Major security incidents since 2014: an African perspective
- Van Heerden, Renier, Von Solms, Sune, Vorster, Johannes
- Authors: Van Heerden, Renier , Von Solms, Sune , Vorster, Johannes
- Date: 2018
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/68291 , vital:29234 , https://ieeexplore.ieee.org/abstract/document/8417326/
- Description: Publisher version , The integration of technology in the modern society provides many benefits, but with increased connectivity comes increased risk where governments, businesses and individuals are vulnerable to a variety of cyber-attacks. Many of the large information security attacks of the last decade can be seen as an attack on 'foreign” systems or individuals when viewed from an African perspective, with no direct impact on an individual in Africa. However, information security experts in Africa states that although some of these attacks might not have had a direct impact of the African individual, but never the less should not be ignored as it does indirectly influence the African individual. The experts state that even if the individuals or businesses are not directly influenced by an attack, it should not be ignored as similar attacks might influence them in the future. They emphasise that these attacks should improve their cybersecurity awareness and behaviour, in order to prevent similar attacks from impacting them.
- Full Text: false
- Date Issued: 2018
- Authors: Van Heerden, Renier , Von Solms, Sune , Vorster, Johannes
- Date: 2018
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/68291 , vital:29234 , https://ieeexplore.ieee.org/abstract/document/8417326/
- Description: Publisher version , The integration of technology in the modern society provides many benefits, but with increased connectivity comes increased risk where governments, businesses and individuals are vulnerable to a variety of cyber-attacks. Many of the large information security attacks of the last decade can be seen as an attack on 'foreign” systems or individuals when viewed from an African perspective, with no direct impact on an individual in Africa. However, information security experts in Africa states that although some of these attacks might not have had a direct impact of the African individual, but never the less should not be ignored as it does indirectly influence the African individual. The experts state that even if the individuals or businesses are not directly influenced by an attack, it should not be ignored as similar attacks might influence them in the future. They emphasise that these attacks should improve their cybersecurity awareness and behaviour, in order to prevent similar attacks from impacting them.
- Full Text: false
- Date Issued: 2018
The pattern-richness of graphical passwords
- Vorster, Johannes, Van Heerden, Renier, Irwin, Barry V W
- Authors: Vorster, Johannes , Van Heerden, Renier , Irwin, Barry V W
- Date: 2016
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/68322 , vital:29238 , https://doi.org/10.1109/ISSA.2016.7802931
- Description: Publisher version , Conventional (text-based) passwords have shown patterns such as variations on the username, or known passwords such as “password”, “admin” or “12345”. Patterns may similarly be detected in the use of Graphical passwords (GPs). The most significant such pattern - reported by many researchers - is hotspot clustering. This paper qualitatively analyses more than 200 graphical passwords for patterns other than the classically reported hotspots. The qualitative analysis finds that a significant percentage of passwords fall into a small set of patterns; patterns that can be used to form attack models against GPs. In counter action, these patterns can also be used to educate users so that future password selection is more secure. It is the hope that the outcome from this research will lead to improved behaviour and an enhancement in graphical password security.
- Full Text: false
- Date Issued: 2016
- Authors: Vorster, Johannes , Van Heerden, Renier , Irwin, Barry V W
- Date: 2016
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/68322 , vital:29238 , https://doi.org/10.1109/ISSA.2016.7802931
- Description: Publisher version , Conventional (text-based) passwords have shown patterns such as variations on the username, or known passwords such as “password”, “admin” or “12345”. Patterns may similarly be detected in the use of Graphical passwords (GPs). The most significant such pattern - reported by many researchers - is hotspot clustering. This paper qualitatively analyses more than 200 graphical passwords for patterns other than the classically reported hotspots. The qualitative analysis finds that a significant percentage of passwords fall into a small set of patterns; patterns that can be used to form attack models against GPs. In counter action, these patterns can also be used to educate users so that future password selection is more secure. It is the hope that the outcome from this research will lead to improved behaviour and an enhancement in graphical password security.
