Visible to the public Biblio

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Yajin Zhou, Xuxian Jiang.  2012.  Dissecting Android Malware: Characterization and Evolution. Security and Privacy (SP), 2012 IEEE Symposium on. :95-109.

The popularity and adoption of smart phones has greatly stimulated the spread of mobile malware, especially on the popular platforms such as Android. In light of their rapid growth, there is a pressing need to develop effective solutions. However, our defense capability is largely constrained by the limited understanding of these emerging mobile malware and the lack of timely access to related samples. In this paper, we focus on the Android platform and aim to systematize or characterize existing Android malware. Particularly, with more than one year effort, we have managed to collect more than 1,200 malware samples that cover the majority of existing Android malware families, ranging from their debut in August 2010 to recent ones in October 2011. In addition, we systematically characterize them from various aspects, including their installation methods, activation mechanisms as well as the nature of carried malicious payloads. The characterization and a subsequent evolution-based study of representative families reveal that they are evolving rapidly to circumvent the detection from existing mobile anti-virus software. Based on the evaluation with four representative mobile security software, our experiments show that the best case detects 79.6% of them while the worst case detects only 20.2% in our dataset. These results clearly call for the need to better develop next-generation anti-mobile-malware solutions.

Varadarajan, P., Crosby, G..  2014.  Implementing IPsec in Wireless Sensor Networks. New Technologies, Mobility and Security (NTMS), 2014 6th International Conference on. :1-5.

There is an increasing need for wireless sensor networks (WSNs) to be more tightly integrated with the Internet. Several real world deployment of stand-alone wireless sensor networks exists. A number of solutions have been proposed to address the security threats in these WSNs. However, integrating WSNs with the Internet in such a way as to ensure a secure End-to-End (E2E) communication path between IPv6 enabled sensor networks and the Internet remains an open research issue. In this paper, the 6LoWPAN adaptation layer was extended to support both IPsec's Authentication Header (AH) and Encapsulation Security Payload (ESP). Thus, the communication endpoints in WSNs are able to communicate securely using encryption and authentication. The proposed AH and ESP compressed headers performance are evaluated via test-bed implementation in 6LoWPAN for IPv6 communications on IEEE 802.15.4 networks. The results confirm the possibility of implementing E2E security in IPv6 enabled WSNs to create a smooth transition between WSNs and the Internet. This can potentially play a big role in the emerging "Internet of Things" paradigm.

Oberle, A., Larbig, P., Kuntze, N., Rudolph, C..  2014.  Integrity based relationships and trustworthy communication between network participants. Communications (ICC), 2014 IEEE International Conference on. :610-615.

Establishing trust relationships between network participants by having them prove their operating system's integrity via a Trusted Platform Module (TPM) provides interesting approaches for securing local networks at a higher level. In the introduced approach on OSI layer 2, attacks carried out by already authenticated and participating nodes (insider threats) can be detected and prevented. Forbidden activities and manipulations in hard- and software, such as executing unknown binaries, loading additional kernel modules or even inserting unauthorized USB devices, are detected and result in an autonomous reaction of each network participant. The provided trust establishment and authentication protocol operates independently from upper protocol layers and is optimized for resource constrained machines. Well known concepts of backbone architectures can maintain the chain of trust between different kinds of network types. Each endpoint, forwarding and processing unit monitors the internal network independently and reports misbehaviours autonomously to a central instance in or outside of the trusted network.

Pawlowski, M.P., Jara, A.J., Ogorzalek, M.J..  2014.  Extending Extensible Authentication Protocol over IEEE 802.15.4 Networks. Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), 2014 Eighth International Conference on. :340-345.

Internet into our physical world and making it present everywhere. This evolution is also raising challenges in issues such as privacy, and security. For that reason, this work is focused on the integration and lightweight adaptation of existing authentication protocols, which are able also to offer authorization and access control functionalities. In particular, this work is focused on the Extensible Authentication Protocol (EAP). EAP is widely used protocol for access control in local area networks such Wireless (802.11) and wired (802.3). This work presents an integration of the EAP frame into IEEE 802.15.4 frames, demonstrating that EAP protocol and some of its mechanisms are feasible to be applied in constrained devices, such as the devices that are populating the IoT networks.

