DDoS-Capable IoT Malwares: comparative analysis and Mirai Investigation

The Internet of Things (IoT) revolution has not only carried the astonishing promise to interconnect a whole generation of traditionally “dumb” devices, but also brought to the Internet the menace of billions of badly protected and easily hackable objects. Not surprisingly, this sudden flooding of fresh and insecure devices fueled older threats, such as Distributed Denial of Service (DDoS) attacks. In this paper, we first propose an updated and comprehensive taxonomy of DDoS attacks, together with a number of examples on how this classification maps to real-world attacks. Then, we outline the current situation of DDoS-enabled malwares in IoT networks, highlighting how recent data support our concerns about the growing in popularity of these malwares. Finally, we give a detailed analysis of the general framework and the operating principles of Mirai, the most disruptive DDoS-capable IoT malware seen so far

The IEC 61850 sampled measured values protocol: Analysis, threat identification, and feasibility of using NN forecasters to detect spoofed packets \u3csup\u3e†\u3c/sup\u3e

The operation of the smart grid is anticipated to rely profoundly on distributed microprocessor-based control. Therefore, interoperability standards are needed to address the heterogeneous nature of the smart grid data. Since the IEC 61850 emerged as a wide-spread interoperability standard widely accepted by the industry, the Sampled Measured Values method has been used to communicate digitized voltage and current measurements. Realizing that current and voltage measurements (i.e., feedback measurements) are necessary for reliable and secure noperation of the power grid, firstly, this manuscript provides a detailed analysis of the Sampled Measured Values protocol emphasizing its advantages, then, it identifies vulnerabilities in this protocol and explains the cyber threats associated to these vulnerabilities. Secondly, current efforts to mitigate these vulnerabilities are outlined and the feasibility of using neural network forecasters to detect spoofed sampled values is investigated. It was shown that although such forecasters have high spoofed data detection accuracy, they are prone to the accumulation of forecasting error. Accordingly, this paper also proposes an algorithm to detect the accumulation of the forecasting error based on lightweight statistical indicators. The effectiveness of the proposed methods is experimentally verified in a laboratory-scale smart grid testbed

Automated and intelligent hacking detection system

Dissertação de mestrado integrado em Informatics EngineeringThe Controller Area Network (CAN) is the backbone of automotive networking, connecting many Electronic ControlUnits (ECUs) that control virtually every vehicle function from fuel injection to parking sensors. It possesses,however, no security functionality such as message encryption or authentication by default. Attackers can easily inject or modify packets in the network, causing vehicle malfunction and endangering the driver and passengers. There is an increasing number of ECUs in modern vehicles, primarily driven by the consumer’s expectation of more features and comfort in their vehicles as well as ever-stricter government regulations on efficiency and emissions. Combined with vehicle connectivity to the exterior via Bluetooth, Wi-Fi, or cellular, this raises the risk of attacks. Traditional networks, such as Internet Protocol (IP), typically have an Intrusion Detection System (IDS) analysing traffic and signalling when an attack occurs. The system here proposed is an adaptation of the traditional IDS into the CAN bus using a One Class Support Vector Machine (OCSVM) trained with live, attack-free traffic. The system is capable of reliably detecting a variety of attacks, both known and unknown, without needing to understand payload syntax, which is largely proprietary and vehicle/model dependent. This allows it to be installed in any vehicle in a plug-and-play fashion while maintaining a large degree of accuracy with very few false positives.A Controller Area Network (CAN) é a principal tecnologia de comunicação interna automóvel, ligando muitas Electronic Control Units (ECUs) que controlam virtualmente todas as funções do veículo desde injeção de combustível até aos sensores de estacionamento. No entanto, não possui por defeito funcionalidades de segurança como cifragem ou autenticação. É possível aos atacantes facilmente injetarem ou modificarem pacotes na rede causando estragos e colocando em perigo tanto o condutor como os passageiros. Existe um número cada vez maior de ECUs nos veículos modernos, impulsionado principalmente pelas expectativas do consumidores quanto ao aumento do conforto nos seus veículos, e pelos cada vez mais exigentes regulamentos de eficiência e emissões. Isto, associada à conexão ao exterior através de tecnologias como o Bluetooth, Wi-Fi, ou redes móveis, aumenta o risco de ataques. Redes tradicionais, como a rede Internet Protocol (IP), tipicamente possuem um Intrusion Detection Systems (IDSs) que analiza o tráfego e assinala a presença de um ataque. O sistema aqui proposto é uma adaptação do IDS tradicional à rede CAN utilizando uma One Class Support Vector Machine (OCSVM) treinada com tráfego real e livre de ataques. O sistema é capaz de detetar com fiabilidade uma variedade de ataques, tanto conhecidos como desconhecidos, sem a necessidade de entender a sintaxe do campo de dados das mensagens, que é maioritariamente proprietária. Isto permite ao sistema ser instalado em qualquer veículo num modo plug-and-play enquanto mantém um elevado nível de desempenho com muito poucos falsos positivos

