14,979 research outputs found
IoT Sentinel: Automated Device-Type Identification for Security Enforcement in IoT
With the rapid growth of the Internet-of-Things (IoT), concerns about the
security of IoT devices have become prominent. Several vendors are producing
IP-connected devices for home and small office networks that often suffer from
flawed security designs and implementations. They also tend to lack mechanisms
for firmware updates or patches that can help eliminate security
vulnerabilities. Securing networks where the presence of such vulnerable
devices is given, requires a brownfield approach: applying necessary protection
measures within the network so that potentially vulnerable devices can coexist
without endangering the security of other devices in the same network. In this
paper, we present IOT SENTINEL, a system capable of automatically identifying
the types of devices being connected to an IoT network and enabling enforcement
of rules for constraining the communications of vulnerable devices so as to
minimize damage resulting from their compromise. We show that IOT SENTINEL is
effective in identifying device types and has minimal performance overhead
Body language, security and e-commerce
Security is becoming an increasingly more important concern both at the desktop level and at the network level. This article discusses several approaches to authenticating individuals through the use of biometric devices. While libraries might not implement such devices, they may appear in the near future of desktop computing, particularly for access to institutional computers or for access to sensitive information. Other approaches to computer security focus on protecting the contents of electronic transmissions and verification of individual users. After a brief overview of encryption technologies, the article examines public-key cryptography which is getting a lot of attention in the business world in what is called public key infrastructure. It also examines other efforts, such as IBM’s Cryptolope, the Secure Sockets Layer of Web browsers, and Digital Certificates and Signatures. Secure electronic transmissions are an important condition for conducting business on the Net. These business transactions are not limited to purchase orders, invoices, and contracts. This could become an important tool for information vendors and publishers to control access to the electronic resources they license. As license negotiators and contract administrators, librarians need to be aware of what is happening in these new technologies and the impact that will have on their operations
Conceivable security risks and authentication techniques for smart devices
With the rapidly escalating use of smart devices and fraudulent transaction of users’ data from their devices, efficient and reliable techniques for authentication of the smart devices have become an obligatory issue. This paper reviews the security risks for mobile devices and studies several authentication techniques available for smart devices. The results from field studies enable a comparative evaluation of user-preferred authentication mechanisms and their opinions about reliability, biometric authentication and visual authentication techniques
Exploiting Lack of Hardware Reciprocity for Sender-Node Authentication at the PHY Layer
This paper proposes to exploit the so-called reciprocity
parameters (modelling non-reciprocal communication
hardware) to use them as decision metric for binary hypothesis
testing based authentication framework at a receiver node Bob.
Specifically, Bob first learns the reciprocity parameters of the
legitimate sender Alice via initial training. Then, during the test
phase, Bob first obtains a measurement of reciprocity parameters
of channel occupier (Alice, or, the intruder Eve). Then, with
ground truth and current measurement both in hand, Bob
carries out the hypothesis testing to automatically accept (reject)
the packets sent by Alice (Eve). For the proposed scheme, we
provide its success rate (the detection probability of Eve), and
its performance comparison with other schemes
Data Leak Detection As a Service: Challenges and Solutions
We describe a network-based data-leak detection (DLD)
technique, the main feature of which is that the detection
does not require the data owner to reveal the content of the
sensitive data. Instead, only a small amount of specialized
digests are needed. Our technique – referred to as the fuzzy
fingerprint – can be used to detect accidental data leaks due
to human errors or application flaws. The privacy-preserving
feature of our algorithms minimizes the exposure of sensitive
data and enables the data owner to safely delegate the
detection to others.We describe how cloud providers can offer
their customers data-leak detection as an add-on service
with strong privacy guarantees.
We perform extensive experimental evaluation on the privacy,
efficiency, accuracy and noise tolerance of our techniques.
Our evaluation results under various data-leak scenarios
and setups show that our method can support accurate
detection with very small number of false alarms, even
when the presentation of the data has been transformed. It
also indicates that the detection accuracy does not degrade
when partial digests are used. We further provide a quantifiable
method to measure the privacy guarantee offered by our
fuzzy fingerprint framework
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