Jan, M.A., Nanda, P., Xiangjian He, Zhiyuan Tan, Ren Ping Liu.  2014.  A Robust Authentication Scheme for Observing Resources in the Internet of Things Environment. Trust, Security and Privacy in Computing and Communications (TrustCom), 2014 IEEE 13th International Conference on. :205-211.

The Internet of Things is a vision that broadens the scope of the internet by incorporating physical objects to identify themselves to the participating entities. This innovative concept enables a physical device to represent itself in the digital world. There are a lot of speculations and future forecasts about the Internet of Things devices. However, most of them are vendor specific and lack a unified standard, which renders their seamless integration and interoperable operations. Another major concern is the lack of security features in these devices and their corresponding products. Most of them are resource-starved and unable to support computationally complex and resource consuming secure algorithms. In this paper, we have proposed a lightweight mutual authentication scheme which validates the identities of the participating devices before engaging them in communication for the resource observation. Our scheme incurs less connection overhead and provides a robust defence solution to combat various types of attacks.

Abgrall, E., le Traon, Y., Gombault, S., Monperrus, M..  2014.  Empirical Investigation of the Web Browser Attack Surface under Cross-Site Scripting: An Urgent Need for Systematic Security Regression Testing. Software Testing, Verification and Validation Workshops (ICSTW), 2014 IEEE Seventh International Conference on. :34-41.

One of the major threats against web applications is Cross-Site Scripting (XSS). The final target of XSS attacks is the client running a particular web browser. During this last decade, several competing web browsers (IE, Netscape, Chrome, Firefox) have evolved to support new features. In this paper, we explore whether the evolution of web browsers is done using systematic security regression testing. Beginning with an analysis of their current exposure degree to XSS, we extend the empirical study to a decade of most popular web browser versions. We use XSS attack vectors as unit test cases and we propose a new method supported by a tool to address this XSS vector testing issue. The analysis on a decade releases of most popular web browsers including mobile ones shows an urgent need of XSS regression testing. We advocate the use of a shared security testing benchmark as a good practice and propose a first set of publicly available XSS vectors as a basis to ensure that security is not sacrificed when a new version is delivered.

Kampanakis, P., Perros, H., Beyene, T..  2014.  SDN-based solutions for Moving Target Defense network protection. A World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2014 IEEE 15th International Symposium on. :1-6.

Software-Defined Networking (SDN) allows network capabilities and services to be managed through a central control point. Moving Target Defense (MTD) on the other hand, introduces a constantly adapting environment in order to delay or prevent attacks on a system. MTD is a use case where SDN can be leveraged in order to provide attack surface obfuscation. In this paper, we investigate how SDN can be used in some network-based MTD techniques. We first describe the advantages and disadvantages of these techniques, the potential countermeasures attackers could take to circumvent them, and the overhead of implementing MTD using SDN. Subsequently, we study the performance of the SDN-based MTD methods using Cisco's One Platform Kit and we show that they significantly increase the attacker's overheads.

Haddadi, F., Morgan, J., Filho, E.G., Zincir-Heywood, A.N..  2014.  Botnet Behaviour Analysis Using IP Flows: With HTTP Filters Using Classifiers. Advanced Information Networking and Applications Workshops (WAINA), 2014 28th International Conference on. :7-12.

Botnets are one of the most destructive threats against the cyber security. Recently, HTTP protocol is frequently utilized by botnets as the Command and Communication (C&C) protocol. In this work, we aim to detect HTTP based botnet activity based on botnet behaviour analysis via machine learning approach. To achieve this, we employ flow-based network traffic utilizing NetFlow (via Softflowd). The proposed botnet analysis system is implemented by employing two different machine learning algorithms, C4.5 and Naive Bayes. Our results show that C4.5 learning algorithm based classifier obtained very promising performance on detecting HTTP based botnet activity.