DNS in Computer Forensics

The Domain Name Service (DNS) is a critical core component of the global Internet and integral to the majority of corporate intranets. It provides resolution services between the human-readable name-based system addresses and the machine operable Internet Protocol (IP) based addresses required for creating network level connections. Whilst structured as a globally dispersed resilient tree data structure, from the Global and Country Code Top Level Domains (gTLD/ccTLD) down to the individual site and system leaf nodes, it is highly resilient although vulnerable to various attacks, exploits and systematic failures

Project BeARCAT : Baselining, Automation and Response for CAV Testbed Cyber Security : Connected Vehicle & Infrastructure Security Assessment

Connected, software-based systems are a driver in advancing the technology of transportation systems. Advanced automated and autonomous vehicles, together with electrification, will help reduce congestion, accidents and emissions. Meanwhile, vehicle manufacturers see advanced technology as enhancing their products in a competitive market. However, as many decades of using home and enterprise computer systems have shown, connectivity allows a system to become a target for criminal intentions. Cyber-based threats to any system are a problem; in transportation, there is the added safety implication of dealing with moving vehicles and the passengers within

Intrusion Detection System of industrial control networks using network telemetry

Industrial Control Systems (ICSs) are designed, implemented, and deployed in most major spheres of production, business, and entertainment. ICSs are commonly split into two subsystems - Programmable Logic Controllers (PLCs) and Supervisory Control And Data Acquisition (SCADA) systems - to achieve high safety, allow engineers to observe states of an ICS, and perform various configuration updates. Before wide adoption of the Internet, ICSs used air-gap security measures, where the ICS network was isolated from other networks, including the Internet, by a physical disconnect [1]. This level of security allowed ICS protocol designers to concentrate on the availability and safety of operation of physical systems while decreasing the need for many cyber security implementations. As the price of networking devices fell, and the Internet received global adoption, many businesses became interested in the benefits of attaching ICSs to wide and global area networks. However, since ICS network protocols were originally designed for an air-gapped environment, it did not include any of the security measures needed for a proper operation of a critical protocol that exposes its packets to the Internet. This dissertation designs, implements, and evaluates a telemetry based Intrusion Detection System (IDS). The designed IDS utilizes aggregation and analysis of the traffic telemetry features to classify the incoming packets as malicious or benign. An IDS that uses network telemetry was created, and it achieved a high classification accuracy, protecting nodes from malicious traffic. Such an IDS is not vulnerable to address or encryption spoofings, as it does not utilize the content of the packets to differentiate between malicious and benign traffic. The IDS uses features of timing and network sessions to determine whether the machine that sent a particular packet and its software is, in fact, a combination that is benign, as well as whether or not it resides on a network that is benign. The results of the experiments conducted for this dissertation establish that such system is possible to create and use in an environment of ICS networks. Several features are recognized and selected as means for fingerprinting the hardware and software characteristics of the SCADA system that can be used in pair with machine learning algorithms to allow for a high accuracy detection of intrusions into the ICS network. The results showed a classification accuracy of at least 95% is possible, and as the differences between machines increase, the accuracy increases too

The Proceedings of 15th Australian Information Security Management Conference, 5-6 December, 2017, Edith Cowan University, Perth, Australia

Conference Foreword The annual Security Congress, run by the Security Research Institute at Edith Cowan University, includes the Australian Information Security and Management Conference. Now in its fifteenth year, the conference remains popular for its diverse content and mixture of technical research and discussion papers. The area of information security and management continues to be varied, as is reflected by the wide variety of subject matter covered by the papers this year. The papers cover topics from vulnerabilities in “Internet of Things” protocols through to improvements in biometric identification algorithms and surveillance camera weaknesses. The conference has drawn interest and papers from within Australia and internationally. All submitted papers were subject to a double blind peer review process. Twenty two papers were submitted from Australia and overseas, of which eighteen were accepted for final presentation and publication. We wish to thank the reviewers for kindly volunteering their time and expertise in support of this event. We would also like to thank the conference committee who have organised yet another successful congress. Events such as this are impossible without the tireless efforts of such people in reviewing and editing the conference papers, and assisting with the planning, organisation and execution of the conference. To our sponsors, also a vote of thanks for both the financial and moral support provided to the conference. Finally, thank you to the administrative and technical staff, and students of the ECU Security Research Institute for their contributions to the running of the conference

A deception based framework for the application of deceptive countermeasures in 802.11b wireless networks

