3,280 research outputs found
The Effect of IoT New Features on Security and Privacy: New Threats, Existing Solutions, and Challenges Yet to Be Solved
The future of Internet of Things (IoT) is already upon us. IoT applications
have been widely used in many field of social production and social living such
as healthcare, energy and industrial automation. While enjoying the convenience
and efficiency that IoT brings to us, new threats from IoT also have emerged.
There are increasing research works to ease these threats, but many problems
remain open. To better understand the essential reasons of new threats and the
challenges in current research, this survey first proposes the concept of "IoT
features". Then, the security and privacy effects of eight IoT new features
were discussed including the threats they cause, existing solutions and
challenges yet to be solved. To help researchers follow the up-to-date works in
this field, this paper finally illustrates the developing trend of IoT security
research and reveals how IoT features affect existing security research by
investigating most existing research works related to IoT security from 2013 to
2017
A Review of Performance, Energy and Privacy of Intrusion Detection Systems for IoT
Internet of Things (IoT) is a disruptive technology with applications across
diverse domains such as transportation and logistics systems, smart grids,
smart homes, connected vehicles, and smart cities. Alongside the growth of
these infrastructures, the volume and variety of attacks on these
infrastructures has increased highlighting the significance of distinct
protection mechanisms. Intrusion detection is one of the distinguished
protection mechanisms with notable recent efforts made to establish effective
intrusion detection for IoT and IoV. However, unique characteristics of such
infrastructures including battery power, bandwidth and processors overheads,
and the network dynamics can influence the operation of an intrusion detection
system. This paper presents a comprehensive study of existing intrusion
detection systems for IoT systems including emerging systems such as Internet
of Vehicles (IoV). The paper analyzes existing systems in three aspects:
computational overhead, energy consumption and privacy implications. Based on a
rigorous analysis of the existing intrusion detection approaches, the paper
also identifies open challenges for an effective and collaborative design of
intrusion detection system for resource-constrained IoT system in general and
its applications such as IoV. These efforts are envisaged to highlight state of
the art with respect to intrusion detection for IoT and open challenges
requiring specific efforts to achieve efficient intrusion detection within
these systems
Trends on Computer Security: Cryptography, User Authentication, Denial of Service and Intrusion Detection
The new generation of security threats has been promoted by digital
currencies and real-time applications, where all users develop new ways to
communicate on the Internet. Security has evolved in the need of privacy and
anonymity for all users and his portable devices. New technologies in every
field prove that users need security features integrated into their
communication applications, parallel systems for mobile devices, internet, and
identity management. This review presents the key concepts of the main areas in
computer security and how it has evolved in the last years. This work focuses
on cryptography, user authentication, denial of service attacks, intrusion
detection and firewalls
A lightweight cryptography (LWC) framework to secure memory heap in Internet of Things
The extensive networking of devices and the large amount of data generated
from the Internet of Things (IoT) has brought security issues to the attention
of the researcher. Java is the most common platform for embedded applications
such as IoT, Wireless Sensors Networks (WSN), Near Field Communications (NFC)
and Radio Frequency Identification (RFID). The object programming languages
such as Java, SWIFT, PHP and C++ use garbage collection after any object run
which creates security loophole for attacks such as Next Memory Address
Occupation (NMAO), memory replay, Learning Tasks Behaviors (LTB). The security
risk increases in IoT when attacks exceeds the target device to the surrounding
connected devices. Inappropriate or wrong operations causes energy loss and
increased costs. In this paper, a security method to protect IoT system
operation from memory heap penetration and address modification attack is
proposed. The proposed method prevents directed attack by encrypting the object
Garbage Collection at run time. To form a unique signature mechanism, the
Cryptographic Hash Function (CHF) which employs a specific one-way hash
algorithm. The proposed framework uses L-function based ECC and one-time Key
(OTK) to secure the memory heap. Our method is used with open system where the
effect on the operating system is not considered. The proposed method proved to
be powerful and efficient which can help in achieving higher levels of security
across several IoT applications, by enabling better detection of malicious
attacks.Comment: Alexandria Engineering Journa
Securing Edge Networks with Securebox
The number of mobile and IoT devices connected to home and enterprise
networks is growing fast. These devices offer new services and experiences for
the users; however, they also present new classes of security threats
pertaining to data and device safety and user privacy. In this article, we
first analyze the potential threats presented by these devices connected to
edge networks. We then propose Securebox: a new cloud-driven, low cost
Security-as-a-Service solution that applies Software-Defined Networking (SDN)
to improve network monitoring, security and management. Securebox enables
remote management of networks through a cloud security service (CSS) with
minimal user intervention required. To reduce costs and improve the
scalability, Securebox is based on virtualized middleboxes provided by CSS. Our
proposal differs from the existing solutions by integrating the SDN and cloud
into a unified edge security solution, and by offering a collaborative
protection mechanism that enables rapid security policy dissemination across
all connected networks in mitigating new threats or attacks detected by the
system. We have implemented two Securebox prototypes, using a low-cost
Raspberry-PI and off-the-shelf fanless PC. Our system evaluation has shown that
Securebox can achieve automatic network security and be deployed incrementally
to the infrastructure with low management overhead
Internet of Things: Survey on Security and Privacy
The Internet of Things (IoT) is intended for ubiquitous connectivity among
different entities or "things". While its purpose is to provide effective and
efficient solutions, security of the devices and network is a challenging
issue. The number of devices connected along with the ad-hoc nature of the
system further exacerbates the situation. Therefore, security and privacy has
emerged as a significant challenge for the IoT. In this paper,we aim to provide
a thorough survey related to the privacy and security challenges of the IoT.