Zhenlong Yuan, Cuilan Du, Xiaoxian Chen, Dawei Wang, Yibo Xue.  2014.  SkyTracer: Towards fine-grained identification for Skype traffic via sequence signatures. Computing, Networking and Communications (ICNC), 2014 International Conference on. :1-5.

Skype has been a typical choice for providing VoIP service nowadays and is well-known for its broad range of features, including voice-calls, instant messaging, file transfer and video conferencing, etc. Considering its wide application, from the viewpoint of ISPs, it is essential to identify Skype flows and thus optimize network performance and forecast future needs. However, in general, a host is likely to run multiple network applications simultaneously, which makes it much harder to classify each and every Skype flow from mixed traffic exactly. Especially, current techniques usually focus on host-level identification and do not have the ability to identify Skype traffic at the flow-level. In this paper, we first reveal the unique sequence signatures of Skype UDP flows and then implement a practical online system named SkyTracer for precise Skype traffic identification. To the best of our knowledge, this is the first time to utilize the strong sequence signatures to carry out early identification of Skype traffic. The experimental results show that SkyTracer can achieve very high accuracy at fine-grained level in identifying Skype traffic.

Holm, H..  2014.  Signature Based Intrusion Detection for Zero-Day Attacks: (Not) A Closed Chapter? System Sciences (HICSS), 2014 47th Hawaii International Conference on. :4895-4904.

A frequent claim that has not been validated is that signature based network intrusion detection systems (SNIDS) cannot detect zero-day attacks. This paper studies this property by testing 356 severe attacks on the SNIDS Snort, configured with an old official rule set. Of these attacks, 183 attacks are zero-days' to the rule set and 173 attacks are theoretically known to it. The results from the study show that Snort clearly is able to detect zero-days' (a mean of 17% detection). The detection rate is however on overall greater for theoretically known attacks (a mean of 54% detection). The paper then investigates how the zero-days' are detected, how prone the corresponding signatures are to false alarms, and how easily they can be evaded. Analyses of these aspects suggest that a conservative estimate on zero-day detection by Snort is 8.2%.

Kaur, R., Singh, M..  2014.  A Survey on Zero-Day Polymorphic Worm Detection Techniques. Communications Surveys Tutorials, IEEE. 16:1520-1549.

Zero-day polymorphic worms pose a serious threat to the Internet security. With their ability to rapidly propagate, these worms increasingly threaten the Internet hosts and services. Not only can they exploit unknown vulnerabilities but can also change their own representations on each new infection or can encrypt their payloads using a different key per infection. They have many variations in the signatures of the same worm thus, making their fingerprinting very difficult. Therefore, signature-based defenses and traditional security layers miss these stealthy and persistent threats. This paper provides a detailed survey to outline the research efforts in relation to detection of modern zero-day malware in form of zero-day polymorphic worms.

B. C. M. Cappers, J. J. van Wijk.  2015.  "SNAPS: Semantic network traffic analysis through projection and selection". 2015 IEEE Symposium on Visualization for Cyber Security (VizSec). :1-8.

Most network traffic analysis applications are designed to discover malicious activity by only relying on high-level flow-based message properties. However, to detect security breaches that are specifically designed to target one network (e.g., Advanced Persistent Threats), deep packet inspection and anomaly detection are indispensible. In this paper, we focus on how we can support experts in discovering whether anomalies at message level imply a security risk at network level. In SNAPS (Semantic Network traffic Analysis through Projection and Selection), we provide a bottom-up pixel-oriented approach for network traffic analysis where the expert starts with low-level anomalies and iteratively gains insight in higher level events through the creation of multiple selections of interest in parallel. The tight integration between visualization and machine learning enables the expert to iteratively refine anomaly scores, making the approach suitable for both post-traffic analysis and online monitoring tasks. To illustrate the effectiveness of this approach, we present example explorations on two real-world data sets for the detection and understanding of potential Advanced Persistent Threats in progress.

