latest research topics on vanet attacks - thesis scientist research/vanet... · impact of gray hole...
TRANSCRIPT
Latest Research Topics On VANET Attacks
On The Detection Of Grey Hole And Rushing Attacks In
Self-driving Vehicular Networks
An intelligent Intrusion Detection System (IDS) which is based on
anomaly detection to protect external communications from grey hole
and rushing attacks can be presented. A feed-forward neural network
and a support vector machine can be used for the designing of the
intelligent IDS. The present system will use only significant
characteristics extracted from the trace file.
Impact Of Gray
Hole Attack In
VANET
In this topic, impact of the
gray hole attack on the
routing protocol AODV can
be examined. this observation
can be performed on four
different parameters i.e.
NRL, PDR, Throughput, and
Delay.
A Preventive Approach To Mitigate The Effects Of
Gray Hole Attack Using Genetic Algorithm
A unique solution to mitigate the effects of gray hole attack can be presented
in VANET. In this system, a node range of 20 to 80 can be taken over a
network with the height and width of 1000 meters. The system can be
evaluated ten times under the effects of gray hole attack.
Bayesian-based Model For A Reputation System In
Vehicular Networks
Here, a robust distributed reputation model based on Bayesian filter
can be proposed. The model will permit nodes to establish profiles
(such as malicious, honest) on their neighbors and to detect malicious
behaviors (e.g. black hole, gray hole).
An Intrusion Detection
System Against Black
Hole Attacks On The
Communication
Network Of Self-driving
Cars
In this topic, an intelligent
intrusion detection system (IDS)
for VANETs can be built that
will use a Proportional
Overlapping Scores (POS)
method to decrease the no. of
features that will extract from
the trace file of VANET behavior
and will be used for
classification.
A New Intrusion Detection Framework For Vehicular
Networks
A new Intrusion Detection Framework for Vehicular Networks
(IDFV) can be designed and implemented that will provide the
security against the most dangerous routing attacks such as
selective forwarding, black hole, wormhole, packets duplication
and resource exhaustion attacks that can target such networks.
A Novel Approach For Avoiding Wormhole Attacks In
VANET
In this topic, an efficient method to prevent wormhole attack can be
proposed in vehicular ad hoc networks. For this, packet leashes and
new method of authentication called HEAP can be used. Also, some
correction can be performed in packet leashes method.
Region Authority
Based Collaborative
Scheme To Detect
Sybil Attacks In
VANET
An improvement for the scheme
CP2DAP [1] can be proposed,
which can detect Sybil attacks by
the cooperation of a central
authority and a set of fixed nodes
called road-side units (RSUs). The
modification in the present system
is a region authority based
collaborative scheme for detecting
Sybil attacks and a revocation
method using bloom filter to
prevent further attacks from
malicious vehicles.
Sybil Attack Detection Using A Low Cost Short
Group Signature In VANET
In this topic, a secure protocol for solving two conflicting goals
privacy and Sybil attack in vehicle to vehicle (V2V)
communications in VANET can be proposed. The protocol will
base on the Boneh-Shacham (BS) short group signature scheme
and batch verification.
Isolation Of Sybil Attack In VANET Using Neighboring
Information
Here, a new technique can be proposed to detect and isolate Sybil
attack on vehicles resulting in network proficiency. It will work in
two-phases. In first phase RSU will register the nodes by identifying
their credentials offered by them. If they are successfully verified,
second phase will start & it will allot identification to vehicles.
Defense against Sybil
attack in vehicular ad
hoc network based on
roadside unit support
In this topic, a timestamp series
approach to protect against Sybil
attack in a vehicular ad hoc
network (VANET) based on
roadside unit support can be
proposed. This approach will
target the initial deployment
stage of VANET when basic
roadside unit (RSU) support
infrastructure is available and a
small fraction of vehicles have
network communication
capability.
Cross-layer Scheme For Detecting Large-scale
Colluding Sybil Attack In VANETs
A cross-layer scheme to enable the RSUs to identify such Sybil
vehicles can be proposed. Since Sybil vehicles do not exist in their
claimed locations, our scheme will base on verifying the vehicles'
locations.
A Traffic Flow Theory Aided Physical Measurement-based
Sybil Nodes Detection Mechanism In Vehicular Ad-hoc
Networks
A novel scheme to detect the Sybil nodes in VANETs can be presented. This
Sybil nodes detection scheme, Traffic Flow Theory Aided Physical
Measurement-Based Sybil Nodes Detection Mechanism in VANETs (PMSD),
will take benefits of un-modifiable physical measurements of the beacon
messages instead of key-based materials.
A Privacy Preserving
Solution For The
Protection Against Sybil
Attacks In Vehicular
Ad Hoc Networks
In this topic, a solution to
prevent and detect Sybil attacks
in VANETs can be presented.
The identification of attackers
will depend on two kinds of
authentication techniques. The
first will use RFID tags
embedded in the vehicle to
authenticate them to the RSU
and will obtain short lifetime
certificates. The second will use
certificates to authenticate
vehicles to their neighbors.
L-P2DSA: Location-based Privacy-preserving
Detection Of Sybil Attacks
An approach that will use infrastructures and localization of nodes
to detect Sybil attacks can be presented. Security and privacy are
two major concerns in VANETs. Regrettably, most privacy-
preserving schemes are prone to Sybil attacks, where a malicious
user pretends to be multiple vehicles. L-P2DSA will be an
improvement to C-P2DAP [3], as it will permit detecting Sybil
attacks while decreasing the load on the DMV.
A Novel Mechanism For Detecting DOS Attack In VANET
Using Enhanced Attacked Packet Detection Algorithm
(EAPDA)
In order to shelter the VANET from DOS attack, an Enhanced Attacked
Packet Detection Algorithm can be proposed which will prohibit the
deterioration of the network performance even under this attack. EAPDA not
only verify the nodes and detect malicious nodes but will also improve the
throughput with minimized delay thus security will be enhanced.
A Novel Mechanism Of
Detection Of Denial Of
Service Attack (Dos) In
VANET Using
Malicious And
Irrelevant Packet
Detection Algorithm
(MIPDA)
In this topic, an Malicious and
Irrelevant Packet Detection
Algorithm (MIPDA) can be
proposed which will be used to
analyze and detect the Denial-of
Service (DOS) attack. It will
reduce the overhead delay in the
information processing and will
increase the communication
speed and will enhance the
security in VANET.
IP-CHOCK (Filter)-based Detection Scheme For Denial
Of Service (Dos) Attacks In VANET
In this topic, the Bloom-filter-based detection method, which will
provide the availability of a service for the legitimate vehicles in
the VANET can be used to detect and protect against the IP
spoofing of addresses of the DOS attacks. This method will provide
a faster detection time, lower storage capacity and computational
cost.
Request Response Detection Algorithm For Detecting Dos
Attack In VANET
In this topic, a Request Response Detection Algorithm (RRDA) can be
proposed which will be used to detect DOS after APDA. This will increase the
response time and maximize the security in VANET.
Reference
Broadcast
Synchronization-
based Prevention
To Dos Attacks In
VANET
A new model for prevention of
DOS attacks in VANET can be
proposed and named as RBS
protocol. This model will
depend on the master chock
filter concept for filtration of
packets during busy traffic and
other attacks.
Early Detection Of DOS Attacks In VANET Using
Attacked Packet Detection Algorithm (APDA)
An Attacked Packet Detection Algorithm (APDA) can be proposed
which will be used to detect the DOS (Denial-of-Service) attacks
before the verification time. This will minimize the overhead delay
for processing and will enhance the security in VANET.
THANK YOU..Contact us at