- Full Text: false
- Date Issued: 2016
Classifying network attack scenarios using an ontology
- Van Heerden, Renier, Irwin, Barry V W, Burke, I D
- Authors: Van Heerden, Renier , Irwin, Barry V W , Burke, I D
- Date: 2012
- Language: English
- Type: Conference paper
- Identifier: vital:6606 , http://hdl.handle.net/10962/d1009326
- Description: This paper presents a methodology using network attack ontology to classify computer-based attacks. Computer network attacks differ in motivation, execution and end result. Because attacks are diverse, no standard classification exists. If an attack could be classified, it could be mitigated accordingly. A taxonomy of computer network attacks forms the basis of the ontology. Most published taxonomies present an attack from either the attacker's or defender's point of view. This taxonomy presents both views. The main taxonomy classes are: Actor, Actor Location, Aggressor, Attack Goal, Attack Mechanism, Attack Scenario, Automation Level, Effects, Motivation, Phase, Scope and Target. The "Actor" class is the entity executing the attack. The "Actor Location" class is the Actor‟s country of origin. The "Aggressor" class is the group instigating an attack. The "Attack Goal" class specifies the attacker‟s goal. The "Attack Mechanism" class defines the attack methodology. The "Automation Level" class indicates the level of human interaction. The "Effects" class describes the consequences of an attack. The "Motivation" class specifies incentives for an attack. The "Scope" class describes the size and utility of the target. The "Target" class is the physical device or entity targeted by an attack. The "Vulnerability" class describes a target vulnerability used by the attacker. The "Phase" class represents an attack model that subdivides an attack into different phases. The ontology was developed using an "Attack Scenario" class, which draws from other classes and can be used to characterize and classify computer network attacks. An "Attack Scenario" consists of phases, has a scope and is attributed to an actor and aggressor which have a goal. The "Attack Scenario" thus represents different classes of attacks. High profile computer network attacks such as Stuxnet and the Estonia attacks can now be been classified through the “Attack Scenario” class.
- Full Text:
- Date Issued: 2012
- Authors: Van Heerden, Renier , Irwin, Barry V W , Burke, I D
- Date: 2012
- Language: English
- Type: Conference paper
- Identifier: vital:6606 , http://hdl.handle.net/10962/d1009326
- Description: This paper presents a methodology using network attack ontology to classify computer-based attacks. Computer network attacks differ in motivation, execution and end result. Because attacks are diverse, no standard classification exists. If an attack could be classified, it could be mitigated accordingly. A taxonomy of computer network attacks forms the basis of the ontology. Most published taxonomies present an attack from either the attacker's or defender's point of view. This taxonomy presents both views. The main taxonomy classes are: Actor, Actor Location, Aggressor, Attack Goal, Attack Mechanism, Attack Scenario, Automation Level, Effects, Motivation, Phase, Scope and Target. The "Actor" class is the entity executing the attack. The "Actor Location" class is the Actor‟s country of origin. The "Aggressor" class is the group instigating an attack. The "Attack Goal" class specifies the attacker‟s goal. The "Attack Mechanism" class defines the attack methodology. The "Automation Level" class indicates the level of human interaction. The "Effects" class describes the consequences of an attack. The "Motivation" class specifies incentives for an attack. The "Scope" class describes the size and utility of the target. The "Target" class is the physical device or entity targeted by an attack. The "Vulnerability" class describes a target vulnerability used by the attacker. The "Phase" class represents an attack model that subdivides an attack into different phases. The ontology was developed using an "Attack Scenario" class, which draws from other classes and can be used to characterize and classify computer network attacks. An "Attack Scenario" consists of phases, has a scope and is attributed to an actor and aggressor which have a goal. The "Attack Scenario" thus represents different classes of attacks. High profile computer network attacks such as Stuxnet and the Estonia attacks can now be been classified through the “Attack Scenario” class.
- Full Text:
- Date Issued: 2012
- «
- ‹
- 1
- ›
- »