Nunes, E., Kulkarni, N., Shakarian, P., Ruef, A., Little, J..  2015.  Cyber-deception and attribution in capture-the-flag exercises. 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). :962–965.

Attributing the culprit of a cyber-attack is widely considered one of the major technical and policy challenges of cyber-security. The lack of ground truth for an individual responsible for a given attack has limited previous studies. Here, we overcome this limitation by leveraging DEFCON capture-the-flag (CTF) exercise data where the actual ground-truth is known. In this work, we use various classification techniques to identify the culprit in a cyberattack and find that deceptive activities account for the majority of misclassified samples. We also explore several heuristics to alleviate some of the misclassification caused by deception.

Shanthi, K., Seenivasan, D..  2015.  Detection of botnet by analyzing network traffic flow characteristics using open source tools. 2015 IEEE 9th International Conference on Intelligent Systems and Control (ISCO). :1–5.

Botnets are emerging as the most serious cyber threat among different forms of malware. Today botnets have been facilitating to launch many cybercriminal activities like DDoS, click fraud, phishing attacks etc. The main purpose of botnet is to perform massive financial threat. Many large organizations, banks and social networks became the target of bot masters. Botnets can also be leased to motivate the cybercriminal activities. Recently several researches and many efforts have been carried out to detect bot, C&C channels and bot masters. Ultimately bot maters also strengthen their activities through sophisticated techniques. Many botnet detection techniques are based on payload analysis. Most of these techniques are inefficient for encrypted C&C channels. In this paper we explore different categories of botnet and propose a detection methodology to classify bot host from the normal host by analyzing traffic flow characteristics based on time intervals instead of payload inspection. Due to that it is possible to detect botnet activity even encrypted C&C channels are used.

Wakchaure, M., Sarwade, S., Siddavatam, I..  2016.  Reconnaissance of Industrial Control System by deep packet inspection. 2016 IEEE International Conference on Engineering and Technology (ICETECH). :1093–1096.

Industrial Control System (ICS) consists of large number of electronic devices connected to field devices to execute the physical processes. Communication network of ICS supports wide range of packet based applications. A growing issue with network security and its impact on ICS have highlighted some fundamental risks to critical infrastructure. To address network security issues for ICS a clear understanding of security specific defensive countermeasures is required. Reconnaissance of ICS network by deep packet inspection (DPI) consists analysis of the contents of the captured packets in order to get accurate measures of process that uses specific countermeasure to create an aggregated posture. In this paper we focus on novel approach by presenting a technique with captured network traffic. This technique is capable to identify the protocols and extract different features for classification of traffic based on network protocol, header information and payload to understand the whole architecture of complex system. Here we have segregated possible types of attacks on ICS.

Weckstén, M., Frick, J., Sjöström, A., Järpe, E..  2016.  A novel method for recovery from Crypto Ransomware infections. 2016 2nd IEEE International Conference on Computer and Communications (ICCC). :1354–1358.

Extortion using digital platforms is an increasing form of crime. A commonly seen problem is extortion in the form of an infection of a Crypto Ransomware that encrypts the files of the target and demands a ransom to recover the locked data. By analyzing the four most common Crypto Ransomwares, at writing, a clear vulnerability is identified; all infections rely on tools available on the target system to be able to prevent a simple recovery after the attack has been detected. By renaming the system tool that handles shadow copies it is possible to recover from infections from all four of the most common Crypto Ransomwares. The solution is packaged in a single, easy to use script.

Zalbina, M. R., Septian, T. W., Stiawan, D., Idris, M. Y., Heryanto, A., Budiarto, R..  2017.  Payload recognition and detection of Cross Site Scripting attack. 2017 2nd International Conference on Anti-Cyber Crimes (ICACC). :172–176.

