Biblio

This paper presents implementation results of several side channel countermeasures for protecting the scalar multiplication of ECC (Elliptic Curve Cryptography) implemented on an ARM Cortex M3 processor that is used in security sensitive wireless sensor nodes. Our implementation was done for the ECC curves P-256, brainpool256r1, and Ed25519. Investigated countermeasures include Double-And-Add Always, Montgomery Ladder, Scalar Randomization, Randomized Scalar Splitting, Coordinate Randomization, and Randomized Sliding Window. Practical side channel tests for SEMA (Simple Electromagnetic Analysis) and MESD (Multiple Exponent, Single Data) are included. Though more advanced side channel attacks are not evaluated, yet, our results show that an appropriate level of resistance against the most relevant attacks can be reached.

We present a method for key compression in quantumresistant isogeny-based cryptosystems, which allows a reduction in and transmission costs of per-party public information by a factor of two, with no e ect on security. We achieve this reduction by associating a canonical choice of elliptic curve to each j-invariant, and representing elements on the curve as linear combinations with respect to a canonical choice of basis. This method of compressing public information can be applied to numerous isogeny-based protocols, such as key exchange, zero-knowledge identi cation, and public-key encryption. We performed personal computer and ARM implementations of the key exchange with compression and decompression in C and provided timing results, showing the computational cost of key compression and decompression at various security levels. Our results show that isogeny-based cryptosystems achieve by far the smallest possible key sizes among all existing families of post-quantum cryptosystems at practical security levels; e.g. 3073-bit public keys at the quantum 128-bit security level, comparable to (non-quantum) RSA key sizes.

In this paper we analyse possibilities of application of post-quantum code based signature schemes for message authentication purposes. An error-correcting code based digital signature algorithm is presented. There also shown results of computer simulation for this algorithm in case of Reed-Solomon codes and the estimated efficiency of its software implementation. We consider perspectives of error-correcting codes for message authentication and outline further research directions.

In this paper, a dual-field elliptic curve cryptographic processor is proposed to support arbitrary curves within 576-bit in dual field. Besides, two heterogeneous function units are coupled with the processor for the parallel operations in finite field based on the analysis of the characteristics of elliptic curve cryptographic algorithms. To simplify the hardware complexity, the clustering technology is adopted in the processor. At last, a fast Montgomery modular division algorithm and its implementation is proposed based on the Kaliski's Montgomery modular inversion. Using UMC 90-nm CMOS 1P9M technology, the proposed processor occupied 0.86-mm2 can perform the scalar multiplication in 0.34ms in GF(p160) and 0.22ms in GF(2160), respectively. Compared to other elliptic curve cryptographic processors, our design is advantageous in hardware efficiency and speed moderation.

Elliptic Curve Cryptosystems are very much delicate to attacks or physical attacks. This paper aims to correctly implementing the fault injection attack against Elliptic Curve Digital Signature Algorithm. More specifically, the proposed algorithm concerns to fault attack which is implemented to sufficiently alter signature against vigilant periodic sequence algorithm that supports the efficient speed up and security perspectives with most prominent and well known scalar multiplication algorithm for ECDSA. The purpose is to properly injecting attack whether any probable countermeasure threatening the pseudo code is determined by the attack model according to the predefined methodologies. We show the results of our experiment with bits acquire from the targeted implementation to determine the reliability of our attack.

Cloud computing is becoming the main computing model in the future due to its advantages such as high resource utilization rate and save high cost of performance. The public environments is become necessary to secure their storage and transmission against possible attacks such as known-plain-text attack and semantic security. How to ensure the data security and the privacy preserving, however, becomes a huge obstacle to its development. The traditional way to solve Secure Multiparty Computation (SMC) problem is using Trusted Third Party (TTP), however, TTPs are particularly hard to achieve and compute complexity. To protect user's privacy data, the encrypted outsourcing data are generally stored and processed in cloud computing by applying homomorphic encryption. According to above situation, we propose Elliptic Curve Cryptography (ECC) based homomorphic encryption scheme for SMC problem that is dramatically reduced computation and communication cost. It shows that the scheme has advantages in energy consumption, communication consumption and privacy protection through the comparison experiment between ECC based homomorphic encryption and RSA&Paillier encryption algorithm. Further evidence, the scheme of homomorphic encryption scheme based on ECC is applied to the calculation of GPS data of the earthquake and prove it is proved that the scheme is feasible, excellent encryption effect and high security.

