Wireless security threat taxonomy

Welch, Donald; Lathrop, Scott D.

doi:10.1109/smcsia.2003.1232404

Cited by 82 publications

(44 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Finally, the third piece of information the attacker can learn through traffic analysis is the type of protocol that is being used in the transmission, along with the size, type and number of packets being transmitted. For example, analysis of the three-way handshake information of TCP [17]. [16].…”

Section: A Confidentiality Attacksmentioning

confidence: 99%

“…This attack occurs in real-time and the attacker uses the session for whatever purpose he/she wants and can maintain the session for an extended period of time [17].…”

Section: ) Session Hijacking: In Session Hijacking An Attacker Takementioning

confidence: 99%

“…This requires a successful eavesdropping on the target communication to gather the necessary information. Secondly, the attacker deluges the air with a sequence of spoofed disassociate packets to keep the legitimate target out of the session [17]. [22].…”

Section: ) Session Hijacking: In Session Hijacking An Attacker Takementioning

confidence: 99%

See 2 more Smart Citations

Wireless LAN Security Threats & Vulnerabilities

Waliullah¹,

Gan²

2014

IJACSA

View full text Add to dashboard Cite

Abstract-Wireless LANs are everywhere these days from home to large enterprise corporate networks due to the ease of installation, employee convenience, avoiding wiring cost and constant mobility support. However, the greater availability of wireless LANs means increased danger from attacks and increased challenges to an organization, IT staff and IT security professionals. This paper discusses the various security issues and vulnerabilities related to the IEEE 802.11 Wireless LAN encryption standard and common threats/attacks pertaining to the home and enterprise Wireless LAN system and provide overall guidelines and recommendation to the home users and organizations.

show abstract

Section: A Confidentiality Attacksmentioning

confidence: 99%

“…This attack occurs in real-time and the attacker uses the session for whatever purpose he/she wants and can maintain the session for an extended period of time [17].…”

Section: ) Session Hijacking: In Session Hijacking An Attacker Takementioning

confidence: 99%

See 1 more Smart Citation

Wireless LAN Security Threats & Vulnerabilities

Waliullah¹,

Gan²

2014

IJACSA

View full text Add to dashboard Cite

show abstract

“…To successfully execute session hijacking, the attacker must accomplish two tasks: He first needs to stop the target node from continuing the session and then disguise himself as one of the legal client nodes (Welch & Lathrop, 2003). The attacker can take the advantage of using Denial of Services (DoS) or a flood attack to achieve his first task for the session hijacking to temporarily interrupt the target's session connection; however, in order to masquerade himself as the target, he also needs to obtain the original secret key to maintain communication with the peer node.…”

Section: Session Hijackingmentioning

confidence: 99%

Security and Dynamic Encryption System in Mobile Ad-Hoc Network

Yu¹,

Pooch²

2011

Mobile Ad-Hoc Networks: Protocol Design

View full text Add to dashboard Cite

“…Malware can be used to launch attacks that vary from the less intrusive confidentiality or privacy attacks, such as traffic analysis and eavesdropping, to the more intrusive methods that either disrupt the nodes normal functions such as those in relaying data and establishing end-to-end routes (e.g., sinkhole attacks [1]), or even alter the network traffic and hence destroy the integrity of the information, such as unauthorized access and session hijacking attacks [2], [3]. Malware outbreaks like those of Slammer [4] and Code Red [5] worms in wired Internet have already inflicted expenses of billions of dollars in repair after the viruses rapidly infected thousands of hosts within few hours.…”

Section: Introduction A) Motivationmentioning

confidence: 99%

Maximum Damage Malware Attack in Mobile Wireless Networks

Khouzani

Sarkar

Altman

2012

IEEE/ACM Trans. Networking

View full text Add to dashboard Cite

Malware attacks constitute a serious security risk that threatens to slow down the large scale proliferation of wireless applications. As a first step towards thwarting this security threat, we seek to quantify the maximum damage inflicted on the system owing to such outbreaks and identify the most vicious attacks. We represent the propagation of malware in a battery-constrained mobile wireless network by an epidemic model in which the worm can dynamically control the rate at which it kills the infected node and also the transmission range and/or the media scanning rate. At each moment of time, the worm at each node faces the following tradeoffs: (i) using larger transmission range and media scanning rate to accelerate its spread at the cost of exhausting the battery and thereby reducing the overall infection propagation rate in the long run or (ii) killing the node to inflict a large cost on the network, however at the expense of loosing the chance of infecting more susceptible nodes at later times. We mathematically formulate the decision problems and utilize Pontryagin Maximum Principle from optimal control theory to quantify the damage that the malware can inflict on the network by deploying optimum decision rules. Next, we establish structural properties of the optimal strategy of the attacker over time. Specifically, we prove that it is optimal for the attacker to defer killing of the infective nodes in the propagation phase for a certain time and then start the slaughter with maximum effort. We also show that in the optimal attack policy, the battery resources are used according to a decreasing function of time, i.e., mostly during the initial phase of the outbreak. Finally, our numerical investigations reveal a framework for identifying intelligent defense strategies that can limit the damage by appropriately selecting network parameters. Abstract-Malware attacks constitute a serious security risk that threatens to slow down the large scale proliferation of wireless applications. As a first step towards thwarting this security threat, we seek to quantify the maximum damage inflicted on the system owing to such outbreaks and identify the most vicious attacks. We represent the propagation of malware in a battery-constrained mobile wireless network by an epidemic model in which the worm can dynamically control the rate at which it kills the infected node and also the transmission range and/or the media scanning rate. At each moment of time, the worm at each node faces the following trade-offs: (i) using larger transmission range and media scanning rate to accelerate its spread at the cost of exhausting the battery and thereby reducing the overall infection propagation rate in the long run or (ii) killing the node to inflict a large cost on the network, however at the expense of loosing the chance of infecting more susceptible nodes at later times. We mathematically formulate the decision problems and utilize Pontryagin Maximum Principle from optimal control theory to quantify the damage that the mal...

show abstract

Wireless security threat taxonomy

Cited by 82 publications

References 2 publications

Wireless LAN Security Threats & Vulnerabilities

Wireless LAN Security Threats & Vulnerabilities

Security and Dynamic Encryption System in Mobile Ad-Hoc Network

Maximum Damage Malware Attack in Mobile Wireless Networks

Contact Info

Product

Resources

About