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Related papers: An Immune Inspired Approach to Anomaly Detection

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When the equipment is working, real-time collection of environmental sensor data for anomaly detection is one of the key links to prevent industrial process accidents and network attacks and ensure system security. However, under the…

Machine Learning · Computer Science 2024-03-25 Zilong Shao

Current network protection systems use a collection of intelligent components - e.g. classifiers or rule-based firewall systems to detect intrusions and anomalies and to secure a network against viruses, worms, or trojans. However, these…

Cryptography and Security · Computer Science 2008-05-08 Michael Hilker , Christoph Schommer

Autonomous agents deployed in the real world need to be robust against adversarial attacks on sensory inputs. Robustifying agent policies requires anticipating the strongest attacks possible. We demonstrate that existing observation-space…

By developing communications and increase of access points, computer networks have been vulnerable considerably against wide range of information attacks, specially new and complicated attacks. Every day, replication attacks attack millions…

Cryptography and Security · Computer Science 2015-04-15 Amir Hosein Bodaghi

In this thesis, the uses of Artificial Immune Systems (AIS) in Machine learning is studded. the thesis focus on some of immune inspired algorithms such as clonal selection algorithm and artificial immune network. The effect of changing the…

Neural and Evolutionary Computing · Computer Science 2017-09-14 Mohammad Tarek Al Muallim

Generative adversarial networks (GANs) have shown promise for various problems including anomaly detection. When anomaly detection is performed using GAN models that learn only the features of normal data samples, data that are not similar…

Machine Learning · Computer Science 2020-12-23 Teguh Budianto , Tomohiro Nakai , Kazunori Imoto , Takahiro Takimoto , Kosuke Haruki

The Dendritic Cell Algorithm (DCA) is inspired by the function of the dendritic cells of the human immune system. In nature, dendritic cells are the intrusion detection agents of the human body, policing the tissue and organs for potential…

Artificial Intelligence · Computer Science 2010-07-05 Julie Greensmith , Uwe Aickelin , Steve Cayzer

Cyber attacks constitute a significant threat to organizations with implications ranging from economic, reputational, and legal consequences. As cybercriminals' techniques get sophisticated, information security professionals face a more…

Cryptography and Security · Computer Science 2021-04-01 Emrah Tufan , Cihangir Tezcan , Cengiz Acartürk

Innate immunity now occupies a central role in immunology. However, artificial immune system models have largely been inspired by adaptive not innate immunity. This paper reviews the biological principles and properties of innate immunity…

Artificial Intelligence · Computer Science 2010-07-05 Jamie Twycross , Uwe Aickelin

Cyber-physical systems are infrastructures that use digital information such as network communications and sensor readings to control entities in the physical world. Many cyber-physical systems in airports, hospitals and nuclear power…

Cryptography and Security · Computer Science 2022-01-03 Nuno Oliveira , Norberto Sousa , Jorge Oliveira , Isabel Praça

Current network protection systems use a collection of intelligent components - e.g. classifiers or rule-based firewall systems to detect intrusions and anomalies and to secure a network against viruses, worms, or trojans. However, these…

Multiagent Systems · Computer Science 2008-05-14 Michael Hilker , Christoph Schommer

The adaptive immune system is a natural diagnostic and therapeutic. It recognizes threats earlier than clinical symptoms manifest and neutralizes antigen with exquisite specificity. Recognition specificity and broad reactivity is enabled…

Quantitative Methods · Quantitative Biology 2019-07-26 Alex J. Brown , Igor Snapkov , Rahmad Akbar , Milena Pavlović , Enkelejda Miho , Geir K. Sandve , Victor Greiff

We present a novel method for image anomaly detection, where algorithms that use samples drawn from some distribution of "normal" data, aim to detect out-of-distribution (abnormal) samples. Our approach includes a combination of encoder and…

Image and Video Processing · Electrical Eng. & Systems 2020-03-02 Nina Tuluptceva , Bart Bakker , Irina Fedulova , Anton Konushin

There has been an ongoing cycle where stronger defenses against adversarial attacks are subsequently broken by a more advanced defense-aware attack. We present a new approach towards ending this cycle where we "deflect'' adversarial attacks…

Machine Learning · Computer Science 2020-02-19 Yao Qin , Nicholas Frosst , Colin Raffel , Garrison Cottrell , Geoffrey Hinton

Current network security systems are progressively showing their limitations. One credible estimate is that only about 45% of new threats are detected. Therefore it is vital to find a new direction that cybersecurity development should…

Cryptography and Security · Computer Science 2016-04-14 Wojciech Mazurczyk , Szymon Drobniak , Sean Moore

Anomaly detection consists in identifying, within a dataset, those samples that significantly differ from the majority of the data, representing the normal class. It has many practical applications, e.g. ranging from defective product…

Computer Vision and Pattern Recognition · Computer Science 2020-11-13 Pankaj Mishra , Claudio Piciarelli , Gian Luca Foresti

Life insurance, like other forms of insurance, relies heavily on large volumes of data. The business model is based on an exchange where companies receive payments in return for the promise to provide coverage in case of an accident. Thus,…

Applications · Statistics 2024-11-27 Andreas Groll , Akshat Khanna , Leonid Zeldin

Industrial Control Systems (ICSs) are becoming more and more important in managing the operation of many important systems in smart manufacturing, such as power stations, water supply systems, and manufacturing sites. While massive digital…

Systems and Control · Electrical Eng. & Systems 2022-05-05 Do Thu Ha , Nguyen Xuan Hoang , Nguyen Viet Hoang , Nguyen Huu Du , Truong Thu Huong , Kim Phuc Tran

Anomaly detection in supercomputers is a very difficult problem due to the big scale of the systems and the high number of components. The current state of the art for automated anomaly detection employs Machine Learning methods or…

Machine Learning · Computer Science 2020-07-30 Andrea Borghesi , Andrea Bartolini , Michele Lombardi , Michela Milano , Luca Benini

Anomaly detection methods are part of the systems where rare events may endanger an operation's profitability, safety, and environmental aspects. Although many state-of-the-art anomaly detection methods were developed to date, their…

Machine Learning · Computer Science 2023-02-01 Marek Wadinger , Michal Kvasnica
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