Web Application becomes the leading solution for the utilization of systems that need access globally, distributed, cost-effective, as well as the diversity of the content that can run on this technology. At the same time web application security have always been a major issue that must be considered due to the fact that 60% of Internet attacks targeting web application platform. One of the biggest impacts on this technology is Cross Site Scripting (XSS) attack, the most frequently occurred and are always in the TOP 10 list of Open Web Application Security Project (OWASP). Vulnerabilities in this attack occur in the absence of checking, testing, and the attention about secure coding practices. There are several alternatives to prevent the attacks that associated with this threat. Network Intrusion Detection System can be used as one solution to prevent the influence of XSS Attack. This paper investigates the XSS attack recognition and detection using regular expression pattern matching and a preprocessing method. Experiments are conducted on a testbed with the aim to reveal the behaviour of the attack.

Priya, S. R., Swetha, P., Srigayathri, D., Sumedha, N., Priyatharishini, M..  2017.  Hardware malicious circuit identification using self referencing approach. 2017 International conference on Microelectronic Devices, Circuits and Systems (ICMDCS). :1–5.

Robust Trojans are inserted in outsourced products resulting in security vulnerabilities. Post-silicon testing is done mandatorily to detect such malicious inclusions. Logic testing becomes obsolete for larger circuits with sequential Trojans. For such cases, side channel analysis is an effective approach. The major challenge with the side channel analysis is reduction in hardware Trojan detection sensitivity due to process variation (process variation could lead to false positives and false negatives and it is unavoidable during a manufacturing stage). In this paper Self Referencing method is proposed that measures leakage power of the circuit at four different time windows that hammers the Trojan into triggering and also help to identify/eliminate false positives/false negatives due to process variation.

Fotiou, N., Siris, V. A., Xylomenos, G., Polyzos, G. C., Katsaros, K. V., Petropoulos, G..  2017.  Edge-ICN and its application to the Internet of Things. 2017 IFIP Networking Conference (IFIP Networking) and Workshops. :1–6.

While research on Information-Centric Networking (ICN) flourishes, its adoption seems to be an elusive goal. In this paper we propose Edge-ICN: a novel approach for deploying ICN in a single large network, such as the network of an Internet Service Provider. Although Edge-ICN requires nothing beyond an SDN-based network supporting the OpenFlow protocol, with ICN-aware nodes only at the edges of the network, it still offers the same benefits as a clean-slate ICN architecture but without the deployment hassles. Moreover, by proxying legacy traffic and transparently forwarding it through the Edge-ICN nodes, all existing applications can operate smoothly, while offering significant advantages to applications such as native support for scalable anycast, multicast, and multi-source forwarding. In this context, we show how the proposed functionality at the edge of the network can specifically benefit CoAP-based IoT applications. Our measurements show that Edge-ICN induces on average the same control plane overhead for name resolution as a centralized approach, while also enabling IoT applications to build on anycast, multicast, and multi-source forwarding primitives.

Hendriks, L., Velan, P., Schmidt, R. d O., Boer, P. T. de, Pras, A..  2017.  Threats and surprises behind IPv6 extension headers. 2017 Network Traffic Measurement and Analysis Conference (TMA). :1–9.

The concept of Extension Headers, newly introduced with IPv6, is elusive and enables new types of threats in the Internet. Simply dropping all traffic containing any Extension Header - a current practice by operators-seemingly is an effective solution, but at the cost of possibly dropping legitimate traffic as well. To determine whether threats indeed occur, and evaluate the actual nature of the traffic, measurement solutions need to be adapted. By implementing these specific parsing capabilities in flow exporters and performing measurements on two different production networks, we show it is feasible to quantify the metrics directly related to these threats, and thus allow for monitoring and detection. Analysing the traffic that is hidden behind Extension Headers, we find mostly benign traffic that directly affects end-user QoE: simply dropping all traffic containing Extension Headers is thus a bad practice with more consequences than operators might be aware of.

Khan, J..  2017.  Vehicle Network Security Testing. 2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS). :119–123.

