2,452 research outputs found
A Study of IEEE 802.15.4 Security Framework for Wireless Body Area Network
A Wireless Body Area Network (WBAN) is a collection of low-power and
lightweight wireless sensor nodes that are used to monitor the human body
functions and the surrounding environment. It supports a number of innovative
and interesting applications, including ubiquitous healthcare and Consumer
Electronics (CE) applications. Since WBAN nodes are used to collect sensitive
(life-critical) information and may operate in hostile environments, they
require strict security mechanisms to prevent malicious interaction with the
system. In this paper, we first highlight major security requirements and
Denial of Service (DoS) attacks in WBAN at Physical, Medium Access Control
(MAC), Network, and Transport layers. Then we discuss the IEEE 802.15.4
security framework and identify the security vulnerabilities and major attacks
in the context of WBAN. Different types of attacks on the Contention Access
Period (CAP) and Contention Free Period (CFP) parts of the superframe are
analyzed and discussed. It is observed that a smart attacker can successfully
corrupt an increasing number of GTS slots in the CFP period and can
considerably affect the Quality of Service (QoS) in WBAN (since most of the
data is carried in CFP period). As we increase the number of smart attackers
the corrupted GTS slots are eventually increased, which prevents the legitimate
nodes to utilize the bandwidth efficiently. This means that the direct
adaptation of IEEE 802.15.4 security framework for WBAN is not totally secure
for certain WBAN applications. New solutions are required to integrate high
level security in WBAN.Comment: 14 pages, 7 figures, 2 table
Roadmap on semiconductor-cell biointerfaces.
This roadmap outlines the role semiconductor-based materials play in understanding the complex biophysical dynamics at multiple length scales, as well as the design and implementation of next-generation electronic, optoelectronic, and mechanical devices for biointerfaces. The roadmap emphasizes the advantages of semiconductor building blocks in interfacing, monitoring, and manipulating the activity of biological components, and discusses the possibility of using active semiconductor-cell interfaces for discovering new signaling processes in the biological world
LeakyOhm: Secret Bits Extraction using Impedance Analysis
The threats of physical side-channel attacks and their countermeasures have
been widely researched. Most physical side-channel attacks rely on the
unavoidable influence of computation or storage on current consumption or
voltage drop on a chip. Such data-dependent influence can be exploited by, for
instance, power or electromagnetic analysis. In this work, we introduce a novel
non-invasive physical side-channel attack, which exploits the data-dependent
changes in the impedance of the chip. Our attack relies on the fact that the
temporarily stored contents in registers alter the physical characteristics of
the circuit, which results in changes in the die's impedance. To sense such
impedance variations, we deploy a well-known RF/microwave method called
scattering parameter analysis, in which we inject sine wave signals with high
frequencies into the system's power distribution network (PDN) and measure the
echo of the signals. We demonstrate that according to the content bits and
physical location of a register, the reflected signal is modulated differently
at various frequency points enabling the simultaneous and independent probing
of individual registers. Such side-channel leakage challenges the -probing
security model assumption used in masking, which is a prominent side-channel
countermeasure. To validate our claims, we mount non-profiled and profiled
impedance analysis attacks on hardware implementations of unprotected and
high-order masked AES. We show that in the case of the profiled attack, only a
single trace is required to recover the secret key. Finally, we discuss how a
specific class of hiding countermeasures might be effective against impedance
leakage
A Survey on Wireless Security: Technical Challenges, Recent Advances and Future Trends
This paper examines the security vulnerabilities and threats imposed by the
inherent open nature of wireless communications and to devise efficient defense
mechanisms for improving the wireless network security. We first summarize the
security requirements of wireless networks, including their authenticity,
confidentiality, integrity and availability issues. Next, a comprehensive
overview of security attacks encountered in wireless networks is presented in
view of the network protocol architecture, where the potential security threats
are discussed at each protocol layer. We also provide a survey of the existing
security protocols and algorithms that are adopted in the existing wireless
network standards, such as the Bluetooth, Wi-Fi, WiMAX, and the long-term
evolution (LTE) systems. Then, we discuss the state-of-the-art in
physical-layer security, which is an emerging technique of securing the open
communications environment against eavesdropping attacks at the physical layer.