This document addresses these challenges from the perspective of technologies
and architecture used. This work focuses also in IoT intrinsic vulnerabilities
as well as the security challenges of various layers based on the security
principles of data confidentiality, integrity and availability. This survey
analyzes articles published for the IoT at the time and relates it to the
security conjuncture of the field and its projection to the future.Comment: 16 pages, 3 figure
Wireless Sensor Networks Security: State of the Art
Wireless sensor networks (WSNs) have become one of the main research topics
in computer science in recent years, primarily owing to the significant
challenges imposed by these networks and their immense applicability. WSNs have
been employed for a diverse group of monitoring applications, with emphasis on
industrial control scenarios, traffic management, rescue operations, public
safety, residential automation, weather forecasting, and several other fields.
These networks constitute resource-constrained sensors for which security and
energy efficiency are essential concerns. In this context, many research
efforts have been focused on increasing the security levels and reducing the
energy consumption in the network. This paper provides a state-of-the-art
survey of recent works in this direction, proposing a new taxonomy for the
security attacks and requirements of WSNs.Comment: 11 pages, 3 Figures, 2 Table
HADES-IoT: A Practical Host-Based Anomaly Detection System for IoT Devices (Extended Version)
Internet of Things (IoT) devices have become ubiquitous and are spread across
many application domains including the industry, transportation, healthcare,
and households. However, the proliferation of the IoT devices has raised the
concerns about their security, especially when observing that many
manufacturers focus only on the core functionality of their products due to
short time to market and low-cost pressures, while neglecting security aspects.
Moreover, it does not exist any established or standardized method for
measuring and ensuring the security of IoT devices. Consequently,
vulnerabilities are left untreated, allowing attackers to exploit IoT devices
for various purposes, such as compromising privacy, recruiting devices into a
botnet, or misusing devices to perform cryptocurrency mining.
In this paper, we present a practical Host-based Anomaly DEtection System for
IoT (HADES-IoT) that represents the last line of defense. HADES-IoT has
proactive detection capabilities, provides tamper-proof resistance, and it can
be deployed on a wide range of Linux-based IoT devices. The main advantage of
HADES-IoT is its low performance overhead, which makes it suitable for the IoT
domain, where state-of-the-art approaches cannot be applied due to their
high-performance demands. We deployed HADES-IoT on seven IoT devices to
evaluate its effectiveness and performance overhead. Our experiments show that
HADES-IoT achieved 100% effectiveness in the detection of current IoT malware
such as VPNFilter and IoTReaper; while on average, requiring only 5.5% of
available memory and causing only a low CPU load
A Survey on the Security of Pervasive Online Social Networks (POSNs)
Pervasive Online Social Networks (POSNs) are the extensions of Online Social
Networks (OSNs) which facilitate connectivity irrespective of the domain and
properties of users. POSNs have been accumulated with the convergence of a
plethora of social networking platforms with a motivation of bridging their
gap. Over the last decade, OSNs have visually perceived an altogether
tremendous amount of advancement in terms of the number of users as well as
technology enablers. A single OSN is the property of an organization, which
ascertains smooth functioning of its accommodations for providing a quality
experience to their users. However, with POSNs, multiple OSNs have coalesced
through communities, circles, or only properties, which make
service-provisioning tedious and arduous to sustain. Especially, challenges
become rigorous when the focus is on the security perspective of cross-platform
OSNs, which are an integral part of POSNs. Thus, it is of utmost paramountcy to
highlight such a requirement and understand the current situation while
discussing the available state-of-the-art. With the modernization of OSNs and
convergence towards POSNs, it is compulsory to understand the impact and reach
of current solutions for enhancing the security of users as well as associated
services. This survey understands this requisite and fixates on different sets
of studies presented over the last few years and surveys them for their
applicability to POSNs...Comment: 39 Pages, 10 Figure
DDoS Attacks: Tools, Mitigation Approaches, and Probable Impact on Private Cloud Environment
The future of the Internet is predicted to be on the cloud, resulting in more
complex and more intensive computing, but possibly also a more insecure digital
world. The presence of a large amount of resources organized densely is a key
factor in attracting DDoS attacks. Such attacks are arguably more dangerous in
private individual clouds with limited resources. This paper discusses several
prominent approaches introduced to counter DDoS attacks in private clouds. We
also discuss issues and challenges to mitigate DDoS attacks in private clouds
- …