In-vehicle networks like Controller Area Network, FlexRay, Ethernet are now subjected to huge security threats where unauthorized entities can take control of the whole vehicle. This can pose very serious threats including accidents. Security features like encryption, message authentication are getting implemented in vehicle networks to counteract these issues. This paper is proposing a set of novel validation techniques to ensure that vehicle network security is fool proof. Security validation against requirements, security validation using white box approach, black box approach and grey box approaches are put forward. Test system architecture, validation of message authentication, decoding the patterns from vehicle network data, using diagnostics as a security loophole, V2V V2X loopholes, gateway module security testing are considered in detail. Aim of this research paper is to put forward a set of tools and methods for finding and reporting any security loopholes in the in-vehicle network security implementation.

Gonzalez, D., Hayajneh, T..  2017.  Detection and Prevention of Crypto-Ransomware. 2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON). :472–478.

Crypto-ransomware is a challenging threat that ciphers a user's files while hiding the decryption key until a ransom is paid by the victim. This type of malware is a lucrative business for cybercriminals, generating millions of dollars annually. The spread of ransomware is increasing as traditional detection-based protection, such as antivirus and anti-malware, has proven ineffective at preventing attacks. Additionally, this form of malware is incorporating advanced encryption algorithms and expanding the number of file types it targets. Cybercriminals have found a lucrative market and no one is safe from being the next victim. Encrypting ransomware targets business small and large as well as the regular home user. This paper discusses ransomware methods of infection, technology behind it and what can be done to help prevent becoming the next victim. The paper investigates the most common types of crypto-ransomware, various payload methods of infection, typical behavior of crypto ransomware, its tactics, how an attack is ordinarily carried out, what files are most commonly targeted on a victim's computer, and recommendations for prevention and safeguards are listed as well.

Zimba, A., Wang, Z., Chen, H..  2017.  Reasoning Crypto Ransomware Infection Vectors with Bayesian Networks. 2017 IEEE International Conference on Intelligence and Security Informatics (ISI). :149–151.

Ransomware techniques have evolved over time with the most resilient attacks making data recovery practically impossible. This has driven countermeasures to shift towards recovery against prevention but in this paper, we model ransomware attacks from an infection vector point of view. We follow the basic infection chain of crypto ransomware and use Bayesian network statistics to infer some of the most common ransomware infection vectors. We also employ the use of attack and sensor nodes to capture uncertainty in the Bayesian network.

McLaren, P., Russell, G., Buchanan, B..  2017.  Mining Malware Command and Control Traces. 2017 Computing Conference. :788–794.

Detecting botnets and advanced persistent threats is a major challenge for network administrators. An important component of such malware is the command and control channel, which enables the malware to respond to controller commands. The detection of malware command and control channels could help prevent further malicious activity by cyber criminals using the malware. Detection of malware in network traffic is traditionally carried out by identifying specific patterns in packet payloads. Now bot writers encrypt the command and control payloads, making pattern recognition a less effective form of detection. This paper focuses instead on an effective anomaly based detection technique for bot and advanced persistent threats using a data mining approach combined with applied classification algorithms. After additional tuning, the final test on an unseen dataset, false positive rates of 0% with malware detection rates of 100% were achieved on two examined malware threats, with promising results on a number of other threats.

Schürmann, D., Zengen, G. V., Priedigkeit, M., Wolf, L..  2017.  \#x003BC;DTNSec: A Security Layer for Disruption-Tolerant Networks on Microcontrollers. 2017 16th Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net). :1–7.

We introduce $μ$DTNSec, the first fully-implemented security layer for Delay/Disruption-Tolerant Networks (DTN) on microcontrollers. It provides protection against eavesdropping and Man-in-the-Middle attacks that are especially easy in these networks. Following the Store-Carry-Forward principle of DTNs, an attacker can simply place itself on the route between source and destination. Our design consists of asymmetric encryption and signatures with Elliptic Curve Cryptography and hardware-backed symmetric encryption with the Advanced Encryption Standard. $μ$DTNSec has been fully implemented as an extension to $μ$DTN on Contiki OS and is based on the Bundle Protocol specification. Our performance evaluation shows that the choice of the curve (secp128r1, secp192r1, secp256r1) dominates the influence of the payload size. We also provide energy measurements for all operations to show the feasibility of our security layer on energy-constrained devices.