We also introduce the family of various jamming attacks and their
counter-measures, including the constant jammer, intermittent jammer, reactive
jammer, adaptive jammer and intelligent jammer. Additionally, we discuss the
integration of physical-layer security into existing authentication and
cryptography mechanisms for further securing wireless networks. Finally, some
technical challenges which remain unresolved at the time of writing are
summarized and the future trends in wireless security are discussed.Comment: 36 pages. Accepted to Appear in Proceedings of the IEEE, 201
Peri-implant diseases diagnosis, prognosis and dental implant monitoring: a narrative review of novel strategies and clinical impact
BACKGROUND: The diagnosis of peri-implantar and periodontal relies mainly on a set of clinical measures and the evaluation of radiographic images. However, these clinical settings alone are not sufficient to determine, much less predict, periimplant bone loss or future implant failure. Early diagnosis of periimplant diseases and its rate of progress may be possible through biomarkers assessment. Once identified, biomarkers of peri-implant and periodontal tissue destruction may alert the clinicians before clinical signs show up. Therefore, it is important to consider developing chair-side diagnostic tests with specificity for a particular biomarker, indicating the current activity of the disease. METHODS: A search strategy was created at Pubmed and Web of Science to answer the question: "How the molecular point-of-care tests currently available can help in the early detection of peri-implant diseases and throws light on improvements in point of care diagnostics devices?". RESULTS: The PerioSafe® PRO DRS (dentognostics GmbH, Jena) and ImplantSafe® DR (dentognostics GmbH, Jena ORALyzer® test kits, already used clinically, can be a helpful adjunct tool in enhancing the diagnosis and prognosis of periodontal/peri-implantar diseases. With the advances of sensor technology, the biosensors can perform daily monitoring of dental implants or periodontal diseases, making contributions to personal healthcare and improve the current status quo of health management and human health. CONCLUSIONS: Based on the findings, more emphasis is given to the role of biomarkers in diagnosing and monitoring periodontal and peri-implant diseases. By combining these strategies with traditional protocols, professionals could increase the accuracy of early detection of peri-implant and periodontal diseases, predicting disease progression, and monitoring of treatment outcomes.info:eu-repo/semantics/publishedVersio
Security, trust and cooperation in wireless sensor networks
Wireless sensor networks are a promising technology for many real-world applications such as critical infrastructure monitoring, scientific data gathering, smart buildings, etc.. However, given the typically unattended and potentially unsecured operation environment, there has been an increased number of security threats to sensor networks. In addition, sensor networks have very constrained resources, such as limited energy, memory, computational power, and communication bandwidth. These unique challenges call for new security mechanisms and algorithms. In this dissertation, we propose novel algorithms and models to address some important and challenging security problems in wireless sensor networks.
The first part of the dissertation focuses on data trust in sensor networks. Since sensor networks are mainly deployed to monitor events and report data, the quality of received data must be ensured in order to make meaningful inferences from sensor data. We first study a false data injection attack in the distributed state estimation problem and propose a distributed Bayesian detection algorithm, which could maintain correct estimation results when less than one half of the sensors are compromised. To deal with the situation where more than one half of the sensors may be compromised, we introduce a special class of sensor nodes called \textit{trusted cores}. We then design a secure distributed trust aggregation algorithm that can utilize the trusted cores to improve network robustness. We show that as long as there exist some paths that can connect each regular node to one of these trusted cores, the network can not be subverted by attackers.
The second part of the dissertation focuses on sensor network monitoring and anomaly detection. A sensor network may suffer from system failures due to loss of links and nodes, or malicious intrusions. Therefore, it is critical to continuously monitor the overall state of the network and locate performance anomalies. The network monitoring and probe selection problem is formulated as a budgeted coverage problem and a Markov decision process. Efficient probing strategies are designed to achieve a flexible tradeoff between inference accuracy and probing overhead. Based on the probing results on traffic measurements, anomaly detection can be conducted. To capture the highly dynamic network traffic, we develop a detection scheme based on multi-scale analysis of the traffic using wavelet transforms and hidden Markov models. The performance of the probing strategy and of the detection scheme are extensively evaluated in malicious scenarios using the NS-2 network simulator.
Lastly, to better understand the role of trust in sensor networks, a game theoretic model is formulated to mathematically analyze the relation between trust and cooperation. Given the trust relations, the interactions among nodes are modeled as a network game on a trust-weighted graph. We then propose an efficient heuristic method that explores network heterogeneity to improve Nash equilibrium efficiency
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