Implementation attacks and more specifically Power Analysis (PA) (the dominant type of side channel attack) and fault injection (FA) attacks constitute a pragmatic hazard for scalar multiplication, the main operation behind Elliptic Curve Cryptography. There exists a wide variety of countermeasures attempting to thwart such attacks that, however, few of them explore the potential of alternative number systems like the Residue Number System (RNS). In this paper, we explore the potential of RNS as an PA-FA countermeasure and propose an PA-FA resistant scalar multiplication algorithm and provide an extensive security analysis against the most effective PA-FA techniques. We argue through a security analysis that combining traditional PA-FA countermeasures with lightweight RNS countermeasures can provide strong PA-FA resistance.

Public-key cryptography schemes are widely used due to their high level of security. As a very efficient one among public-key cryptosystems, elliptic curve cryptography (ECC) has been studied for years. Researchers used to improve the efficiency of ECC through point multiplication, which is the most important and complex operation of ECC. In our research, we use special families of curves and prime fields which have special properties. After that, we introduce the instruction set architecture (ISA) extension method to accelerate this algorithm (192-bit private key) and build an ECC\_ASIP model with six new ECC custom instructions. Finally, the ECC\_ASIP model is implemented in a field-programmable gate array (FPGA) platform. The persuasive experiments have been conducted to evaluate the performance of our new model in the aspects of the performance, the code storage space and hardware resources. Experimental results show that our processor improves 69.6% in the execution efficiency and requires only 6.2% more hardware resources.

Hypervisors are the main components for managing virtual machines on cloud computing systems. Thus, the security of hypervisors is very crucial as the whole system could be compromised when just one vulnerability is exploited. In this paper, we assess the vulnerabilities of widely used hypervisors including VMware ESXi, Citrix XenServer and KVM using the NIST 800-115 security testing framework. We perform real experiments to assess the vulnerabilities of those hypervisors using security testing tools. The results are evaluated using weakness information from CWE, and using vulnerability information from CVE. We also compute the severity scores using CVSS information. All vulnerabilities found of three hypervisors will be compared in terms of weaknesses, severity scores and impact. The experimental results showed that ESXi and XenServer have common weaknesses and vulnerabilities whereas KVM has fewer vulnerabilities. In addition, we discover a new vulnerability called HTTP response splitting on ESXi Web interface.

Increasing cyber-security presents an ongoing challenge to security professionals. Research continuously suggests that online users are a weak link in information security. This research explores the relationship between cyber-security and cultural, personality and demographic variables. This study was conducted in four different countries and presents a multi-cultural view of cyber-security. In particular, it looks at how behavior, self-efficacy and privacy attitude are affected by culture compared to other psychological and demographics variables (such as gender and computer expertise). It also examines what kind of data people tend to share online and how culture affects these choices. This work supports the idea of developing personality based UI design to increase users' cyber-security. Its results show that certain personality traits affect the user cyber-security related behavior across different cultures, which further reinforces their contribution compared to cultural effects.

The Software Assurance Metrics and Tool Evaluation (SAMATE) project at the National Institute of Standards and Technology (NIST) has created the Software Assurance Reference Dataset (SARD) to provide researchers and software security assurance tool developers with a set of known security flaws. As part of an empirical evaluation of a runtime monitoring framework, two test suites were executed and monitored, revealing deficiencies which led to a collaboration with the NIST SAMATE team to provide replacements. Test Suites 45 and 46 are analyzed, discussed, and updated to improve accuracy, consistency, preciseness, and automation. Empirical results show metrics such as recall, precision, and F-Measure are all impacted by invalid base assumptions regarding the test suites.

