-Based Artificial Immune System for Intrusion Detection

Chen

Pang²

2022

Wireless Communications and Mobile Computing

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Artificial immune system has made many contributions to network security areas, but there are still problems of insufficient detection range and high time cost. This paper presents a Hybrid Detector (HD) mechanism in which temporal logic antigens are proposed. The HD mechanism is constructed by using the advantage of temporal logic to describe time-varying behaviors in system. Finally, simulation experiments were carried out on KDD99 and NSL-KDD datasets. Experimental results show that the proposed method can extend the detection range and improve the detection rate. This work proves the possibility of applying temporal logic to AIS system.

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Section: Related Workmentioning

confidence: 99%

Temporal Logic-Based Artificial Immune System for Intrusion Detection

Chen

Pang²

2022

Wireless Communications and Mobile Computing

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“…University of California Irvine (UCI) heart disease is a popular medical dataset [42]. Virus is a dataset developed by the University of Genova to deal with data traffic analysis [43][44][45]. Sonar represents the readings of a sonar system that analyses materials, distinguishing between rocks and metallic material [46,47].…”

Section: Experimental Analysis and Resultsmentioning

confidence: 99%

Machine Learning on Mainstream Microcontrollers

Sakr

Bellotti

Berta

et al. 2020

Sensors

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This paper presents the Edge Learning Machine (ELM), a machine learning framework for edge devices, which manages the training phase on a desktop computer and performs inferences on microcontrollers. The framework implements, in a platform-independent C language, three supervised machine learning algorithms (Support Vector Machine (SVM) with a linear kernel, k-Nearest Neighbors (K-NN), and Decision Tree (DT)), and exploits STM X-Cube-AI to implement Artificial Neural Networks (ANNs) on STM32 Nucleo boards. We investigated the performance of these algorithms on six embedded boards and six datasets (four classifications and two regression). Our analysis—which aims to plug a gap in the literature—shows that the target platforms allow us to achieve the same performance score as a desktop machine, with a similar time latency. ANN performs better than the other algorithms in most cases, with no difference among the target devices. We observed that increasing the depth of an NN improves performance, up to a saturation level. k-NN performs similarly to ANN and, in one case, even better, but requires all the training sets to be kept in the inference phase, posing a significant memory demand, which can be afforded only by high-end edge devices. DT performance has a larger variance across datasets. In general, several factors impact performance in different ways across datasets. This highlights the importance of a framework like ELM, which is able to train and compare different algorithms. To support the developer community, ELM is released on an open-source basis.

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“…A feature set containing 14 components (indicated as features) will be used to classify each flow are listed in the Table below. This feature set is created by [77], it was used mainly to detect whether a flow is affected by a malware or not, it is selected since it represents an effective feature set and it encompass the main characteristics of a network traffic, and also the use of these features is coherent with the literature in the field.…”

Section: Dataset Creation: Generating Web Attacksmentioning

confidence: 99%

The Importance to Manage Data Protection in the Right Way: Problems and Solutions

Mokalled

Debertol

Meda

et al. 2017

Springer Proceedings in Mathematics &Amp; Statistics

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Information and communication technology (ICT) has made remarkable impact on the society, especially on companies and organizations. The use of computers, databases, servers, and other technologies has made an evolution on the way of storing, processing, and transferring data. However, companies access and share their data on internet or intranet, thus there is a critical need to protect this data from destructive forces and from the unwanted actions of unauthorized users. This thesis groups a set of solutions proposed, from a company point of view, to reach the goal of "Managing data protection". The work presented in this thesis represents a set of security solutions, which focuses on the management of data protection taking into account both the organizational and technological side. The work achieved can be divided into set of goals that are obtained particularly from the needs of the research community. This thesis handles the issue of managing data protection in a systematic way, through proposing a Data protection management approach, aiming to protect the data from both the organizational and the technological side, which was inspired by the ISO 27001 requirements. An Information Security Management System (ISMS) is then presented implementing this approach, an ISMS consists of the policies, procedures, guidelines, and associated resources and activities, collectively managed by an organization, in the pursuit of protecting its information assets. An ISMS is a systematic approach for establishing, implementing, operating, monitoring, reviewing, maintaining and improving an organization's information security to achieve business objectives, The goal of ISMS is to minimize risk and ensure continuity by pro-actively limiting the impact of a security breach. To be well-prepared to the potential threats that could occur to an organization, it is important to adopt an ISMS that helps in managing the data protection process, and in saving time and effort, minimizes cost of any loss. After that, a comprehensive framework is designed for the security risk management of Cyber Physical Systems (CPSs), this framework represents the strategy used to manage the security risk management, and it falls inside the ISMS as a security strategy. Traditional IT risk assessment methods can do the job (security risk management for a CPS); however, and because of the characteristics of a CPS, it is more efficient to adopt a solution that is wider than a method that addresses the type, functionalities and complexity of a CPS. Therefore, there is a critical need to follow a solution that breaks the restriction to a traditional risk assessment method, and so a high-level framework is proposed, it encompasses wider set of procedures and gives a great attention to the cybersecurity of these systems, which consequently leads to the safety of the physical world. In addition, inside the ISMS, another part of the work takes place, suggesting the guidelines to select an applicable Security Incident and Event Management (SIEM) solution. It ...

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Statistical fingerprint‐based intrusion detection system (SF‐IDS)

Cited by 23 publications

References 37 publications

Temporal Logic-Based Artificial Immune System for Intrusion Detection

Temporal Logic-Based Artificial Immune System for Intrusion Detection

Machine Learning on Mainstream Microcontrollers

The Importance to Manage Data Protection in the Right Way: Problems and Solutions

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