Technological and Legal Aspects of CIS

Stavroulakis, Peter

doi:10.1007/978-3-642-04117-4_38

Cited by 10 publications

(13 citation statements)

References 12 publications

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“…Then, the entire signal acquired for each particle and condition was split into epochs of 2 s. The z-score of each 2 s signal portion was computed in order to remove noisy signal epochs. Independently of the type of features used in this kind of problems, it is important that their raw signals have as higher signal-to-noise ratio (SNR) as possible [ 44 , 45 , 46 ]. 2 s z-scored signal portions which, in magnitude, exceeded the threshold value of 5 were therefore discarded.…”

Section: Methodsmentioning

confidence: 99%

Single Particle Differentiation through 2D Optical Fiber Trapping and Back-Scattered Signal Statistical Analysis: An Exploratory Approach

Paiva

Ribeiro

Cunha

et al. 2018

Sensors

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Recent trends on microbiology point out the urge to develop optical micro-tools with multifunctionalities such as simultaneous manipulation and sensing. Considering that miniaturization has been recognized as one of the most important paradigms of emerging sensing biotechnologies, optical fiber tools, including Optical Fiber Tweezers (OFTs), are suitable candidates for developing multifunctional small sensors for Medicine and Biology. OFTs are flexible and versatile optotools based on fibers with one extremity patterned to form a micro-lens. These are able to focus laser beams and exert forces onto microparticles strong enough (piconewtons) to trap and manipulate them. In this paper, through an exploratory analysis of a 45 features set, including time and frequency-domain parameters of the back-scattered signal of particles trapped by a polymeric lens, we created a novel single feature able to differentiate synthetic particles (PMMA and Polystyrene) from living yeasts cells. This single statistical feature can be useful for the development of label-free hybrid optical fiber sensors with applications in infectious diseases detection or cells sorting. It can also contribute, by revealing the most significant information that can be extracted from the scattered signal, to the development of a simpler method for particles characterization (in terms of composition, heterogeneity degree) than existent technologies.

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Section: Methodsmentioning

confidence: 99%

Single Particle Differentiation through 2D Optical Fiber Trapping and Back-Scattered Signal Statistical Analysis: An Exploratory Approach

Paiva

Ribeiro

Cunha

et al. 2018

Sensors

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“…A traffic mining–based intrusion detection method proposed by Stavroulakis and Stamp 20 extracts five tuples (source IP address, destination IP address, transport-layer protocol, source port, destination port), the traffic duration, and the average time interval between adjacent packets from the collected traffic data. Then the data mining technology is employed to distinguish the abnormal behaviors from the normal behaviors of the system and finally detect a variety of intrusions such as Replay, Denial of Service (DoS), Man-in-the-Middle, and Packet Tampering.…”

Section: New Taxonomy Of Ics Idsmentioning

confidence: 99%

A survey of intrusion detection on industrial control systems

et al. 2018

International Journal of Distributed Sensor Networks

127

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The modern industrial control systems now exhibit an increasing connectivity to the corporate Internet technology networks so as to make full use of the rich resource on the Internet. The increasing interaction between industrial control systems and the outside Internet world, however, has made them an attractive target for a variety of cyber attacks, raising a great need to secure industrial control systems. Intrusion detection technology is one of the most important security precautions for industrial control systems. It can effectively detect potential attacks against industrial control systems. In this survey, we elaborate on the characteristics and the new security requirements of industrial control systems. After that, we present a new taxonomy of intrusion detection systems for industrial control systems based on different techniques: protocol analysis based, traffic mining based, and control process analysis based. In addition, we analyze the advantages and disadvantages of different categories of intrusion detection systems and discuss some future developments of intrusion detection systems for industrial control systems, in order to promote further research on intrusion detection technology for industrial control systems.

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“…However, encryption itself is not effective enough where a malicious attacker can perform traffic analysis on the overheard cipher text, which could release sensitive information from the data. Moreover, to avoid the exploit of information, confidentiality of sensed data in smart grids also must be applied by access control policies [10,11,15]. Furthermore, to maintain the confidentiality in smart grids, secure channels should be built into the network.…”

Section: A Security Requirementsmentioning

confidence: 99%

“…Furthermore, to maintain the confidentiality in smart grids, secure channels should be built into the network. Also, public node information such as node identities must be encrypted to some extent to defend against traffic analysis attacks [15]. Compromising a node physically becomes a problem of data confidentiality, whereas, a malicious user physically captures a node, it is generally expected that the adversary can obtain all data from that node such as reading meter data or customers' data.…”

Section: A Security Requirementsmentioning

confidence: 99%

A Cloud of Things (CoT) Based Security for Home Area Network (HAN) in the Smart Grid

Alohali

Merabti

Kifayat

2014

2014 Eighth International Conference on Next Generation Mobile Apps, Services and Technologies

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A smart grid is a power system that consists of communication infrastructure, IT systems, advanced actuators, and advanced monitoring building blocks for a smart city. The devices powered in smart homes have embedded systems in appliances. They are sensor-based and network-enabled and commonly referred to as Internet of Things (IoT). A Cloud of Things (CoT) virtualizes the IoT and provides monitoring and control. The CoT services in the home area network will enable a collection of applications that will use real-time data from these appliances. As always, security and privacy issues are prime since it involves private data from the home. In this paper, we propose a secure scheme for Home Area Network (HAN) based on CoT. The security scheme discusses how a device that is connected at a home is serviced from the CoT. Specifically, it illustrates how the security requirements are administered from the CoT and discusses a specific scheme for key management for the HAN.

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Technological and Legal Aspects of CIS

Cited by 10 publications

References 12 publications

Single Particle Differentiation through 2D Optical Fiber Trapping and Back-Scattered Signal Statistical Analysis: An Exploratory Approach

Single Particle Differentiation through 2D Optical Fiber Trapping and Back-Scattered Signal Statistical Analysis: An Exploratory Approach

A survey of intrusion detection on industrial control systems

A Cloud of Things (CoT) Based Security for Home Area Network (HAN) in the Smart Grid

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