A two-factor authenticated key-agreement scheme for session initiation protocol emerged as a best remedy to overcome the ascribed limitations of the password-based authentication scheme. Recently, Lu et al. proposed an anonymous two-factor authenticated key-agreement scheme for SIP using elliptic curve cryptography. They claimed that their scheme is secure against attacks and achieves user anonymity. Conversely, this paper's keen analysis points out several severe security weaknesses of the Lu et al.'s scheme. In addition, this paper puts forward an enhanced anonymous two-factor mutual authenticated key-agreement scheme for session initiation protocol using elliptic curve cryptography. The security analysis and performance analysis sections demonstrates that the proposed scheme is more robust and efficient than Lu et al.'s scheme.

Recently, various certificate-less signature (CLS) schemes have been developed using bilinear pairing to provide authenticity of message. In 2015, Jia-Lun Tsai proposed a certificate-less pairing based short signature scheme using elliptic curve cryptography (ECC) and prove its security under random oracle. However, it is shown that the scheme is inappropriate for its practical use as there is no message-signature dependency present during signature generation and verification. Thus, the scheme is vulnerable. To overcome these attacks, this paper aims to present a variant of Jia-Lun Tsai's short signature scheme. Our scheme is secured under the hardness of collusion attack algorithm with k traitors (k–-CAA). The performance analysis demonstrates that proposed scheme is efficient than other related signature schemes.

Security patterns are generic solutions that can be applied since early stages of software life to overcome recurrent security weaknesses. Their generic nature and growing number make their choice difficult, even for experts in system design. To help them on the pattern choice, this paper proposes a semi-automatic methodology of classification and the classification itself, which exposes relationships among software weaknesses, security principles and security patterns. It expresses which patterns remove a given weakness with respect to the security principles that have to be addressed to fix the weakness. The methodology is based on seven steps, which anatomize patterns and weaknesses into set of more precise sub-properties that are associated through a hierarchical organization of security principles. These steps provide the detailed justifications of the resulting classification and allow its upgrade. Without loss of generality, this classification has been established for Web applications and covers 185 software weaknesses, 26 security patterns and 66 security principles. Research supported by the industrial chair on Digital Confidence (http://confiance-numerique.clermont-universite.fr/index-en.html).

Information security deals with a large number of subjects like spoofed message detection, audio processing, video surveillance and cyber-attack detections. However the biggest threat for the homeland security is cyber-attacks. Distributed Denial of Service attack is one among them. Interconnected systems such as database server, web server, cloud computing servers etc., are now under threads from network attackers. Denial of service is common attack in the internet which causes problem for both the user and the service providers. Distributed attack sources can be used to enlarge the attack in case of Distributed Denial of Service so that the effect of the attack will be high. Distributed Denial of Service attacks aims at exhausting the communication and computational power of the network by flooding the packets through the network and making malicious traffic in the network. In order to be an effective service the DDoS attack must be detected and mitigated quickly before the legitimate user access the attacker's target. The group of systems that is used to perform the DoS attack is known as the botnets. This paper introduces the overview of the state of art in DDoS attack detection strategies.

This paper presents a framework for privacy-preserving video delivery system to fulfill users' privacy demands. The proposed framework leverages the inference channels in sensitive behavior prediction and object tracking in a video surveillance system for the sequence privacy protection. For such a goal, we need to capture different pieces of evidence which are used to infer the identity. The temporal, spatial and context features are extracted from the surveillance video as the observations to perceive the privacy demands and their correlations. Taking advantage of quantifying various evidence and utility, we let users subscribe videos with a viewer-dependent pattern. We implement a prototype system for off-line and on-line requirements in two typical monitoring scenarios to construct extensive experiments. The evaluation results show that our system can efficiently satisfy users' privacy demands while saving over 25% more video information compared to traditional video privacy protection schemes.