The advance of 802.11 b wireless networking has been beset by inherent and in-built security problems. Network security tools that are freely available may intercept network transmissions readily and stealthily, making organisations highly vulnerable to attack. Therefore, it is incumbent upon defending organisations to take initiative and implement proactive defences against common network attacks. Deception is an essential element of effective security that has been widely used in networks to understand attack methods and intrusions. However, little thought has been given to the type and the effectiveness of the deception. Deceptions deployed in nature, the military and in cyberspace were investigated to provide an understanding of how deception may be used in network security. Deceptive network countermeasures and attacks may then be tested on a wireless honeypot as an investigation into the effectiveness of deceptions used in network security. A structured framework, that describes the type of deception and its modus operandi, was utilised to deploy existing honeypot technologies for intrusion detection. Network countermeasures and attacks were mapped to deception types in the framework. This enabled the honeypot to appear as a realistic network and deceive targets in varying deceptive conditions. The investigation was to determine if particular deceptive countermeasures may reduce the effectiveness of particular attacks. The effectiveness of deceptions was measured, and determined by the honeypot\u27s ability to fool the attacking tools used. This was done using brute force network attacks on the wireless honeypot. The attack tools provided quantifiable forensic data from network sniffing, scans, and probes of the wireless honeypot. The aim was to deceive the attack tools into believing a wireless network existed, and contained vulnerabilities that may be further exploited by the naive attacker

Collaboration Enforcement In Mobile Ad Hoc Networks

Mobile Ad hoc NETworks (MANETs) have attracted great research interest in recent years. Among many issues, lack of motivation for participating nodes to collaborate forms a major obstacle to the adoption of MANETs. Many contemporary collaboration enforcement techniques employ reputation mechanisms for nodes to avoid and penalize malicious participants. Reputation information is propagated among participants and updated based on complicated trust relationships to thwart false accusation of benign nodes. The aforementioned strategy suffers from low scalability and is likely to be exploited by adversaries. To address these problems, we first propose a finite state model. With this technique, no reputation information is propagated in the network and malicious nodes cannot cause false penalty to benign hosts. Misbehaving node detection is performed on-demand; and malicious node punishment and avoidance are accomplished by only maintaining reputation information within neighboring nodes. This scheme, however, requires that each node equip with a tamper-proof hardware. In the second technique, no such restriction applies. Participating nodes classify their one-hop neighbors through direct observation and misbehaving nodes are penalized within their localities. Data packets are dynamically rerouted to circumvent selfish nodes. In both schemes, overall network performance is greatly enhanced. Our approach significantly simplifies the collaboration enforcement process, incurs low overhead, and is robust against various malicious behaviors. Simulation results based on different system configurations indicate that the proposed technique can significantly improve network performance with very low communication cost

Networks security: attacks and defense mechanism by designing an intelligent firewall agent

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Günümüzde elektronik banka, elektronik ticaret ve elektronik vergi uygulamaları gibi çok sayıda işlem internet üzerinden gerçekleştirilmektedir. Bu işlemler çeşitli riskler içermekte, kişi ve kurumları çeşitli bilgi sızmalarıyla mesul bırakarak hedef haline getirebilmektedir. Günümüzdeki en yaygın saldırılar "DOS" ve "Spoofing" saldırılarıdır. Bu konuda çok sayıda açık kaynak uygulama olması, saldırganların bu uygulamalarla firmaların kaynaklarına kolayca erişebilmesini sağlamıştır. Çoğu firma klasik güvenlik sistemlerinin bir parçası olan saldırı tespit sistemleri ve güvenlik duvarı kullanmaktadır. Bu sistemlerin kullanılmasına rağmen, klasik sistemlerin işlevsel eksiklikleri vardır. Örneğin güvenlik duvarları zararlı paketlerle normal paketleri birbirinden ayıramazlar. Saldırı tespit sistemleri atakları tespit edebilir, fakat yanlış alarm da verebilmektedir. Bu durum, "DOS" ve "Spoofing" saldırılarına karşı daha etkili bir sistem geliştirme ihtiyacını ortaya çıkarmıştır. Çalışmada güvenlik duvarları ile saldırı tespit sistemlerini bütünleştirilecek zeki bir etmen sistemi ele alınmıştır.A number of transactions like e-banking, e-commerce and e-taxations are carried out over the internet today. Some of these transactions pose security risks and have made various people and organizations become targets of attacks there by exposing them to lots of business liabilities such as data leakages and compliance. Today the most common forms of attacks are DOS and Spoofing attacks and this is mainly due to the availability of a number of open source software which can be used by attacker's to easily gain unauthorized access to company resources and as a result numerous systems have been victims of DOS and spoofing attacks. Most organizations have been deploying traditional network security mechanisms such as firewalls and IDSs to secure their systems. Despite deploying these security measures, networks are still prone to attacks since traditional network security mechanisms have shortcomings for example firewall systems do not have the ability to differentiate between legitimate and illegitimate packets sent to a network. IDSs can detect attacks but give out a lot of false alarms. This has therefore necessitated the need to come up with a much more efficient defense mechanism against these DOS and Spoofing attacks. The study proposed an intelligent firewall agent, and the intelligent firewall agent integrated a firewall and IDS systems for prevention and detection of attacks respectively. Also an expert system was integrated in the IDS so that to record the time an attack happened in seconds by so doing false alerts can be reduced and prevent network attacks