In part I of a three-part series on active surveillance using depth-sensing technology, this paper proposes an algorithm to identify outdoor intrusion activities by monitoring skeletal positions from Microsoft Kinect sensor in real-time. This algorithm implements three techniques to identify a premise intrusion. The first technique observes a boundary line along the wall (or fence) of a surveilled premise for skeletal trespassing detection. The second technique observes the duration of a skeletal object within a region of a surveilled premise for loitering detection. The third technique analyzes the differences in skeletal height to identify wall climbing. Experiment results suggest that the proposed algorithm is able to detect trespassing, loitering and wall climbing at a rate of 70%, 85% and 80% respectively.

Video surveillance has been widely adopted to ensure home security in recent years. Most video encoding standards such as H.264 and MPEG-4 compress the temporal redundancy in a video stream using difference coding, which only encodes the residual image between a frame and its reference frame. Difference coding can efficiently compress a video stream, but it causes side-channel information leakage even though the video stream is encrypted, as reported in this paper. Particularly, we observe that the traffic patterns of an encrypted video stream are different when a user conducts different basic activities of daily living, which must be kept private from third parties as obliged by HIPAA regulations. We also observe that by exploiting this side-channel information leakage, attackers can readily infer a user's basic activities of daily living based on only the traffic size data of an encrypted video stream. We validate such an attack using two off-the-shelf cameras, and the results indicate that the user's basic activities of daily living can be recognized with a high accuracy.

Multimedia authentication is an integral part of multimedia signal processing in many real-time and security sensitive applications, such as video surveillance. In such applications, a full-fledged video digital rights management (DRM) mechanism is not applicable due to the real time requirement and the difficulties in incorporating complicated license/key management strategies. This paper investigates the potential of multimedia authentication from a brand new angle by employing hardware-based security primitives, such as physical unclonable functions (PUFs). We show that the hardware security approach is not only capable of accomplishing the authentication for both the hardware device and the multimedia stream but, more importantly, introduce minimum performance, resource, and power overhead. We justify our approach using a prototype PUF implementation on Xilinx FPGA boards. Our experimental results on the real hardware demonstrate the high security and low overhead in multimedia authentication obtained by using hardware security approaches.

This paper address the problem of shadow detection and removal in traffic vision analysis. Basically, the presence of the shadow in the traffic sequences is imminent, and therefore leads to errors at segmentation stage and often misclassified as an object region or as a moving object. This paper presents a shadow removal method, based on both color and texture features, aiming to contribute to retrieve efficiently the moving objects whose detection are usually under the influence of cast-shadows. Additionally, in order to get a shadow-free foreground segmentation image, a morphology reconstruction algorithm is used to recover the foreground disturbed by shadow removal. Once shadows are detected, an automatic shadow removal model is proposed based on the information retrieved from the histogram shape. Experimental results on a real traffic sequence is presented to test the proposed approach and to validate the algorithm's performance.

H.264/SVC (Scalable Video Coding) codestreams, which consist of a single base layer and multiple enhancement layers, are designed for quality, spatial, and temporal scalabilities. They can be transmitted over networks of different bandwidths and seamlessly accessed by various terminal devices. With a huge amount of video surveillance and various devices becoming an integral part of the security infrastructure, the industry is currently starting to use the SVC standard to process digital video for surveillance applications such that clients with different network bandwidth connections and display capabilities can seamlessly access various SVC surveillance (sub)codestreams. In order to guarantee the trustworthiness and integrity of received SVC codestreams, engineers and researchers have proposed several authentication schemes to protect video data. However, existing algorithms cannot simultaneously satisfy both efficiency and robustness for SVC surveillance codestreams. Hence, in this article, a highly efficient and robust authentication scheme, named TrustSSV (Trust Scalable Surveillance Video), is proposed. Based on quality/spatial scalable characteristics of SVC codestreams, TrustSSV combines cryptographic and content-based authentication techniques to authenticate the base layer and enhancement layers, respectively. Based on temporal scalable characteristics of surveillance codestreams, TrustSSV extracts, updates, and authenticates foreground features for each access unit dynamically with background model support. Using SVC test sequences, our experimental results indicate that the scheme is able to distinguish between content-preserving and content-changing manipulations and to pinpoint tampered locations. Compared with existing schemes, the proposed scheme incurs very small computation and communication costs.

Video surveillance, closed-circuit TV and IP-camera systems became virtually omnipresent and indispensable for many organizations, businesses, and users. Their main purpose is to provide physical security, increase safety, and prevent crime. They also became increasingly complex, comprising many communication means, embedded hardware and non-trivial firmware. However, most research to date focused mainly on the privacy aspects of such systems, and did not fully address their issues related to cyber-security in general, and visual layer (i.e., imagery semantics) attacks in particular. In this paper, we conduct a systematic review of existing and novel threats in video surveillance, closed-circuit TV and IP-camera systems based on publicly available data. The insights can then be used to better understand and identify the security and the privacy risks associated with the development, deployment and use of these systems. We study existing and novel threats, along with their existing or possible countermeasures, and summarize this knowledge into a comprehensive table that can be used in a practical way as a security checklist when assessing cyber-security level of existing or new CCTV designs and deployments. We also provide a set of recommendations and mitigations that can help improve the security and privacy levels provided by the hardware, the firmware, the network communications and the operation of video surveillance systems. We hope the findings in this paper will provide a valuable knowledge of the threat landscape that such systems are exposed to, as well as promote further research and widen the scope of this field beyond its current boundaries.

With recent advances in consumer electronics and the increasingly urgent need for public security, camera networks have evolved from their early role of providing simple and static monitoring to current complex systems capable of obtaining extensive video information for intelligent processing, such as target localization, identification, and tracking. In all cases, it is of vital importance that the optimal camera configuration (i.e., optimal location, orientation, etc.) is determined before cameras are deployed as a suboptimal placement solution will adversely affect intelligent video surveillance and video analytic algorithms. The optimal configuration may also provide substantial savings on the total number of cameras required to achieve the same level of utility. In this article, we examine most, if not all, of the recent approaches (post 2000) addressing camera placement in a structured manner. We believe that our work can serve as a first point of entry for readers wishing to start researching into this area or engineers who need to design a camera system in practice. To this end, we attempt to provide a complete study of relevant formulation strategies and brief introductions to most commonly used optimization techniques by researchers in this field. We hope our work to be inspirational to spark new ideas in the field.

This paper evaluates a new video surveillance platform presented in a previous study, through an abandoned object detection task. The proposed platform has a function of automated detection and alerting, which is still a big challenge for a machine algorithm due to its recall-precision tradeoff problem. To achieve both high recall and high precision simultaneously, a hybrid approach using crowdsourcing after image analysis is proposed. This approach, however, is still not clear about what extent it can improve detection accuracy and raise quicker alerts. In this paper, the experiment is conducted for abandoned object detection, as one of the most common surveillance tasks. The results show that detection accuracy was improved from 50% (without crowdsourcing) to stable 95-100% (with crowdsourcing) by majority vote of 7 crowdworkers for each task. In contrast, alert time issue still remains open to further discussion since at least 7+ minutes are required to get the best performance.

This paper explores fully integrated inductive voltage regulators (FIVR) as a technique to improve the side channel resistance of encryption engines. We propose security aware design modes for low passive FIVR to improve robustness of an encryption-engine against statistical power attacks in time and frequency domain. A Correlation Power Analysis is used to attack a 128-bit AES engine synthesized in 130nm CMOS. The original design requires \textasciitilde250 Measurements to Disclose (MTD) the 1st byte of key; but with security-aware FIVR, the CPA was unsuccessful even after 20,000 traces. We present a reversibility based threat model for the FIVR-based protection improvement and show the robustness of security aware FIVR against such threat.